Bank Indonesia, Financial Stability Review No 6 - March 2006

The Financial Stability Review (FSR) is one of the avenues through which

Bank Indonesia achieves its mission ≈to safeguard the stability of the Indonesian Rupiah by

maintaining monetary and financial system stability towards sustainable economic

growth.Δ

Published by:

Bank Indonesia

Jl. MH Thamrin No.2, Jakarta

Indonesia

This edition was launched in September 2006 and is based on data and information available by the end of June 2006, except

stated otherwise. With the exception of those stated in graphs and tables, all data sources are from Bank Indonesia.

The pdf format is downloadable at http://www.bi.go.id

Any inquiries, comments and feedback please contact :

Bank Indonesia

Directorate of Banking Research and Regulation

Financial System Stability Bureau

Jl.MH Thamrin No.2, Jakarta, Indonesia

Phone : (+62-21) 381 7353, 8336

Fax : (+62-21) 2311672

E-mail : [email protected]

FSR is published bi-annually with the objectives:

- To analyze potential risks confronting domestic financial system;

- To recommend policies to relevant authorities for promoting a stable financial system; and

- To foster market discipline and public knowledge on domestic and global financial system stability

issues.

Financial Stability ReviewI - 2006

( No. 7, September 2006 )

iii

Foreword vi

Chapter 1 Overview 3

Sources of Potential Instability 4

The Impact of Potential Instability on the

Financial System 6

Measures to Mitigate Instability Risk 7

Prospect of Financial System Stability 9

Chapter 2 Macroeconomy 13

International Economy 13

Domestic Economy 15

Chapter 3 Corporate and Household Sector 23

Credit Risk in the Corporate Sector 23

Credit Risk in the Household Sector 25

Chapter 4 Financial Sector 31

Banking 31

Intermediary Function 32

Credit Risk 34

Provisions 42

Liquidity Risk 42

Market Risk 45

Profitability 46

Capital 47

Non Bank Financial Institution 50

Multi-finance Companies 50

Business Volume 50

Source of Funds 51

Profitability and Solvency 52

Capital Market 52

Equity Market 52

Table of Contents

Equity Market Performance 53

Mutual Funds 55

Performance of Mutual Funds 56

Bonds Market 57

Government Bonds 57

Corporate Bonds 58

Box 4.1. Impacts of the Earthquake in Yogyakarta

on Financial Stability 38

Box 4.2. The Threat of Hot Mudflow in Porong-

Sidoarjo on Financial Stability 40

Box 4.3. The Impact of Limited Insurance Scheme

Implementation 44

Box 4.4. Credit Information Bureau and Debtor

Information System 49

Chapter 5 Financial Infrastructure 59

Payment System 59

Development of Payment System RTGS

and Clearing 59

Card-Based Payments 60

Payment System Development 61

Box 5.1. 10% Minimum Payment For Credit Cards 62

Article

Article 1 Hedge Fund Activities in Developing

Countries and Effort of Maintain

Financial Stability 3a

Article 2 The Efficiency of Indonesian Foreign

Exchange Market 13a

Glossary, Abbreviation, Appendix 27a

iv

List Graphs and Tables

Table

1.1. Financial Soundness Indicators 3

2.1. Global Economic Indicators 14

2.2. Policy Package 16

2.3. Growth of Gross Domestic Product 17

2.4. Balance of Payment 19

4.1. Assumptions and Scenarios 45

4.2. CAR - BI Rate Increased Scenario 46

4.3. CAR - BI Rate Declined Scenario 46

4.4. CAR - IDR Depreciation Scenario 46

Tables in Boxes :

4.1.1. DIY Banking Statistic ( April 2006 ) 38

4.1.2. Bank Loans and Deposits in Yogyakarta

( April 2006 ) 39

4.2.1. Account Distribution 45

2.1. World Commodities Price 14

2.2. Trend of Global Interest Rate 14

2.3. Trend of Regional & Global Index 15

2.4. Trend of PE Ratio 15

2.5. Capacity Utilization and Retail Sales 16

2.6. Inflation, BI Rate and SBI 17

2.7. Exchange Rate IDR to US $ 18

2.8. Country Risk of Indonesia 19

2.9. Expected Inflation for the Next 6 Months 20

3.1. Amount and NPL of Working Capital

& Investment Loan 23

3.2. Corporate Financial Indicator 24

3.3. Corporate Loss Ratio 24

3.4. Growth of ROA and ROE 24

3.5. Cash Flow 24

3.6. Corporate Leverage 25

3.7. Business Survey 25

3.8. Plan of Investment 25

3.9. Consumer Loan & NPL 26

3.10. Residential Inflation 26

3.11. Lay-off 26

3.12. Mortgages (House & Apartment) 26

3.13. Consumer Confidence Index 27

3.14. Consumer Expectation for the Next 6 Months 27

Graphs

v

4.1. Credit growth, Deposit, and LDR 31

4.2. Sectoral Credit Growth 32

4.3. Growth of Property Loans 32

4.4. Type of Credit 33

4.5. Credit Growth per Type 33

4.6. Growth of Loans to SMEs 34

4.7. Gross NPL 34

4.8. Net NPL 34

4.9. Non Performing Loans 35

4.10. Non Performing Loans - Foreign Currency

& Rupiah Denomination 35

4.11. Non Performing Loans - per Business Sector 35

4.12. NPL of Trading and Manufacturing 35

4.13. NPL - Industry Manufacturing 36

4.14. Growth of NPL as of type 36

4.15. Gross NPL of SMES 36

4.16. Gross NPL 37

4.17. Loans, NPL and Provision 42

4.18. Liquidity Ratio 42

4.19. Deposits 43

4.20. Deposit Structure 43

4.21. Deposits Structure - Per Ownership 43

4.22. Deposit Structure - Per Nominal Amount 43

4.23. Deposit - Lending Rate Spread 46

4.24. NII and Certificate of Bank Indonesia Rate 46

4.25. Cost Efficiency Ratio and ROA 47

4.26. Komposisi Pendapatan Bunga 47

4.27. Revenue Structure of 15 Large Banks 47

4.28. Capital Adeguay Ratio 48

4.29. Tier 1 to Risk Weighted Asset (June 2006) 48

4.30. CAR as of Bank Peer 48

4.31. Financial Structure of Multifinance Companies 50

4.32. Securities and Loan Loss Provisions 51

4.33. Source of Funds 51

4.34. Funding Structure 51

4.35. Debt/Assets, and Debt/Financing Ratios 52

4.36. Capital/Financing 52

4.37. Jakarta Composite Index and Volume of Shares 53

4.38. Foreign Investors Transactions 53

4.39. Volatility of JCI 54

4.40. JCI and Market Capitalization 54

4.41. Foreign Investors Trading 54

4.42. Sectoral Index and JCI 55

4.43. Mutual Fund and Net Asset Values 56

4.44. Type of Mutual Funds 56

4.45. Bond Prices - Selected Series 57

4.46. Yield Spread of Selected Asian Countries 57

4.47. Government Securities Yield Curve 58

4.48. Ownership of Government Bond 58

4.49. Corporate Bond 58

4.50. Corporate Bond Holders 58

4.51. Issuer Profile 59

5.1. RTGS Settlements 59

5.2. RTGS Players 60

5.3. Clearing Settlements 60

5.4. Value of ATM, Credit and Debit Cards

Transactions 60

5.5. Volume of ATM, Credit and Debit Cards

Transactions 61

Graphs in Boxes :

4.1.1. Sectoral Credit - DIY 38

4.1.2. Type of Credit - DIY 38

4.2.1 Deposits 45

vi

Financial system stability is prerequisite to a sustainable economy and, hence, surveillance to monitor potential risks

that threaten financial system stability is a necessity. The Financial Stability Review (FSR) is a venue through which Bank

Indonesia continually monitors and analyzes all potential factors that may incite financial instability. This publication is

expected to deliver comprehensive information to all stakeholders in the financial system and, consequently, relationships

among the agents in the financial system, potential threats, as well as anticipative measures can be well-understood. The

FSR also represents a means to disseminate pertinent information concerning the role and responsibility of Bank Indonesia

in safeguarding the stability of the domestic financial system.

During the course of the reporting period, domestic financial system stability remained in a positive shape. The

financial system has shown resilience in absorbing externalities stemming from persistent global imbalances, an incessantly

soaring global oil price, and the global trend of interest rate hikes. The Fed Fund Rate and international capital flows have

been two major drivers determining indices in domestic capital markets. In addition, vulnerability in the domestic equity

markets has become increasingly correlated to movements in the equity market of other emerging markets. Identical

equity market rallies in the vast majority of emerging countries, including Indonesia, have been occasionally suspended by

the rise of the Fed Fund Rate that was previously expected to have peaked. This has illustrated the increasingly integrated

financial markets as a result of globalization and, therefore, regional effects have been more crystallized.

The second round effect of last year»s fuel price hikes generated detrimental impacts on the purchasing power of

the household sector. Significant spill-over effects have impinged on domestic economic growth and the intermediary

role of banks. Loan growth and business activities decelerated despite intermediation from bond issuance remaining

steady, a condition reflecting that the role of the financial system in generating financing remained sub-optimal. On the

other hand, capital markets recorded pleasing intermediary performance as reflected by substantial growth in the number

of Initial Public Offerings (IPO), a condition indicating the burgeoning intermediary role of the non-banking sector.

Downward pressure on purchasing power coupled with rising living costs slashed consumer demand and, therefore,

production has decelerated. This was exacerbated by the high production costs and sub-optimal business environment.

These conditions have diminished the repayment capacity of both producers and consumers and, hence, triggered upward

credit risk pressures in the financial system. This has been reflected by the increase in the impaired asset ratio, which

surpassed the indicative threshold of 5%, net of provision. In addition, the asset quality of non-bank financial institutions

deteriorated, particularly credit card financing. This adverse state of affairs requires banks and other financial institutions

to enhance their capabilities in handling problem financing and loans intensively. To this end, capacity enhancement in

the areas of risk management and risk measurement for all financial institutions has been the focal point in endeavors to

Foreword

vii

safeguard financial system stability. Through risk-management certification, it is expected that bankers will have more

capacity to manage and measure risks and, hence, risks can be well-mitigated and handled. Besides, the launch of the

Credit Bureau is expected to enhance disclosure and helps banks avoid adverse selection. These measures help build a

sounder banking system capable of carrying out its functions effectively.

Even though the intermediary function decelerated, financial institutions maintained steady profitability and solvency.

Banks and finance companies reported positive profits leading to a positive accumulation of capital, a condition reflecting

steady domestic financial stability despite recent externalities. Furthermore, measures to mitigate risks have been introduced

by Bank Indonesia, the government and the corporate sector in order to maintain sustainable economy growth. The

government instituted a policy package to improve the investment climate and upgrade existing infrastructure. Bank

Indonesia and the government made concerted efforts to launch a financial sector policy package in an endeavor to

safeguard domestic financial system stability. Furthermore, corporations have had to continuously improve efficiency to

survive in the changing business environment via organizational restructuring, innovation, market expansion as well as

developing alternative sources of energy.

The outlook appears to be positive. Near-term financial stability is more optimistic, which is attributable to rising

intermediation and the robust payment system. The recovery of macro-economy indicators, particularly inflation

expectations, exchange rates, the balance of payment, sovereign rating, as well as positive expectations on returns in

domestic financial markets will help stimulate economy growth and stabilize the financial system. Nevertheless, challenges

remain. Growth in intermediation is predicted to remain at an average level considering the lagged response of domestic

lending rates to the easing of monetary policy and the recent decline of the Bank Indonesia Rate.

Finally, we wish this publication furnishes stakeholders with comprehensive information concerning potential risks

and recent financial system conditions. Therefore, it is expected that efforts to safeguard financial system stability can be

concerted corresponding to the roles of the relevant authorities. Bank Indonesia also expresses gratitude to bankers,

finance companies, security companies, authorities of capital markets, and all self-regulatory organizations involved,

whose significant contributions have enriched this edition. Constructive commentaries from stakeholders are urgently

sought to help Bank Indonesia enhance the surveillance and upcoming review. May Allah Almighty bestow His blessing

on our good intentions and deeds.

Jakarta, September 2006

Deputy Governor

Maman H. SomantriMaman H. SomantriMaman H. SomantriMaman H. SomantriMaman H. Somantri

viii

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1

Chapter I Overview

Chapter 1Overview

2

Chapter I Overview


3

Chapter I Overview

OverviewChapter 1

Amidst risk pressures resulting from the second-round effects of the lastAmidst risk pressures resulting from the second-round effects of the lastAmidst risk pressures resulting from the second-round effects of the lastAmidst risk pressures resulting from the second-round effects of the lastAmidst risk pressures resulting from the second-round effects of the last

year»s oil prices and an upswing in interest rates, financial system stability inyear»s oil prices and an upswing in interest rates, financial system stability inyear»s oil prices and an upswing in interest rates, financial system stability inyear»s oil prices and an upswing in interest rates, financial system stability inyear»s oil prices and an upswing in interest rates, financial system stability in

Indonesia remained positive. The near-term outlook is optimistic, as financialIndonesia remained positive. The near-term outlook is optimistic, as financialIndonesia remained positive. The near-term outlook is optimistic, as financialIndonesia remained positive. The near-term outlook is optimistic, as financialIndonesia remained positive. The near-term outlook is optimistic, as financial

system stability in Indonesia is forecast to improve in line with the increasinglysystem stability in Indonesia is forecast to improve in line with the increasinglysystem stability in Indonesia is forecast to improve in line with the increasinglysystem stability in Indonesia is forecast to improve in line with the increasinglysystem stability in Indonesia is forecast to improve in line with the increasingly

recovering domestic economy.recovering domestic economy.recovering domestic economy.recovering domestic economy.recovering domestic economy.

Table1.1Financial Soundness Indicators

Main Indicator

BankingGrowth of Credit (yoy-%) 21.93 27.03 27.98 24.34 14.01Growth of Deposits (yoy-%) 7.96 9.30 11.85 16.86 15.55LDR (%) 57.92 61.79 65.71 64.73 64.83ROA (%) 2.67 3.46 2.91 2.64 2.54NPL gross (%) 7.55 5.75 7.92 8.30 8.75NPL net (%) 2.10 1.72 3.66 4.82 5.08NIM (%) 0.49 0.55 0.49 0.48 0.54ER (%) 86.99 76.64 87.20 88.32 83.23CAR (%) 20.93 19.37 19.45 19.47 20.46

Multi-FinanceGrowth of Financing (yoy-%) 45.24 33.85 21.33 33.85 21.33Debt - Financing Ratio 1.02 1.08 1.07 1.09 1.07CAR (%) 16.05 13.99 12.99 12.30 13.96

Stock MarketJCI (Jakarta Composite Index) 732.40 1000.23 1122.37 1162.64 1310.26Capitalization (Billions of Rp) 495.798 679.949 765.811 801.253 901.021Foreign Transaction (Billions of Rp) 107.82 2,147.23 2,344.02 1,283.95 (605.30)

Bond MarketIGSYC 3 year (%) NA 9,15 10,44 13,22 12,33Volume of Government Bond (Trillions of Rp) 32.81 48.04 39.84 7.55 5.32Volume of Corporate Bond (Trillions of Rp) 0.98 1.79 0.97 4.5 0.93

Mutual FundNet Asset Value (Trillions of Rp) 84.71 100.98 80.17 28.39 33.06Fixed Income (Trillions of Rp) 71.02 85.04 55.14 12.97 13.26Equity (Trillions of Rp) 0.71 1.89 5.03 4.93 4.71

CorporationROA (%) 4.53 9.82 7.11 10.01 4.15 *DER 1.47 1.19 0.99 1.08 0.87 *EBT (Billion of Rp) 135.31 375.56 216.57 262.43 130.82*Forecast of Business 10.06 20.25 28.27 14.17 22.25Forecast of Sale Price 10.85 12.06 28.80 44.76 15.78Forecast of Employment 4.23 0.00 8.90 5.11 5.16Business Situation 24.88 33.65 23.80 16.30 17.76Expectation of Business Situation in 6 Month forward 34.12 43.27 39.09 31.46 36.77Expectation of Retail Price in 6 Month Forward 123.3 119.2 137 119.8 139.2

HouseholdCurrent Economic Condition 74.52 101.8 87.19 71.94 76.80Consumer Expectation 110.23 136.3 116.22 101.24 105.40Consumer Confidence Index 92.38 119.1 101.70 86.59 91.10

2004 2005 2006

I II I II I

* Data as of quarter-I 2006

4

Chapter I Overview

SOURCES OF POTENTIAL INSTABILITY

Financial system stability is a result of interactions amongst all components of an economy strongly influenced by domestic

and international factors. Continual vulnerability in the international economy had a strong impact on the stability of the

domestic financial system during the course of semester I. Sources of the recent susceptibility included international oil

price fluctuations, the persistence of global imbalances, and the rising global interest rate. Besides, upward risk pressures,

as a result of geopolitical tension and the stronger regional effect on domestic economy, triggered potential instability in

the financial system.

The supply and demand gap has been the root of the persistently high global oil priceºThe supply and demand gap has been the root of the persistently high global oil priceºThe supply and demand gap has been the root of the persistently high global oil priceºThe supply and demand gap has been the root of the persistently high global oil priceºThe supply and demand gap has been the root of the persistently high global oil priceº

Despite the rapid growth in global oil consumption decelerating, persistently high demand coupled with short supply

put upward pressure on the global oil price, which recently showed higher volatility. This was also spurred by geopolitical

tension in Iran and Iraq and disturbances in oil production in Nigeria. Volatility in the oil price is likely to be more

relentless than that of the oil price crisis in the 1970»s. Escalation of the Middle East crisis and the persistently wide

supply-demand gap in international markets will drastically amplify oil price expectations; forecast to reach USD100

per barrel.

º and triggered global interest rates hikesºº and triggered global interest rates hikesºº and triggered global interest rates hikesºº and triggered global interest rates hikesºº and triggered global interest rates hikesº

The persistently high oil price in international markets placed growing pressures on global inflation which has tended

to rise. This has driven tight-biased monetary policies in the vast majority of world economies, which are expected to

persist for the next couple of years. The expectation of a continuous cycle of a spiraling Fed Fund Rate triggered more

capital inflows to the United States. Nevertheless, the existing positive expectations of investment returns in Indonesia

helped mitigate the risk of capital outflows from the country.

Global interest rates determined international capital movement, which has been prone to generate greater andGlobal interest rates determined international capital movement, which has been prone to generate greater andGlobal interest rates determined international capital movement, which has been prone to generate greater andGlobal interest rates determined international capital movement, which has been prone to generate greater andGlobal interest rates determined international capital movement, which has been prone to generate greater and

deeper regional effectsº.deeper regional effectsº.deeper regional effectsº.deeper regional effectsº.deeper regional effectsº.

The search for yield by hedge funds drove greater capital inflows into emerging countries. This was attributable to

optimistic expectations on the returns of investment in these countries as a result of attractive interest rates and economic

growth. Notwithstanding, this condition made emerging countries more susceptible to regional effects, as depicted by

simultaneous and identical bullish rallies in these countries» capital markets. Indonesian capital markets have also been

the target of international capital flows. Capital inflows to domestic capital markets dramatically drove short-lived bullish

rallies in the equity market and more active transactions in the bond market. The potential risk of an equity market

bubble finally came to an end following the continuation of raising Fed Fund Rate. As a result, the bond market, particularly

government bonds, experienced active rallies resulting from inflows of foreign investors, a condition which helped to

recover the domestic bond market.

5

Chapter I Overview

ºmarket risk exposure, nevertheless, remained solubleººmarket risk exposure, nevertheless, remained solubleººmarket risk exposure, nevertheless, remained solubleººmarket risk exposure, nevertheless, remained solubleººmarket risk exposure, nevertheless, remained solubleº

Appealing domestic interest rates and expected returns in the Indonesian capital markets attracted more capital inflows.

This spawned bullish asset prices and exchange rate appreciation. Notwithstanding, banks had the capacity to mitigate

price risk because they held sufficient capital and their asset structures were predominantly in the form of government

securities held to maturity (SUN) and Bank Indonesia certificates (SBI). Additionally, the net open position of banks was far

less than the mandatory threshold; another mitigating tool to insulate banks from unexpected losses emanating from

foreign exchange risk.

Weaker purchasing power did not contribute to economy growth and, therefore, created unfavorable impactsWeaker purchasing power did not contribute to economy growth and, therefore, created unfavorable impactsWeaker purchasing power did not contribute to economy growth and, therefore, created unfavorable impactsWeaker purchasing power did not contribute to economy growth and, therefore, created unfavorable impactsWeaker purchasing power did not contribute to economy growth and, therefore, created unfavorable impacts

on intermediation growthºon intermediation growthºon intermediation growthºon intermediation growthºon intermediation growthº

The second-round effects of fuel price hikes in the third quarter of 2005 had latent ramifications on household purchasing

power. As a result, the economy slowed slightly in the first quarter; rebounding in the second quarter of 2006. Lower

purchasing power coupled with rising lending interest rates contributed to weaker intermediation by financial institutions

in the first quarter. Compared to the previous semester, the credit growth of banks and multi-finance companies declined.

However, financing from the equity markets grew significantly, while bond markets also showed positive growth.

Notwithstanding, it appeared that the economy grow more rapidly than financial sector intermediation, a condition

indicating the emergence of intermediation from the non-financial sector.

ºfollowed by slight upward risk pressures on credit in the first quarterººfollowed by slight upward risk pressures on credit in the first quarterººfollowed by slight upward risk pressures on credit in the first quarterººfollowed by slight upward risk pressures on credit in the first quarterººfollowed by slight upward risk pressures on credit in the first quarterº

Weaker purchasing power since October 2005 impinged on demand and, therefore, hampered production and the

subsequent profitability of the corporate sector. This reduced the repayment capacity of all debtors leading to credit

quality deterioration, particularly in the first quarter of 2006. Investment loans and credit cards were two segments which

significantly contributed to the deterioration. Credit quality began to rebound in the second quarter, attributable to the

steady recovery of corporate debtor profitability. In addition, the business confidence index has shown an improvement

with a positive outlook since the beginning of the year. Moreover, the annual salary bonus given to civil servants helped

improve the repayment capacity of household economies, thus stabilizing the profitability of financial institutions.

....nevertheless, the liquidity of banks remained in good shape despite the pressuresº....nevertheless, the liquidity of banks remained in good shape despite the pressuresº....nevertheless, the liquidity of banks remained in good shape despite the pressuresº....nevertheless, the liquidity of banks remained in good shape despite the pressuresº....nevertheless, the liquidity of banks remained in good shape despite the pressuresº

Despite the lower purchasing power, banks effectively maintained a secure level of liquidity position. This indicated that

the level of customer savings was maintained attributable to attractive domestic interest rates for savings and time

deposits. Conversely, perceived uncertainty surrounding business forced business players to postpone expansion whilst

waiting for domestic interest rates to ease. This encouraged business players to retain their liquidity in time deposits as

they expected an attractive pay off from the interest.

6

Chapter I Overview

The generally moderate risk exposure did not engender downward pressure on the profitability or capital of

financial institutions.

The risk pressures did not threaten financial system stability. The profitability of banks and financial institutions remained

steady and their efficiency continued to improve. This development did not impose continuous pressures on capital

adequacy in the financial system. The relatively high CAR of banks indicated that the level of stability is relatively sufficient.

Financial system stability is also supported by the robustness of the payment system, which has been equipped to encounter

operational disruptions via the installation of a Disaster Recovery Center and, therefore, potential failures in the system

can be sufficiently mitigated.

THE IMPACT OF POTENTIAL INSTABILITY ON THE FINANCIAL SYSTEM

Persistence of the soaring international oil price may threaten macroeconomic stabilityºPersistence of the soaring international oil price may threaten macroeconomic stabilityºPersistence of the soaring international oil price may threaten macroeconomic stabilityºPersistence of the soaring international oil price may threaten macroeconomic stabilityºPersistence of the soaring international oil price may threaten macroeconomic stabilityº

Potential sources of instability, as explained previously, may pose both direct and indirect upward risk pressures. The

continuously rising oil price and the prediction it may reach USD100 per barrel may become potential sources of critical

risks in the domestic financial system. Transmission of this risk pressure can occur through the probability of domestic fuel

price re-adjustments. This development is determined by the capability of the state budget to absorb the oil price shock.

Previous experience has shown that substantial fuel price increases create higher costs for the national economy compared

to subsidy efficiency. However, government signals indicated that they will not raise domestic fuel prices up to the end of

2006; even if the oil price reaches USD 100 per barrel. This indicates that externalities will not trigger domestic upward

risk pressures, at least until the end of this year.

ºand domestic financial system stability through transmission of corporate and household sectorººand domestic financial system stability through transmission of corporate and household sectorººand domestic financial system stability through transmission of corporate and household sectorººand domestic financial system stability through transmission of corporate and household sectorººand domestic financial system stability through transmission of corporate and household sectorº

If global oil price pressures are transmitted to domestic fuel prices, then this can create disturbances in the real economy

(corporate and real economy) via the subsequent rise in production and living costs as well as higher unemployment.

Such a development will further reduce repayment capacity and, therefore, bring prompt credit risk pressures leading

to a deterioration in credit quality. The second-round effects could reduce the profitability and solvency of financial

institutions.

ºhigh international inflation affected the movement of interest rates and international capital flowsººhigh international inflation affected the movement of interest rates and international capital flowsººhigh international inflation affected the movement of interest rates and international capital flowsººhigh international inflation affected the movement of interest rates and international capital flowsººhigh international inflation affected the movement of interest rates and international capital flowsº

Amid the prospect of a domestic interest rate decline, the narrowing interest rate differential between domestic and

international rates appeared to be a disincentive for short-term capital inflows to financial markets. This may induce

capital reversal risk, which can threaten the stability of foreign exchange and capital markets, in particular equity and

bond markets can become distorted. Such distortions can raise market risk exposure for financial institutions.

7

Chapter I Overview

Weaker purchasing power, if persistent, can push domestic financial stability downºWeaker purchasing power, if persistent, can push domestic financial stability downºWeaker purchasing power, if persistent, can push domestic financial stability downºWeaker purchasing power, if persistent, can push domestic financial stability downºWeaker purchasing power, if persistent, can push domestic financial stability downº

The prevailing low purchasing power, if persistent, could undermine economic growth by disturbing production. This

process will reduce corporate profitability and repayment capacity and, therefore, credit risks are likely to emerge. If no

solution can be found, the financial system will be subjected to instability.

MEASURES TO MITIGATE INSTABILITY RISK

Against these challenges, the government and Bank Indonesia exercised proactive measures to safeguard financial system

stability, including:

Bank Indonesia launched the January Policy PackageBank Indonesia launched the January Policy PackageBank Indonesia launched the January Policy PackageBank Indonesia launched the January Policy PackageBank Indonesia launched the January Policy Package

This parcel of policy measures is aimed at expediting the recovery of the intermediation process, thus providing a boost to

the economic recovery. The policy package includes: asset quality rules, expansion of the provision of banking services to

the Micro, Small and Medium Enterprises (MSME), adjustment of Risk-Weight Assets on mortgage and pensioner loans,

and the implementation of good corporate governance (GCG).

Government launched the Investment Climate Policy PackageGovernment launched the Investment Climate Policy PackageGovernment launched the Investment Climate Policy PackageGovernment launched the Investment Climate Policy PackageGovernment launched the Investment Climate Policy Package

The objective of this policy package is to expedite the realization of investment to stimulate sustainable economy growth.

This package comprises of improvement measures in the following areas: investment services, provincial and central

government regulations harmonization, customs and taxation, employment relations, as well as improving the MSME

and cooperative business environment. However, the implementation of these policy measures seems to remain sub-

optimal. Hence, strong commitment from the appropriate authorities is the key success factor in achieving a sustainable

economy as well as financial system stability.

The government also launched the Infrastructure Policy PackageThe government also launched the Infrastructure Policy PackageThe government also launched the Infrastructure Policy PackageThe government also launched the Infrastructure Policy PackageThe government also launched the Infrastructure Policy Package

Through this policy package it is expected that infrastructure improvement supports growth in investment and production

activities. The package details measures in the areas of regulatory and institutional frameworks, transportation, toll roads,

electricity, public roads, gas and oil, water and sanitation, housing, provincial and transaction infrastructure project

development.

Bank Indonesia and the government launched the Financial Sector PackageBank Indonesia and the government launched the Financial Sector PackageBank Indonesia and the government launched the Financial Sector PackageBank Indonesia and the government launched the Financial Sector PackageBank Indonesia and the government launched the Financial Sector Package

The objective of this coordinated policy package is to enhance the financial sector, in terms of financial system stability, to

perform its intermediary role effectively and, therefore, support a sustainable economy. The policy package encompasses

measures to bolster financial system stability, banking and non-banking financial institutions as well as capital markets.

8

Chapter I Overview

- Strengthening financial system stability through the implementation of a Financial Safety Net (FSN) and coordination

amongst the authorities responsible for safeguarding financial stability. FSN is designed as a contingency plan

implemented by the government and Bank Indonesia to prevent systemic banking crisis;

- Bolstering banking institutions via the implementation of good corporate governance and effective risk management,

establishment of the Credit Bureau, enhancement of banking supervision and regulation, customer protection, and

banking consolidation;

- Augmenting non-bank financial institutions via structural improvements in the insurance industry, pension funds

and multi-finance companies. Additionally, the capital markets are being strengthened by the merger of the Jakarta

Stock Exchange and Surabaya Stock Exchange, the implementation of remote trading, development of secondary

markets and products, development of government bonds and the mutual funds industry;

- In particular, the policy package also stipulates the establishment of the Indonesian Export Financing Agency;

Bank Indonesia enhanced regulations to reduce credit risk pressureBank Indonesia enhanced regulations to reduce credit risk pressureBank Indonesia enhanced regulations to reduce credit risk pressureBank Indonesia enhanced regulations to reduce credit risk pressureBank Indonesia enhanced regulations to reduce credit risk pressure

Building capacity to mitigate and manage credit risk through:

- Establishment of the Credit Bureau;

- Capacity building for risk management via Risk Management Certification;

- Institute regulations to improve banking prudence, in the allocation of credit for instance, imposing a legal lending

limit, provisioning, and asset quality assurance;

- Stimulate banks to restructure impaired assets;

- Encourage banks to be more prudential and selective when making unsecured loans, for example credit cards and

uncollateralized loans;

- Raise the minimum payment for outstanding credit card debt to 10%; and

- Prepare for Basel II implementation focused on risk management.

Fiscal stimuli are needed to boost intermediationFiscal stimuli are needed to boost intermediationFiscal stimuli are needed to boost intermediationFiscal stimuli are needed to boost intermediationFiscal stimuli are needed to boost intermediation

In order to enhance the role of capital markets as one of the primary funding sources, it is imperative that taxation

incentives for initial public offerings be considered. It is also important to establish more and fair transparent pricing in the

secondary bond markets.

Measures to continuously enhance the payment system have always been implemented by Bank IndonesiaMeasures to continuously enhance the payment system have always been implemented by Bank IndonesiaMeasures to continuously enhance the payment system have always been implemented by Bank IndonesiaMeasures to continuously enhance the payment system have always been implemented by Bank IndonesiaMeasures to continuously enhance the payment system have always been implemented by Bank Indonesia

This, among others, is conducted via monitoring and regulating Card-Based Payment Means to protect card users and issuers,

safeguard the operational preparedness of DRC (Disaster and Recovery Center) via regular back-testing, as well as preventing

payment system disruption by implementing a Failure-to-Settle scheme. Nevertheless, active participation of all payment

system members in regular DRC tests is crucial. Furthermore, to improve transparency, security and customer protection in

electronic transactions and remittance, Bank Indonesia is currently drawing up regulations for electronic transactions.

9

Chapter I Overview

The role of the corporate sector to enhance efficiencyThe role of the corporate sector to enhance efficiencyThe role of the corporate sector to enhance efficiencyThe role of the corporate sector to enhance efficiencyThe role of the corporate sector to enhance efficiency

Corporations have implemented various efficiency measures as a means of survival by sourcing alternative energy (by

building a power plant for example), downsizing and maximizing their utilization of capital goods as well as product

innovation and market penetration to create profitable niche markets. Besides, the government must always encourage

the corporate sector to continuously adhere to risk management and good corporate governance principles as well as

ensure productive innovation to achieve competitive advantage in international and domestic markets.

Strong commitment of Bank Indonesia to maintain low inflationStrong commitment of Bank Indonesia to maintain low inflationStrong commitment of Bank Indonesia to maintain low inflationStrong commitment of Bank Indonesia to maintain low inflationStrong commitment of Bank Indonesia to maintain low inflation

Bank Indonesia recognizes that the sluggish real economy is the result of a high cost of funds. In order to maintain a low

inflation equilibrium it is crucial to balance supply and demand. With falling inflation, the monetary authority is likely to

relax monetary policy to support sustainable economy growth capable of maintaining low inflation. Therefore, interest

rate formation can be lower and is able to dampen the costs of living and production; hence bringing about lower prices.

To this end, Bank Indonesia consistently implements monetary policy to achieve low inflation.

Purchasing Power should be supported through a variety of effortsPurchasing Power should be supported through a variety of effortsPurchasing Power should be supported through a variety of effortsPurchasing Power should be supported through a variety of effortsPurchasing Power should be supported through a variety of efforts

Lower purchasing power deferred the flow of the economy. To help restore purchasing power, the government

plans to raise civil servants salaries by 10%-15% in 2007. Nevertheless, this measure requires extreme caution to

prevent excessive spikes in inflation expectations that may lead to macroeconomic distortion. Besides, the banking

industry is expected to adjust the cost of funds for consumer loans commensurate to the significant cutbacks in the

BI rate. This is expected to help boost demand for consumer loans and stimulate production. Fiscal stimuli are

expected to play a stronger role via a relaxation in income tax and raising the Direct Cash Subsidy (DCS). The DCS

is a subsidy scheme to the poorest of the poor with a focus on health, education and infrastructure. This scheme is

a pilot project that will be implemented in several provinces in 2007 and is aimed to become a provincial social

security program in 2008.

Initiatives to develop alternative sources of energy needs to be intensifiedInitiatives to develop alternative sources of energy needs to be intensifiedInitiatives to develop alternative sources of energy needs to be intensifiedInitiatives to develop alternative sources of energy needs to be intensifiedInitiatives to develop alternative sources of energy needs to be intensified

Against the persistently high oil price, Indonesia √as a net oil importer- continuously seeks alternative sources of energy.

This includes the development of biodiesel and the use of coal in electricity production by the state electricity company. To

this extent, financial institutions are encouraged to allocate financing to corporate debtors with a business line in this type

of industry as its prospects are indeed promising.

PROSPECT OF FINANCIAL SYSTEM STABILITY

Stability of the Indonesian financial system in semester II 2006 appears to be more positive

Considering the risks that have potentially spurred near-term instability and the mitigating measures that have been

implemented, financial system stability in semester II-2006 has been more optimistic. This is supported by a recovery in

10

Chapter I Overview

the macroeconomy reflected by declining inflation, rising GDP growth, improving balance of payments, more conducive

fiscal conditions as well as exchange rate appreciation and falling interest rates. Corporate sector performance is predicted

to improve considering the more conducive macro-economy, effective survival measures and corporate efficiency. This is

expected to encourage optimistic expectations and better domestic financing and, therefore, the quality of financial

system liquidity will be accurately allocated to the real economy. The ramifications of this positive development are

expected to help raise the income and purchasing power of the household sector and, ultimately raise domestic consumption

and production.

Financial system intermediation reboundsFinancial system intermediation reboundsFinancial system intermediation reboundsFinancial system intermediation reboundsFinancial system intermediation rebounds

The above-mentioned improvements are expected to develop the effectiveness of the banking intermediary function that

was significantly undermined in the first semester of 2006. Insensitivity to loan interest rates is expected to ease along

with the continual declining cycle of the BI rate. On the other hand, credit growth is predicted to rebound after slowing

in semester I 2006. The improved banking intermediary function is expected to stimulate financing from multi-finance

companies, as banking is their major sources of fund. This is expected to help accelerate economy growth in 2006,

despite remaining sub-optimal considering the likely postponement of credit demand by debtors looking for further

decline in interest rate.

Credit risk pressure in the financial system will dissipateCredit risk pressure in the financial system will dissipateCredit risk pressure in the financial system will dissipateCredit risk pressure in the financial system will dissipateCredit risk pressure in the financial system will dissipate

Economic improvements are expected to help restore the repayment capacity of the real sector both corporate and

household and, therefore, credit risk in financial system is expected to dissipate. Non-performing loans in the financial

system are expected to improve followed by a rise in the profitability and solvency of banks. Improving financial system

stability is expected to help create a more solid financial system which can perform its intermediary role efficiently and

effectively. The rapid recovery of financial system stability to levels seen before the crisis is expected to transpire and,

therefore, facilitate economic resilience.

Bullish capital market is likely with prevailing foreign investmentBullish capital market is likely with prevailing foreign investmentBullish capital market is likely with prevailing foreign investmentBullish capital market is likely with prevailing foreign investmentBullish capital market is likely with prevailing foreign investment

Improvement in the sovereign rating for both international and domestic debts, referred to as Standard and Poor»s and

Moody»s is expected to lift investor confidence in investing in Indonesia. An influx of short-term capital inflows is forecast

to materialize with economic growth as the main determinant. Such a situation will predictably stimulate bullish rallies in

the equity as well as domestic bond markets. Furthermore, positive business and economy conditions in the near-term are

forecast to raise intermediation and financing through the equity and bond markets. This forecast is also supported by the

positive expectations of business players and consumers towards production and consumption in the near-term.

Furthermore, the bullishness of the bond markets, particularly government bonds, is also supported by the innovative

retail government bonds, which have started to emerge as an alternative outlet for investment.

11

Chapter 2 Macroeconomic Stability

Chapter 2Macroeconomic Stability

12



13


Prolonged externalities of oil price volatility, global

imbalance and tight monetary policies, didi not

substantially disrupt domestic economy stability. Yet, capital

flows in capital market created slightly vulnerabilities as

Fed Fund increased. Second round effect of oil price hikes

led to a lower purchasing power and decelerated economic

growth. Nevertheless, macroeconomic stability kept on,

indicated by improvement in inflation, exchange rate, fiscal

budget and balance of payment. Advancement in fiscal

budget, predominantly triggered by IMF debt repayment,

swap and hair cut. Furthermore, climbing international

commodity price bolstered balance of payment.

INTERNATIONAL ECONOMY

Risks pressures stemming from persevered global

economy. It is forecast to intensify in the next

semester.

Throughout the first half of 2006, the global

economy continued to be driven by the soaring global

oil price, persistent global imbalances and tightening

monetary policy. Against this backdrop and despite

natural disasters in some parts of the world, the forecast

for global economic growth remained strong compared

to 2005. Consumer and business confidence were

forecast to continue improving with an upward trend in

consumption and investment. Albeit decelerating, growth

in prominent emerging markets, particularly in China,

India and Russia, remained sound. The US economy -as

the primary driver of growth, both globally and in the

industrial world- is forecast to strengthen growth. In the

near-term outlook, the global economy appears to

slowdown slightly given the persistently high oil price

and rising interest rates.

Global imbalances have stemmed from growing

current account deficits in the US; nearing 6.5% of GDP,

and the surpluses from oil exporting countries, China and

Japan as well as some emerging countries. Current account

deficits in the US were driven by high household

consumption, underpinned by the wealth effect and the

continuous rise in asset prices; predominantly property.

The US did not confront problems in financing the deficits

as the fund inflows have remained high. The persistence

of global imbalance will possibly trigger instability given

the imbalances in global financial flows. Corrective

measures to purge the imbalances require adjustments to

boost savings in the US, whilst expanding expenditure in

the surplus economies. In addition, the exchange rates in

the surplus countries have to be adjusted for appreciation.

Such adjustments have begun in China and Malaysia;

changing from previously pegging their currencies to the

MacroeconomyChapter 2

Macroeconomy remained stable despite second round effect of oil priceMacroeconomy remained stable despite second round effect of oil priceMacroeconomy remained stable despite second round effect of oil priceMacroeconomy remained stable despite second round effect of oil priceMacroeconomy remained stable despite second round effect of oil price

hikes in 2005. International risks stemming from oil price, global imbalancehikes in 2005. International risks stemming from oil price, global imbalancehikes in 2005. International risks stemming from oil price, global imbalancehikes in 2005. International risks stemming from oil price, global imbalancehikes in 2005. International risks stemming from oil price, global imbalance

and interest rate were subdued.and interest rate were subdued.and interest rate were subdued.and interest rate were subdued.and interest rate were subdued.

14


USD to becoming more flexible by pegging to a basket of

currencies. In general, the oil exporting countries have high

savings rates. The savings are invested in real estate and

equity markets; as well as channeled through hedge funds

in the Middle East and emerging economies.

The oil price continued to soar and volatility reached

its highest ever level. However the price rebounded to

USD70 per barrel in May 2006. This was triggered by

heightening geopolitical tension in the Middle East,

obstruction of supply in Russia, and nuclear weapon trials

by North Korea. Unless abated, these factors will lead to a

continuous oil supply deficiency and intensified upward

pressures as well as volatility. By the end of 2006, the global

oil price is forecast to surpass USD100 per barrel unless

the adverse geopolitical crisis is settled. The rising oil price

has been more driven by a scarcity in supply, despite the

demand growth for oil declining. The decline in global oil

consumption has been supported by a shift to alternative

sources of energy such as bio-energy as well as more

efficient consumption. The International Energy Agency

estimates that both upstream and downstream

investments in the oil industry remain short by about 20%

of global demand. The future commodity markets predict

that price and volatility of the global oil price will likely

rise. Price volatility is considered likely to be more persistent

than during the oil crisis in the 1970»s.

The high-level persistence of the soaring global oil

price and the price hikes of some international

commodities have caused global inflation to remain high

in 2006; forecast to reach the same level as 2005.

Increasing upward inflationary pressure and current

account deficits have driven central banks to exercise

tight-biased monetary policy. Trends of global short-term

interest rates will likely rise over the next two years driven

by movements in the Fed Fund Rate. The Fed made four

adjustments to its Fed Fund Rate in semester I-2006; by

100 bps, accumulating to 5.25%. The continual rise in

the Fed Fund Rate will pose serious threats to capital

movements in Indonesia.

Graph 2.1World Commodities Price

2000 2001 20020

50

100

150

200

250

300

350

400

450

500

US $

Source: Bloomberg

OilGoldAluminiumCopperTin

2003 2004 2005 2006

Graph 2.2Trend of Global Interest Rate

0

1

2

3

4

5

6

7

8(%)

Source: Bloomberg

Fed Rund RateLIBORSIBOR

2001 2002 2003 20052000 2006

Table 2.1Global Economic Indicators

2004 2005

World Output 5.3 4.8 4.9 4.7Advanced Economies 3.3 2.7 3 2.8Emerging & Developing Countries 7.6 7.2 6.9 6.6

Consumer PriceAdvanced Economies 2 2.3 2.3 2.1Emerging & Developing Countries 5.7 5.4 5.4 4.8

LIBORUS Dollar Deposit 1.8 3.8 5 5.1Euro Deposit 2.1 2.2 3 3.4Yen Deposit 0.1 0.1 0.3 0.9

Oil Price (US$) 30.7 41.3 14.8 2.9

%%%%%Projection

2006 2007

Source: World Economic Outlook

15


The regional equity markets in Southeast Asia

reported bullish trends, particularly at the beginning of

the year as a result of capital inflows into emerging

markets. Funds from the surplus countries surged through

hedge funds. Notwithstanding, by the end of semester I-

2006, the regional equity markets in Asia had experienced

a bearish trend as a result of a downfall in the Brazilian

and Turkish equity markets following the rise in the Fed

Fund Rate. Regional developments in global equity markets

have had strong impacts with greater magnitude;

indicating the increasingly integrated global financial

markets, which are prone to contagion effects. Political

instability in some countries exacerbated their equity

markets, yet did not trigger prolonged bearish conditions.

Except for SET, all regional indices recorded upbeat trends.

Thailand has suffered from political tension recently;

however, its equity market remains attractive for investors

given the relatively reasonable PER. PER for the other equity

markets in the region remained practically identical.

The outlook of global risk in the near term is still in

the upward pressures in consequence of prolonged oil price

rise, inflation nuisance and increasing interest rate.

Accordingly, global economy growth is forecast to slow

down, particularly in United States. High probability of

housing bubble burst in US and in others, might lead to a

deep shrink in global economy. Furthermore, this will

restrain increasing cycle of Fed Fund which leads capital

flows to the emerging market. Increasing geopolitical

tension in middle-east could disrupt oil supply and threaten

world economy if oil prices are skyrocketing.

DOMESTIC ECONOMY

The domestic economy remained stable with lower

instability pressures. However, the second-round

effects of last year»s fuel price hikes placed

downward pressures on domestic economic growth.

Graph 2.3Trend of Regional & Global Index

Source : Bloomberg

9,500

10,500

11,500

12,500

13,500

14,500

15,500

16,500

17,500

18,500

-

1,000

2,000

3,000

4,000

5,000

6,000

7,000

NKY

DJIAIHSG

SET

STI

PCOMP

KLSE

Jan Feb Mar Apr May Jun2006

DJIA, NKY IHSG, SET, STI, PCOMP & KLSE

Graph 2.4Trend of PE Ratio

0

5

10

15

20

25

30

35

40

45

50

Source : Bloomberg

NYASTIKLCIJCIPCOMP

STI

NYASET

SET

JCI

PCOMP

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

KLCI

2 0 0 5 2 0 0 6

Global macroeconomic conditions have profound

impacts on global capital markets. The indices of global

markets were driven by expectations on the movement of

global interest rates, prices of commodities, inflationary

pressures and GDP growth. The movement of interest rates

in major economies, particularly the Fed Fund Rate, attracted

significant attention. Global investors previously expected

that the trend of the Fed Fund Rate would be brought to

an end, a condition encouraging euphoria in global equity

markets at the beginning of the year. At this time in Japan,

investors predicted that the ≈near zero interest rateΔ and

deflationary period would end. Nevertheless, up to the end

of semester I-2006, these expectations have not

materialized. Investors have had to rethink their expectations,

as the Fed Fund Rate has continued to rise.

16


Despite the trend of currency appreciation and the

postponement of basic electricity tariff increases, domestic

economy growth declined compared to the previous year.

Uncertainty surrounding any increase in the electricity tariff

triggered high uncertainty in the business sector,

undermining production. Furthermore, uncertainty

surrounding exchange rates, in terms of both depreciation

and appreciation, has added to uncertainty in the real

economy in implementing business plans. A decline in

household consumption and private investment forced

cutbacks domestic economic growth. On the other hand,

consumer purchasing power also declined as a result of

domestic fuel price hikes. This was reflected by a decrease

in capacity utilization of machinery as well as retail sales

Table 2.2Policy Package

Investment Climate

I. Generala. Strenghten the institution of

investment serviceb. Harmonize the central and province

regulationc. Clarification of regulations in

environment complianceII. Tax and tariff

a. Accelerate the flows of goods.b. Develop bounded zonec. Abolish smuggling.d. Tariff simplicity.

III. Taxesa. tax incentive for investmentb. ≈self assessmentΔ implementationc. change value added tax in exportd. protect the rights of tax obligore. promote of transparency and

disclosureIV. Labor Force

a. Create an industrial climate whichsupport employment.

b. Protection and placement ofIndonesian labor abroad.

c. Resolution in industrial environment.d. Accelerate labor license.e. Create a flexible and productive labor

market.f. Create a breakthrough of a

transmigration development.V. Develop of micro, small and medium

scale enterprises.

Infrastructure Financial sector

I. Policy, regulation and institutionframework

II. Sectoral Policy- land transportation- train- marine transportation- air transportation- toll road and road- powerplant- oil and gas- post and telecommunication- drinking water, sanitation, and water

resource- residential

III. Regional GovernanceIV. Transaction of infrastructure development

project

I. Financial System Stabilitya. Bolster financial sector coordinationb. Forum of financial system stability

II. Banking Financial Institutiona. Strengthen banking institution

- Human resource development- Implementation of Good Corporate

Governance- Increase the quality of credit bureau- Increase the efficiency and effectivity

of supervision- Consumer and investor protection- Improvement of market institution

and structureb. Improve the performance of State

Owned Banks- Non performing loan resolution

III. Non bank financial institutiona. Know Your Customer implementationb. Strengthen the non bank financial

institution- consumer and investor protection

c. Strengthen insurance industryd. Strengthen pension fund industrye. Strengthen multi finance industry

IV. Capital Marketa. capital market developmentb. government bonds developmentc. strengthen mutual fund industry

V. Othersa. development of export financingb. privatization of state owned institution

Graph 2.5Capacity Utilization and Retail Sales

40

45

50

55

60

65

70

75

80

85

60

80

100

120

140

160

180

200

Capacity UtilizationRetail Sales

2004 2005 20062003

17


reaching their lowest level; in February 2006. Against this

backdrop, retail sales of consumer goods and automotive

parts recorded their lowest growth. In addition, the decline

in domestic consumption resulted in a decline in

production, including demand for imported goods. Natural

disasters on some parts of Java Island also had an impact

on domestic economic growth, albeit insignificant.

To boost economic recovery, the government

launched a range of policy initiatives in the form of

investment and infrastructure packages in semester I-

2006 and financial sector packages in the beginning of

semester II 2006. However, challenges arose and,

therefore, the implementation of these initiatives

remained sub-optimal in enhancing the performance of

the real economy. An amendment to workforce law, as

one of the important parts of the policy package, has

been impeded by resistance from the labor unions.

Similarly, the other policy packages also fell short of their

expected benefits. The infrastructure package, which

represents a long-term initiative and inevitably requires

solid coordination among governmental institutions, has

been at a standstill, whereas, the financial sector package

only began implementation recently.

These policy initiatives require strong commitment

from the government. Ineffective governmental

coordination and delays in the implementation further

exacerbate the recovery of the real economy. Besides,

other classic problems have repeatedly impeded real

economy performance and, therefore, the high-cost

economy continues. These unfavorable conditions have

deterred business expansion and new investments. By

the end of 2006, these parcels of policy initiatives are

predicted to have insignificant impacts on the

performance of the real economy and the financial sector.

In 2007, however, these policy initiatives will make a

significant contribution to enhance investment growth

and financial system.

The consistency of Bank Indonesia policy has had a

profound impact. Domestic inflation eased to 15.5% in

June 2006 from 17.11% in December 2005. In addition

Table 2.3Growth of Gross Domestic Product

Private consumption 4.94 3.22 3.46 4.43 4.18 3.95 3.24 2.99

Government consumption 1.95 (8.52) (5.61) 16.15 29.98 8.06 14.19 31.38

Investment 15.71 14.98 13.21 9.18 1.78 9.93 2.89 -0.98

Goods and service export 8.47 13.39 7.29 3.39 7.41 8.60 10.75 11.3

Goods and service import 24.95 15.38 10.08 9.29 3.74 12.35 5.01 8.31

Gross Domestic Product 5.13 6.35 5.84 5.34 4.90 5.60 4.59 5.22

2005 200620052004

Total Q I Q II Q III Q IV Total Q I Q II

Source: Statistics Indonesia

%

Graph 2.6Inflation, BI Rate and SBI

-5

0

5

10

15

20%

2001 2002 2003 20052000 20062004

InflationSBI 1 month BI Rate

18


to inflation target of 8%±1% for 2006, made Bank

Indonesia adjusted the BI Rate since May 2006 reaching

12.25% by the end of semester I 2006. This policy was

responded to positively by market players as the

commitment of Bank Indonesia to curb inflation, despite

the probability of a Fed Fund Rate rise. Notwithstanding,

owing to the prevailing attractive interest rate differential,

the difference in policy measures of the Fed and Bank

Indonesia will not trigger potential instability or a capital

reversal. The narrow room for Bank Indonesia to

maneuver seems to have limited impact on the real

economy.

On the other hand, the rupiah fluctuated slightly

against the major currencies with a volatility of 0.45%.

Improvements in country risk exposure as well as a more

attractive interest rate differential in Indonesia than other

Asian countries, made the rupiah appreciate in May 2006.

Notwithstanding, the rupiah relapsed by the end of June

due to continuous tight-biased monetary policy in the

US as well as regional effect by crashed in Turki and Brazil

equity markets.

Regional depreciation has also had a profound

impact on the rupiah. During the course of semester I-

2006 the exchange rates of some Asian countries also

fluctuated slightly with a generally weakening trend

against the USD. Externally, depreciation was also

triggered by the positive expectations of market players

on the cycle of the Fed Fund Rate rise. Whereas internally,

the low interest rate cycle in Japan made the yen

depreciate significantly. This prompted other Asian

countries to retain a low interest rate policy to preserve

their export competitiveness against Japan. Besides,

concern about the situation in South Korea after nuclear

weapon trials by North Korea and an unfavorable political

situation in Thailand were two driving factors of regional

currency depreciation.

The balance of payments in Indonesia has improved

despite slight upward pressures of external risk exposure.

Throughout the first quarter of 2006, trade and current

account balances recorded a surplus due to augmented

in exports; predominantly stemming from the surge in

oil-gas and non oil-gas prices. Conversely, imports

dropped significantly, owing to the substantial decline

of oil-gas imports. This is supported by oil consumption

efficiency since oil price hikes in 2005. Moreover, weaker

purchasing power restrained import demand of either

final and intermediate goods.

The early termination of debts due to the IMF made

the balance of payments and fiscal condition healthier.

This was also supported by a surplus in the capital account

that is forecast to grow significantly and, therefore,

substantially expand the international reserves of

Indonesia to USD40.1 billion in semester I-2006. The

surplus has been due to a substantial amount of capital

inflows, predominantly to domestic equity and bond

markets. Considering the returns in domestic financial

markets, optimistic macroeconomic expectations as well

as low country risk, Indonesia remains attractive for

international investors and, thus, attracted more capital

inflows. Notwithstanding, Indonesia has been strongly

vigilant over the risk of capital reversal, as the surplus

predominantly stems from short-term portfolio

Graph 2.7Exchange Rate IDR to US $

6000

7000

8000

9000

10000

11000

12000

13000

Rp/US$

2000 2001 2002 2003 2004 2005 2006

FFR 5% (May 10, 2006)

- Katrina storm in New Orleans (Aug29, 2005

- World oil price USD 69.81/barrel (Aug 30, 2005)

19


investments. In addition to the portfolio investments,

foreign direct investment to Indonesia is forecast to

slightly expand by year end. Accordingly, improved

balance of payments and fiscal conditions will insulate

Indonesia from externalities.

The near-term forecast of macroeconomic stability

is positive supported by an easing of inflationary pressures,

declining domestic interest rates, more stable exchange

rates, and expanding international reserves. Besides, the

credit rating of Indonesia has also improved, which reflects

positive developments in the macro economy and in terms

of country risk. The higher credit rating is due to enhanced

fiscal and external conditions given the budget surpluses

and declining public debt burden. Taking this positive

development into account, both direct and indirect foreign

investment will predictably escalate during the course of

semester II-2006. Besides, economic turnover is supposed

to take a leap forward as the government has launched a

policy package to improve the investment climate,

infrastructure and the financial sector. Nevertheless, to be

effective, strong commitment from the government in the

Graph 2.8Country Risk of Indonesia

Source: International Country Risk Guide

30

35

40

45

50

55

60

65

70

2003 2004 2005 2006

Aug Nov Feb May Aug Nov Feb May Aug Nov Feb May

Political RiskEconomic Risk

Financial RiskComposite Risk

Table 2.4Balance of Payment

I. Current Account 1,564 340 2,564 1,980 1,949 2,152 8,646A. Goods, net (Trade Balance) 20,152 22,323 8,733 8,683 7,649 7,376 32,442

1. Exports, fob 70,767 86,179 23,146 25,274 25,563 25,003 98,9852. Import, fob -50,615 -63,856 -14,413 -16,591 -17,913 -17,627 -66,544

B. Services, net -8,811 -10,792 -3,298 -3,226 -2,680 -2,591 -11,796C. Income, net -10,917 -12,447 -3,248 -3,608 -3,344 -2,953 -13,153D. Current Transfers, net 1,139 1,257 378 131 324 320 1,152

II. Capital & Financial Account 1,852 -2,579 537 -911 327 -429 -476A. Capital Account n.a. 333 41 56 152 152 400B. Financial Account 1,852 -2,913 496 -967 175 -581 -876

1. Direct investment -1,512 3,042 -171 -137 549 -119 122a. Abroad, net -3,408 -3,065 -655 -628 -745 -911 -2,940b. In Indonesia (FDI), net 1,896 6,107 484 491 1,294 792 3,061

2. Portfolio investment, net 4,409 4,236 3,710 -1,222 824 837 4,149a. Assets, net 353 -1,080 -392 -471 -24 -29 -916b. Liabilities, net 4,056 5,316 4,102 -751 848 866 5,065

3. Other investment -1,045 -10,190 -3,043 392 -1,197 -1,299 -5,147a. Assets, net 985 -8,646 -1,456 1,861 -1,845 -2,909 -4,348b. Liabilities, net -2,030 -1,544 -1,587 -1,469 647 1,610 -799

Memorandum:Reserve Assets Position 36,320 34,724 40,082 40,107 41,916 43,262 43,262(In Months of Imports & Official Debt Repayment) 5.7 4.6 4.6 4.6 4.8 5.0 5.0Current Account (% GDP) 0.6 0.1 - - - - 2.6Debt Service Ratio (%) 27.1 22.1 24.9 34.3 20.5 23.8 25.8

20052006*

2004Q1 Q 2 Q3 Q4 Total

Billions of US$

20


implementation of the policy package is a top priority. On

the other hand, domestic investment will remain slow-

Graph 2.9Expected Inflation for the Next 6 Months

Survei Kegiatan Dunia Usaha (lhs)

0

20

40

60

80

100

120

140

160

-50

0

50

100

150

200

Retail Selling survey

Net balance Net balance

2001 2002 2003 2005 20062004

Consumer Survey

Note : Adjusted calculation in 2004

moving considering the challenges faced in infrastructure,

particularly energy supply. This has been reflected by

investment plans that appear to contract in the near-term.

Besides, the conjuncture of the global economy -

predominantly the global oil price, interest rates, short-

term capital inflows, exchange rates, and regional capital

markets- will increasingly determine the state of the

domestic economy. The state of the near-term global

economy is exacerbated by the political tension in the

Middle East. These determinants will engender upward

risk pressures on the presently stabilizing domestic

macroeconomy and financial sector.

21

Chapter 3 Corporate and Household Sector

Chapter 3Corporate and HouseholdSector

22



23


Corporate and Household SectorChapter 3

Corporate performance has improved in Q1 2006,

in line with diminished risk pressures. Increasing rentability

and financing cash flow lead to optimism on future

corporate performance. Government support to improve

investment policy and reduce high cost economy was

expected to have significant positive impact for the

economy and to foster economic growth. On the

household side, oil price shocks in October 2005 has

undermined the purchasing power of consumers.

Additionally, extensive lay-off by corporate sector and

stagnant job vacancies as well as income level has

contributed to exacerbate the repayment capacity of

consumers. This condition put upward pressure on

consumer loan risk, particularly on credit card along with

significant increase of interest rate which curbed demand

for conumer loan.

CREDIT RISK IN THE CORPORATE SECTOR

Credit risk in the corporate sector has started to

decline in line with the improvement in repayment

capacity

Inflationary pressures stemming from oil price

shocks in quarter IV-2005 generated second-round effects

in semester I-2006. Price hikes √including raising the

industrial property lease- undermined investment in the

corporate sector. Notwithstanding, consistency from Bank

Indonesia in implementing monetary policy effectively

curbed inflationary pressures, as reflected by the

narrowing spread of nominal and real interest rate as

well as macroeconomic stability. Besides, corresponding

to supportive government initiatives to enhance the

investment climate, including the amendment of

investment and labor laws as well as the postponement

of an electricity tariff increase, working capital and

investment loans received a boost. Additionally, the ratio

of non-performing loans is falling. During the first quarter

of 2006, working capital and investment loans increased,

albeit at slower rates.

The increasingly stable macroeconomy of Indonesia had a positive influenceThe increasingly stable macroeconomy of Indonesia had a positive influenceThe increasingly stable macroeconomy of Indonesia had a positive influenceThe increasingly stable macroeconomy of Indonesia had a positive influenceThe increasingly stable macroeconomy of Indonesia had a positive influence

on the performance of the corporate sector, albeit the effects on employmenton the performance of the corporate sector, albeit the effects on employmenton the performance of the corporate sector, albeit the effects on employmenton the performance of the corporate sector, albeit the effects on employmenton the performance of the corporate sector, albeit the effects on employment

and growth remain sub-optimal.and growth remain sub-optimal.and growth remain sub-optimal.and growth remain sub-optimal.and growth remain sub-optimal.

Graph 3.1Amount and NPL of Working Capital

& Investment Loan

% %

-60

-50

-40

-30

-20

-10

0

10

20

30

40

-60

-50

-40

-30

-20

-10

0

10

20

30

40

2001 2002 2003 20042000 2005 2006

Working Capital Loan-Growth (lhs) Investment Loan-Growth (lhs)

NPL Working Capital Loan (rhs) NPL Investment Loan (rhs)

24


The financial performance of the corporate sector

showed slight improvement in terms of better profitability

and liquidity compared to the previous year, shown by

healthier ROA. This was also reflected by a drop in the

number of businesses that recorded losses. With the

exception of basic industry, in general, all industries

reported a decreasing trend in the number of businesses

recording losses. In addition, the mining industry was the

best performer given the least number of companies

recording losses. The driving factors behind the superior

performance of the mining sector include: (1) efficiency

enhancement by shifting energy sources and organizational

restructuring; and (2) rising mining prices in global

commodity markets. In addition, the liquidity of the

corporate sector improved as evidenced by a healthier ratio

Although real interest rates for loans were close to

0%, the relatively high cost of financing scuppered demand

for working capital and investment loans. As a

consequence, credit growth has continuously slowed

down. Notwithstanding, the credit risk associated with

investment loans diminished, whereas, for working capital

loans the risk increased slightly, as confirmed by the non-

performing loan ratios. As a result of oil price shocks in

October 2005, domestic consumer demand turned

sluggish. On the other hand, the cost of production -

predominantly related to energy- grew significantly. Such

adverse conditions slashed the profit margin and

undermined the repayment capacity of corporate debtors

up to the first quarter of 2005. However, they quickly began

to rebound in the second quarter of 2006.

Graph 3.3Corporate Loss Ratio

Graph 3.2Corporate Financial Indicator

Base year 2002=100

Source: Jakarta Stock Exchange

Q1:2005

Q1:2006

Current Ratio

ROA

ROE

Inventory Turn Over Ratio

Collection Period

DER

0

40

80

120

160

200

240

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

Q1 Q2 Q3 Q4 Q1

2003 2004 2005 2006

consumption

infrastructure

agriculture

basicindustry

miscindustry

trading

property

mining


Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

Graph 3.5Cash Flow

Q1 Q4 Q3 Q2 Q1 Q4 Q3 Q2 Q1

2000 2003 2006

Operating activitiesInvesting activitiesFinancing activities


0

100

200

300

400

500

-500

-400

-300

-200

-100

Millions of Rp

Graph 3.4Growth of ROA and ROE

-100

0

100

200

300

400

500

600

700

800

2001 2002 2003 2004 2005 2006

%

ROE


Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1

ROA

25


of current assets. The improvement in corporate

profitability and liquidity indicated the potential to enhance

the repayment capacity. This will enable the financial sector

to better mitigate credit risk as NPL will predictably fall in

the near-term.

On the other hand, corporate leverage has slowed

compared to the previous year, as shown by the

decreasing debt-to-equity and debt-to-total assets ratios.

This was supported by an increase in financing cash flows

as a result of initial public offerings and rights issues

totaling Rp6.5 trillion. Financing from bond issuance also

rose by Rp3.6 trillion. The increase in financing cash flows

indicated that business expansion and investment is

imminent, as shown by the positive business confidence

index and investment plan concurrent with declining

country risk. The emergence of positive expectations

towards investment plans has also been supported by

policy initiatives to enhance the investment climate,

infrastructure and financial sector. To this extent, strong

commitment and effective coordination among the

authorities are essential, as a poor investment climate

has been a major impediment. Additionally, optimistic

expectations of inflation, domestic interest rates, and

stable exchange rates have also been supporting factors.

As a result, investment and business expansion is forecast

to rebound strongly in 2007. The challenges remain,

however; increases in administered prices, including basic

electricity tariffs and fuel prices, as well as the smuggling

of consumer goods to domestic markets that expose the

domestic economy to unprecedented risks.

CREDIT RISK IN THE HOUSEHOLD SECTOR

Credit risk in the household sector was moderate

with a likelihood of increasing in line with weaker

purchasing power.

In line with the dwindling consumer demand, growth

in consumer loans continued to decelerate in semester I-

2006. Oil price shocks and interest rate hikes in October

2005 had adverse impacts on the purchasing power of

the household sector. Expensive cost of funds and a higher

Graph 3.7Business Survey

0

5

10

15

20

25

30

35

40

45

50

2002 2003 2004 2005 2006

Business Situation 6 Month BusinessExpectation

Financial condition

Net Balance

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

Graph 3.6Corporate Leverage


0.6

0.8

1

1.2

1.4

1.6

1.8

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q12003 2004 2005 2006

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

DERDebt/TA

Debt/TADER

Graph 3.8Plan of Investment

10

15

20

25

30

35

40

2003 2004 2005 2006

% Respondent

40

45

50

55

60

65

70Net Balance

Plan of Investment Estimation of investment

Sem II Sem I Sem II Sem I Sem II Sem I

26


cost of living weakened demand for consumer loans and

exacerbated the repayment capacity of consumers.

Additionally, rising residential property inflation also

hampered demand for mortgages. On the income side,

the household sector was hit by scores of employee

dismissals following streamlining measures taken by the

corporate sector subsequent to the oil price shocks. These

dismissals undercut their repayment capacity. Highest lay-

off was in forestry, textile & textile product, shoes,

construction and tourism industry. This trend was due to

the structural problem in the respective sectors, such as

illegal logging in timber industry and smuggling in textile

& textile product industry. The increment lay-off level was

predicted about 2% higher than that of the previous

semester. Accordingly, total number of open

unemployment rose to 11.1 million people, put an upward

pressures on credit risk for consumer loans. This condition

was reflected in NPL of consumer loan which tended to

increase significantly in semester I 2006.

Credit risk associated with mortgages and credit cards

also showed a growing trend. Consumer property

increased significantly, yet followed a growing trend of

distressed loans, which they remained below the

acceptable threshold of 5%. Notwithstanding, credit risk

exposure for households emerged from credit card

financing, as the vast majority of card holders are low

income earners. From the total number of credit card

holders, 55.52% earn a monthly income of Rp1-2 million.

With monthly interest rates of 3.25-3.75% or 39.0-45.0%

per annum and the escalating cost of living, credit risk

from credit cards is becoming alarming. Non-performing

loans for credit cards totaled Rp18.1 trillion or 2.5% of

Graph 3.12Mortgages (House & Apartment)

Graph 3.11Lay-off

Thousand people

-

20

40

60

80

100

120

140

2001 2002 2003 2004 2005 2006 *)

Source: Depnakertrans*) Until Semester I

NPL (rhs)

Billions of Rp

-

10,000

20,000

30,000

40,000

50,000

60,000

70,000

Dec 00 Dec 01 Dec 02 Dec 03 Dec 04 Dec 050

1

2

3

4

5

6

7%

Value (lhs)

Dec 05

Note :

Graph 3.10Residential Inflation

0

2

4

6

8

10

12

14

1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 22000 2001 2002 2003 2004 2005 2006

%

Graph 3.9Consumer Loan & NPL

-4

-2

0

2

4

6

8

10% %

-40

-20

0

20

40

60

80

100

2001 2002 2003 20042000 2005 2006

Consumer Loan-Growth (lhs) NPL(rhs)

27


total loans. Despite the segment»s modest size, growing

credit risk associated with credit card financing will threaten

banking sector unless strong vigilance is exercised.

In the near future, with lower inflationary pressures,

household consumption is forecast to expand and,

therefore, contribute to greater economic growth. Easing

inflationary pressure will have profound effects on relaxing

monetary policy. Nevertheless, monetary relaxation will not

promptly lessen the interest rate of credit, therefore

Graph 3.13Consumer Confidence Index

Graph 3.14Consumer Expectation for the Next 6 Months

demand growth for consumer loans will slow down.

Furthermore, banks are planning to revise their targets for

consumer loan expansion, a condition that potentially

decelerates consumer loan growth. Moreover, consumer

confidence has started to emerge, albeit consumption

appears not to materialize in the near-term. To stimulate

purchasing power and demand, fiscal stimuli from the

government, such as income tax reduction and direct cash

subsidies for the poor, are essential.

Consumer expectationConsumer confidence index

0

20

40

60

80

100

120

140

160

2003 2004 2005 2006

Net Balance

Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun

Recent economy condition

0

20

40

60

80

100

120

140

160

180

2003 2004 2005 2006

IncomeEconomy conditionJob Availability

Net Balance

Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun

28



29

Chapter 4 Financial Sector

Chapter 4Financial Sector

30



31


Financial SectorChapter 4

The stability of Indonesian financial system lingered

despite experiencing slightly shocks in the capital market.

Intermediary function of the financial sector was restrained,

as reflected by a significant decline in financing growth.

Rising interest rates coupled with deteriorating public

purchasing power lead to a decline in financing demand

and quality. Nevertheless, banking sector showed resiliency.

Banks had limited exposures of market and liquidity risks,

and therefore, these risks did not generate disruption in

banks. Banks have been well-capitalized and maintained

steady profitability, making them capable to dampen

various risk pressures. Furthermore, restrained intermediary

function by banks caused a decline in business activities

and the profitability of multi-finance companies. Moreover,

mutual funds market rebounded after substantial

redemptions in the previous year. The stock market

experienced a bullish rally for a short time but was corrected

near the end of 2005 because of a rise in the Fed Fund

Rate and regional effects. The bullish trend in the equity

market was triggered by foreign investors» movement; a

similar condition also occurred in the government bond

market. On the other hand, corporate bond market was

less active. Bank Indonesia exercises strong vigilance over

intensive transactions by foreign investors, as this is prone

to sudden capital reversal.

BANKING

Despite upward risk pressures, the stability of

banking sector remained positive.

Intermediary function of banks remained positive

despite slowed significantly due to a rise in credit risk

pressure. This is an impact generated by the sharp decline

in public purchasing power attributable to sharp hikes in

domestic fuel prices. On the other hand, liquidity risk and

market risk pressures were not significant and well

managed. The application of a limited guarantee scheme

to public savings has not yet indicated significant migration

Financial system stability was remained, despite upward risk pressure triggeredFinancial system stability was remained, despite upward risk pressure triggeredFinancial system stability was remained, despite upward risk pressure triggeredFinancial system stability was remained, despite upward risk pressure triggeredFinancial system stability was remained, despite upward risk pressure triggered

by the fuel price hikes. Financial institutions continuously performed wellby the fuel price hikes. Financial institutions continuously performed wellby the fuel price hikes. Financial institutions continuously performed wellby the fuel price hikes. Financial institutions continuously performed wellby the fuel price hikes. Financial institutions continuously performed well

despite restrained intermediary function.despite restrained intermediary function.despite restrained intermediary function.despite restrained intermediary function.despite restrained intermediary function.

Graph 4.1Credit growth, Deposit, and LDR

%

(10)

-

10

20

30

40

50

60

70

80

2001 2002 2003 2004 2005 2006

Loan to Deposit Ratio

DepositsLoans

32


in banking. On the contrary, banking liquidity increased

as the interest rate remains high. Overall, emerging risks

did not disrupt profitability or capitalization, which helped

to maintain banking sector resilience.

Intermediary Function

The intermediary function of banks remained

positive, albeit decelerating, reflected by continuously

declining credit growth reaching 14.9% (y-o-y). Such

credit growth is still far below targeted growth in the

bank business plan set at 18% in 2006. This development

is the result of the rise in interest rates, weaker public

purchasing power, and unfavorable economic conditions

brought about by the sharp hikes in domestic fuel prices

in October 2005. Moreover, inadequate implementation

of the policy to improve the investment climate did not

boost demand for investment credits. Statistically, high

interest rates supported the acceleration of credit

repayments, while disbursing new credits weakened,

leading to relatively low net credit growth. This indicates

a tendency of contracted economy activity. In addition,

high interest rates as well as a rise in production and

living costs impinged on NPL.

The loan-to-deposit ratio (LDR) stayed at 64.8%,

reflecting the fact of the remaining slow growing

intermediation. The growth of bank funding accelerated

attributable to the rise of interest rates, on the other hand,

credit growth significantly slowed down. Beside credits,

banks had substantial portions of portfolio in government

bonds (SUN) and Certificate of Bank Indonesia (SBI), with

share of 24.7% and 10.9% respectively. This portfolio

structure, nevertheless, was a sign of the remaining sub-

optimal support of banking sector to the real economy.

Throughout the first semester of 2006, credits in all

sectors of economy showed lower growth (y-o-y) than

the previous year. This was attributable to the January

Effect, where all companies are usually preparing for the

commencement of business plan implementation, whilst

waiting for the direction of macro economy development.

Driven by robust demand, credits for construction and

trading sectors were buoyant, achieving 18.3% and

18.24% respectively. On the other side, credit for

manufacturing sector -the prime mover of the economy-

recorded lower growth to 9.78% (y-o-y). The falling credit

demand reflected the second round effect of the hikes

in fuel prices and domestic interest rates, a condition

triggering escalation of production and living costs. Credit

for property ownership has stayed upbeat, attributable

to the growth of residential mortgage.

Banks have increasingly shifted towards

consumption credit despite being hampered by lower

demand in the first half of 2006. Consumption credit

Graph 4.3Growth of Property Loans

-100

-80

-60

-40

-20

0

20

40

60

80

Real EstateConstructionMortgage

1998 1999 2000 2001 2002 2003 2004 2005 2006

%

Graph 4.2Sectoral Credit Growth

-10 0 10 20 30 40 50 60

June 2006June 2005

%

Trading

Manufacturing

Transportation

Contruction

Agrobusiness

Services

Social Services

Mining

Electricity

33


recorded the highest growth despite its deceleration to

16.2% (y-o-y) from 36.81% (y-o-y). High cost of funds

due to the spike in domestic interest rates impeded

demand for consumption credit. This incited a mounting

pressure on consumer credit risk due to lower consumer

repayment capacity coupled with mounting inflationary

pressures. Nevertheless, consumption credit has been

more profitable and secure, and consequently, banks have

maintained growing portion of their portfolio in this

segment. Against this backdrop, the consumption credit

grew to around 29.5% of total aggregate credit. The

primary driven was mortgages, which showed growth

of 33.5% (y-o-y) and led to a share of 31.2% of total

consumption credit. Credit for vehicle ownership as well

as unsecured personal loans expanded rapidly; a condition

demanding stronger surveillance.

Demand for working capital credit remained steady,

as reflected in its unwavering growth attributable to a

steady growth in trading sector. As a result, at the end of

semester 1 2006, working capital was the largest portfolio

of most banks, reaching 51% of total credit. This has

been a sign of remaining positive economic activities

amidst slowing down. In the meantime, the growth of

investment credit has continued to show a downward

trend since 2004, achieving only 6.2% (y-o-y). Low

investment credit growth indicated remarkably low

investment activities. In addition to lower public demand,

low investment credit growth was also attributable to

unfavorable investment climate, including the sub-

standard infrastructure, in particular electricity.

Nevertheless, implementation of policy package to

improve infrastructure remained sub optimal as realization

of investment fell short to meet the target.

Conversely, credit to micro, small and medium-sized

enterprises (MSME) showed buoyant growth. Retail

sector, such as MSME, become a preferred outlet in banks»

portfolio as this sector proved to be more resilient to

shocks. This was reflected by MSME credit growth

achieving 18.2% (y-o-y); notwithstanding, it was lower

than the previous semester (25.2%). Such a movement

bolstered the MSME credit share amounting to 26.1%

of total banking credit. Nonetheless, incentives for MSME

financing expansion through the banking policy package

of January 2006 appeared to be underutilized by banks,

except those with existing networks in the MSME

financing segment. Although the MSME segment has

been relatively higher resilience compared to other

segments, not all banks were able to enter this segment,

considering that the efficiency level of banks differs.

Working capital was the largest portion of MSME credit

and investment credit remained small.

Banking intermediary function is forecast sub-

optimal in the next half of 2006, despite the decline in BI

Graph 4.4Type of Credit

0

20

40

60

80

100

Working Capital (51.5%)

Investment (19%)

Consumer (29.5%)

%

2000 2001 2002 2003 2004 2005 2006

Graph 4.5Credit Growth per Type

%

-60

-40

-20

0

20

40

60

80

Working Capital Loan

Investment Loan

Consumption Loan

2000 2001 2002 2003 2004 2005 2006

34


foreign-currency denominated credits showed high NPL,

reaching 21.9%, compared to those of rupiah

denominated, which was just 6.2%. Notwithstanding,

the stability of banking sector will not be in disruption,

as the share of foreign currency denominated credits is

relatively insignificant (18.0%). Domestic banks held only

12.6% of foreign currency denominated loans, while

other, including foreign and joint-venture banks held

(46.1%) and (58.0%) respectively.

Persisting fundamental economic problems such as

those related to taxation, legal assurance, investment and

infrastructure intensified credit risk pressures. Despite

facing this high pressure, the real sector, in general, survived

and grew. Moreover, enhanced risk management capability

of banks and prudence helped to mitigate the acceleration

of NPL ratio. Increased credit risk pressure caused banks

and savings rates. This is related to the rigidity in credit

interest rate, attributable to the relatively high cost of

funds, particularly in overhead costs including insurance

premium for deposit insurance scheme and technology.

In addition, banks are focusing their efforts in

consolidation as this is accelerated by incentives, among

others in the form of tax relief, as stated in the financial

sector policy package. Banks will be entitled to incentives

for those make successful consolidation in the form of

mergers and acquisitions up to 2008. Third, debtors will

likely to wait and see. The signal of a continuation interest

rate decline cycle will prevent debtors to promptly

demand for credit and shift their expectation, as they

will wait for better rates.

Credit Risk

In addition to the decelerating intermediary

function, credit risk pressures inclined to increase as gross

NPL rise from 8.3% at the end of 2005 to 8.8, peaking

in March 2006. This was a secondary effect of various

macroeconomic shocks including the hikes in fuel prices

and sharp rises in the interest rate in 2005. Due to the

remaining sub-optimal business prospects, NPL have

remained concentrated on corporate segment,

particularly at two large banks. Gross NPL will drop to

below 5%, excludes the two large banks. Moreover,

Graph 4.7Gross NPL

3.7 3.5 3.74.5

4.0

5.0

10.110.6

3.94.6

0

3

6

9

12

Large Bank MediumBank

Small Bank Joint Venture Foreign Bank

Dec'05Jun'06

%

Graph 4.6Growth of Loans to SMEs

2005 2006

%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun0

5

10

15

20

25

30

35

40

Working Capital Loan Investment Loan Total

Graph 4.8Net NPL

%

0

2

4

6

8

Large Bank Medium Bank Small Bank Joint venture Foreign Bank

Dec'05Jun'06

6.0

2.5 2.5

1.61.1

6.3

2.8 2.9 3.0

0.8

35


to be reluctant to allocate credits to the corporate sector,

since the historical probability of default in this segment is

higher compared to other segments. In addition,

impediments in legal resolution since the crisis period

caused the settlement of NPL in this segment to become

very slow and expensive.

Credit to manufacturing industry recorded the

highest gross NPL with a declining trend reaching 15.3%

and credit share (42.4%) of foreign currency-denominated

credit. Overall, share of manufacturing industry credit

reaching 23.8%, indicated that credit risk pressure from

this sector requires strong vigilance and prompt resolution.

Weaker purchasing power exacerbated conditions in the

industrial sector. The timber industry, as well as the textile

and textile products industry showed high NPL, as a

consequence of a limited wood supply and substantial

textile imports competition from China. In addition, the

trade sector also showed a significant rise in NPL, reaching

7.52% from 5.50% at the end of 2005. A decline in the

credit quality of the trade sector indirectly influenced

working capital credit quality, for which NPL reached

8.40%.

As per usage, investment credits recorded the

highest NPL, achieving 16.1%, a slight rise from its

previous position. The accelerating credit risk pressures

attributable to the impaired loans of corporate debtors,

particularly at two large banks, despite rescheduling,

reconditioning and restructuring efforts. A portion of the

NPL, among others, stemmed from un-restructured IBRA

credits. However, in general, gloomy economy as well as

imprudent risk management was the major factors behind

rising NPL of investment credits. On the other hand,

consumption credits showed the lowest credit risk

2000 2002 2003 2004 2005 20060

5

10

15

20

25

30

35

40

45

Rupiah

Foreign Currency Denominated

Total

%

Graph 4.10Non Performing Loans - Foreign Currency

& Rupiah Denomination

Graph 4.9Non Performing Loans

-

2

4

6

8

10

12%

0

100

200

300

400

500

600

700

800Billions of Rp

NPL Gross (lhs)NPL Net (lhs)

Credit (rhs)

2002 2003 2005 20062004Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun

Graph 4.11Non Performing Loans - per Business Sector

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Others industries = transportation, construction, agriculture, mining, social service, dan electricity

0

20

40

60

80

100Other industries

Business Services

Manufacturing

Others

Trading

%

Graph 4.12NPL of Trading and Manufacturing

2001 2002 2003 2004 2005 2006

%

Trading

Manufacturing

0

10

20

30

40

50

60

36


and the interest rate in October 2005, nevertheless slowed

down MSME activity. Such a condition is a reflection of

the substantial share of MSMEs in the trade sector;

reaching 49.9%. Consequently, any decline in purchasing

power weakens MSME performance, specifically the trade

sector as shown by a sharp rise in the NPL from 3.9% to

7%. This is mainly contributed by working capital credits

with NPL reaching 6.95%.

Property credit quality experienced a decline with

upward risk pressure stemming from an NPL rate reaching

6.4% from 5.3%. However, this did not lead to instability

considering the relatively small share property credit has.

Mortgages, as the largest share of property credit, showed

the highest credit quality, but also experienced a significant

leap in NPL reaching 3.8% from 2.4%, in line with the

considerable decline in consumer repayment capacity. The

highest NPL rate, previously held by credits for construction

projects, shifted significantly to real estate credit, reaching

13.4%.

In line with improvements in macroeconomic

conditions, declining cycle in the interest rate and country

risk, banks will rebound their intermediary function in the

second semester of 2006. Moreover, the implementation

of the improvement package for the investment climate,

infrastructure and financial sector will drive demand for

bank financing. However, it is estimated that a high

acceleration in credit growth will not occur considering

pressure, in spite of experiencing a rise in NPL from 2.2%

to 3.2%. This was attributable to high inflation, an

imbalanced condition to household income rise, aside

from the rise in interest rates. These factors influenced

household repayment capacity. Even though the total

consumption NPL ratio was still within the tolerance limit

of 5%, allocating credits through credit cards showed

the highest consumption credit risk reaching an NPL ratio

of 10.8%. The highest NPL was for foreign banks with a

high consumer credit share, specifically in the form of

credit cards. The rising tendency of this NPL ratio requires

vigilant management considering that credits through

credit cards are unsecured credits.

Similar to the corporate segment, the MSME segment

experienced a rise in credit risk with a rise in NPL ratio

from 5.9% to 7.4%. Although MSMEs tend to show high

resilience to economic shocks, the sharp hikes in fuel prices

Graph 4.13NPL - Industry Manufacturing

2001 2002 2003 2004 2005 2006

%

Garment

Wood working

Food and beverage

0

10

20

30

40

50

60

Graph 4.14Growth of NPL as of type

-100

-50

0

50

100

150

200

2000 2001 2002 2003 2004 2005 2006

%

Working Capital

Investment Loans

Consumer

Graph 4.15Gross NPL of SMES

2004 2005 2006

%

0

1

2

3

4

5

6

7

8

10

9

NPL - Investment

NPL - Working Capital

NPL Total

37


the rigidity of credit interest rates up to year end.

Furthermore, it is forecast that credit demand will rise,

specifically in infrastructure, as well as the agricultural/

plantation and mining sectors, considering the bright

prospects offered by these sectors. Credit quality is forecast

to improve in line with better corporate financial

performance and credit restructuring. Notwithstanding,

credit risk in disaster stricken areas will rise, specifically in

the Lapindo hot mud case.

Graph 4.16Gross NPL

(%)

-

5

10

15

20

25

30

35

2002 2003 2004 2005 2006

ConstructionReal Estate

MortgageProperty

38


Working CapitalConsumer

47.0% 38.5%

14.5%

Investment

Impacts of the Earthquake in Yogyakarta on Financial StabilityBox 4.1

Based on experiences from the Bali bomb incident

and the tsunami disaster in Aceh, the earthquake in

Yogyakarta will not threaten financial stability. This is due

to relatively modest systemic risk. Inter-bank obligations

between local banks are relatively small since banks in

this area are branch offices. Furthermore, the quantity

of credits channeled to the area is not substantial and

primarily extended to the retail sector. Nevertheless, the

deceleration of the intermediary function and a potential

rise in NPL in the area are inevitable.

Banks in the district of Yogyakarta (DIY)

The earthquake in the district of Yogyakarta (DIY)

on 27th May 2006 took substantial human victims and

ruined property. It influenced the economic condition

of DIY, including banking. There are 362 bank offices

in the area from 25 banks and one local bank with a

head office in DIY. A part of the outstanding credits in

DIY are assets of banks with offices outside DIY.

Credits in DIY represents only 0.8% of total

national banking credit, while deposits amount to 1%.

Typically, economic activity in DIY consists of small

industries or micro, small and medium-sized enterprises

(MSME), prevailingly trade sector, -working capital

credits-. Consumption credits have the highest share

compared to other types of credits. Prior to the

earthquake, credit quality in DIY was good with far

less NPL compared to the banking industry.

Deposits at banks are dominated by savings and

time deposits, primarily originated from Yogyakarta

City reached 73.3% and Bantul City was only 4.1%.

Therefore, if a rush of depositors occurs in Bantul City,

it will not affect the liquidity of banks in DIY.

The only local bank in DIY has total assets of

Rp2.0 trillion or 0.14% of total banking assets. Credit

quality at the bank is very good, as shown by an NPL

rate of only 1.6%. Pooled funds at the local bank

predominantly consist of demand deposits and savings.

Graph Box 4.1.2Type of Credit - DIY

Table Box 4.1.1DIY Banking Statistic (April 2006)

Total Loans Rp. 5.9 Triliun Total Deposits Rp. 11.7 Triliun

Share Share

- Loans in Bantul 15% - Saving 43.1%

- SME 85% - Deposits 38.1%

- Trading 23.70% - Demand Deposits 1.8%

- Working Capital 38.50%

- Consumer Loans 47%

Gross NPL 3.90%

Loans Deposits

Agriculture

Mining

Industry

Electricity

Construction

Trading

Transportation

Comercial service

Social service

Others

0.4%9.8%

0.0%

8.1%2.4%1.5%

23.7%

3.0%

48.0%

3.1%

Graph Box 4.1.1Sectoral Credit - DIY

39


Worst Case Scenario of Credit Quality in Bantul

The vast area in Bantul is devastated by the

earthquake. Outstanding credit located in the area

amounted to Rp866.1 billion, channeled by 37 banks

and 138 bank offices. Trade sector credits as well as

working capital credits and consumption credits,

recorded major share. Assuming that subsequent to the

earthquake all credits in the Bantul area become default,

gross NPL will experience a modest rise to 9.3%. Such a

rise will not significantly influence the banking system

stability, considering small share of credit in Bantul. This

scenario was created by performing a simulation on one

local bank and other commercial banks.

For one local bank, if all credits become defaults,

NPL will rise to 22.0%, which is far above the average

would require additional provisions amounting to

Rp218.2 billion. Since bank»s current profits is

inadequate, the remaining provisions have to be taken

from the capital. This leads to a drop in CAR far below

the minimum set of 8%, although it will not become

negative. Based on bank regulation regarding specific

treatment for bank credits after a natural disaster will

somewhat mitigate the impacts described above. If such

a scenario causes conditions of the local bank to

deteriorate, bank solvency will remain good as it has a

liquid asset portfolio consisting of government bonds

(SUN) Rp195.7 billion and Fasbi Rp359.3 billion, as well

as cash.

Credit allocated in Bantul area by other banks

represents only 0.1% - 0.4% of total bank credits. Using

the same scenario mentioned above, Gross NPL rate

will rise slightly to 0.01% - 0.036%, so that the

deficiency of provisions can be covered by current year

profits. Therefore, pressures in NPL will not influence

capital as banks recorded high CAR.

Based on such an analysis, the impact of the

earthquake in DIY will not generate financial system

instability. Nevertheless, sluggish recovery and

hampered credit allocation are inevitable, hindered

economic development in the area.

Table Box 4.1.2Bank Loans and Deposits in Yogyakarta

( April 2006 )

Total Loans Rp. 1 Triliun Total Deposits Rp. 1.7 TriliunLoans in Bantul Rp. 214.5 Miliar share

NPL 1.6% - Saving 31.8%- Deposits 24.7%- Demand Deposits 43.6%

Loans Deposits

40


The Threat of Hot Mudflow in Porong-Sidoarjo onFinancial StabilityBox 4.2

Following the earthquake in Yogyakarta and the

surrounding area, Indonesia faced yet another

catastrophic incident in the form of a high pressured

mudflow eruption. The mudflow began on 29th May 2006

and persists to this day. The eruption stems from an

exploratory oil and gas borehole known as Banjarpanji-

1, located in Porong-Sidoarjo, East Java, owned by PT

Lapindo Brantas. The ever increasing volume of the

mudflow and the contagion effects in the surrounding

area are accumulating and aggravating local economic

activities as well as the financial system in the area.

Impact on Local Activities

Short-term immediate impacts:

1. Houses and whole villages have been inundated in

the area surrounding PT Lapindo Brantas.

Furthermore, the radius of the affected area

continues to expand, engulfing the villages of

Jatirejo, Rono Kenongo, Siring and Kedung Bendo

with a total population of 9,789. This has displaced

residents and sparked a serious social crisis.

2. Nineteen factories employing approximately 1,873

staff have been forced to close. Consequently, the

unemployment rate has soared, thus undermining

economic growth.

3. Numerous micro, small and medium enterprises

(MSME) have been devastated. The area was

previously considered an artisan centre for leather,

silver, etc.

4. The closure of the Gempol-Surabaya toll road,

which passes through the affected area and

represents the fastest transportation lane to the

seaport, has severely hampered product

distribution. The resulting detour has raised

transportation costs and docking fees.

5. The mudslide is estimated to have destroyed 360

hectares of prime agricultural land including

plantations. In addition, 1,800 aquaculture

fishponds have been destroyed.

6. The devastation caused to property supply and

demand as well as the expected resulting increase

in real estate NPL funded by banks is estimated to

affect 4,709 debtors at two major banks.

7. Tourism in East Java, particularly in Malang and

other well-established tourism areas has witnessed

a dramatic decline.

The medium-term impacts of the mudflow include

a decline in business and economic activities, which will

raise banking NPL in East Java. This will discourage

foreign investors from East Java, thus disrupting regional

income. Eventually, this could affect national income,

considering that East Java contributes significantly to

Gross Domestic Income (GDP).

Impact on Compensation Claims

PT Lapindo Brantas is owned by PT Energi Mega

Persada Tbk (Bakrie Group) with an ownership share of

50%, Medco 32% and Santos 12%. The contribution

of PT Energi Mega Persada (oil and gas) and its subsidiary

companies to the Bakrie Group is substantial; ranked

third behind the coal sector (Bumi Resources) and

infrastructure/telecommunications (Bakrie & Brothers).

41


With such strong business integration within the Bakrie

Group, group financial performance could be adversely

affected. The Bakrie Group is estimated to own assets

totaling over Rp32 trillion with Rp10.2 trillion in

outstanding debt, more specifically Rp5.3 trillion in the

coal mining sector, Rp2.88 trillion for oil and gas and

Rp1.2 trillion for infrastructure and manufacturing.

The outstanding debt owned by the Bakrie Group

primarily stems from bank loans. This could destabilize

the banks involved should PT Lapindo»s problems not

be resolved immediately. Under its terms of operation,

PT Lapindo Brantas is insured against the possibility of

loss. However, the amount of insurance that will be

paid out by the insurance consortium is estimated to

total no more than US$25 million (Rp237.5 billion),

which falls well short of the loss incurred by PT Lapindo

Brantas. Furthermore, should the company be deemed

liable, PT Lapindo will be unable to settle the

compensation claims made by the affected population.

The assets of PT Lapindo are insufficient and the losses

continue to escalate. Therefore, the losses could affect

the Bakrie Group as a whole. The consortium will be

responsible to partially bare the costs of the loss as long

as the mudflow is deemed not due to an act of God/

force majeure.

Bank Credit Extension

The intermediation function in East Java is served

by 67 banks with 932 offices. Nine banks have their

central office located in East Java, spread out over 4

regencies and 1 municipality. In addition, citizens of East

Java are also served by 338 rural banks. The majority of

bank credit in East Java is extended to MSME with a

market share of over 60% as per June 2006. MSME

credit quality is relatively high with a gross NPL ratio of

just 4.1%. Credit extended by banks in Sidoarjo, the

area directly affected by the mudflow, represents a share

of 20% of total credit to businesses located in East Java.

Up to June 2006, credit quality in Sidoarjo exceeded

the NPL indicative limit of 5%. As such, the hot mudflow

in Sidoarjo is guaranteed to raise NPL in the area.

Worst Case Scenario

With the assumption that all credit extended by

banks to Sidoarjo is non-performing, bank NPL will rise

by Rp7.6 trillion. This in turn will raise gross bank NPL

from 8.3% to 9.4%. Taken holistically, such a rise is

relatively insignificant; however, when reviewed

individually the gross NPL ratios of four banks are

expected to exceed the industry average. The affected

banks include two banks with central offices in East Java,

one joint-venture bank and one state-owned bank.

Initially, the NPL of the state-owned bank was below

6%, which indicates the rise in NPL is a consequence of

unpaid mortgages.

Additional provisions are required to offset the rise

in gross NPL. With current year profits estimated to be

insufficient, the difference has to be paid using capital.

For other banks, increases in gross NPL ranged between

0.1% - 7.7%. Furthermore, the deficit in credit

provisions could be covered by current year profits. The

banks have relatively high CAR, ergo; the impact of a

rise in NPL would not affect capital.

If the worst-case scenario outlined above transpires

it could compound conditions of the three domestic

banks. As a result, banks would have to withdraw their

fund placement or limit their credit extension to the local

banks, enabling the three aforementioned banks to meet

42


Graph 4.18Liquidity Ratio

Provisions

Despite the rising credit risk pressures, the net NPL

ratio showed only a slight rise from 4.8% to 5.08%, due

to ample provisions made by banks. Provisions commenced

to show a rising tendency to confront the persistently high

NPL ratio. This indicated that banks have strong resiliency

in confronting the credit risk pressure, laying a solid ground

for banks to sustained steady profitability and solid

solvability.

Graph 4.17Loans, NPL and Provision

0

10

20

30

40

50

60

70

80

90

100

2000 2001 2002 2003 2004 2005 2006

Loans (rhs)Pr (lhs)NPL (lhs)

0

100

200

300

400

500

600

700

800Trillions of Rp Trillions of Rp

(NCD) kept on rising, reaching 130.5% in May 2006. This

was influenced by the greater rise in liquid instruments

compared to the rise in short-term liabilities. The rather

high increase in liquid instruments occurred on the deposit

component of Bank Indonesia, specifically BI Certificates,

which during some of the most recent auctions absorbed

greater liquidity. This is in line with the high interest rate

of low risk BI Certificates (SBI). Demand deposits at Bank

Indonesia, including reserve requirement, increased in line

with a rise in deposits.

Liquidity in the banking sector increased reaching

Rp1.163 trillion, with growth of 15.50% (y-o-y). Rupiah

deposits showed a great increase, while foreign currency

their liabilities. At the end of June 2006, each bank had

sufficient placements at other banks and adequate SBI

to cover inter-bank liabilities. Consequently, no inter-

bank systemic risk would emerge.

In conclusion, the mudflow incident is not

expected to trigger short-term financial system instability.

However, over the medium and long term, if the Lapindo

incident is not resolved, contagion effects are expected

and need to be mitigated. This will raise operational

costs in the business community, undermine the property

sector, increase the NPL ratio for mortgages and cause

the closure of numerous MSMEs as well as other small

business centers. If this is allowed to occur, bank NPL

will continue to rise and eventually adversely impact

banks with central offices in East Java, especially small

banks and rural banks.

Liquidity Risk

Up to the first semester of 2006 liquidity risk was

dissipating and this was reflected by a rise in the ratio of

liquid instruments held by banks. Since the beginning of

2006, the ratio of liquid instruments to non-core deposits

140

180

220

260

300

61

71

81

91

101

111

121

131

2002 2004 2005 2006

Des Jun Mar Dec Mar Jun

Notes: Liquid Assets consist of Cash, Demand Deposit at BI, CBI, and BI o/n FacilityNon Core Deposits (NCD) consist of 30% Demand Deposits and Savings, and 10% Time Deposits of1 - 3 months maturing.

%Trillions of Rp

NCD (lhs)Liquid Assets (lhs) Liquid Assets/NCD (rhs)

43


Graph 4.19Deposits

2004 2005 2006-20

-10

0

10

20

30

40

50

60%

Saving

Times Deposits

Demand Deposits

deposits decreased due to appreciation in the exchange

rate of the rupiah against the US dollar. Rupiah deposits

experienced a jump in demand deposits amounting to

Rp20 trillion, near the end of the first semester of 2006.

In addition, amidst lower public liquidity, the increase in

banking liquidity, among others, was caused by the wealth

effect of a bullish stock market and migration of

government funds from the central bank. Furthermore,

entrepreneurs tended to reallocate business funds to

deposit temporarily, due to weaker purchasing power and

rising interest rates. Although deposit insurance was

limited, where since 22nd March 2006 the maximum

deposit insured was set at Rp1 billion per depositor per

bank, so far there have been no strong indications of

substantial fund migrations from the perceived unsound

Graph 4.21Deposits Structure - Per Ownership

bank to the perceived safer banks or fragmentation of

large savings into smaller ones.

Deposits were less balanced with a concentration by

92% of short-term, up to 3 months. In addition, savings

with a nominal value over Rp100 million with a share

reaching 75.7%, controlled by only 2% of all account-

holders. Such conditions indicate that banks liquidity is

exposed to a potential risk of sudden substantial

withdrawals by large accountholders. However, research

results showed that 40%-60% of the deposits inclined to

be over the medium term, both in the form of automatic

roll over (ARO) and savings not withdrawn. This indicates

that banking still forms the most important outlet for public

funds investment and it proves that banking in Indonesia

is still reasonably credible.

0

20

40

60

80

100%

2003 2004 2005 2006Dec Jun Oct Dec Jun Dec Feb Apr Jun

SOE Insurance Individual OthersPensiun Fund

32.7%

57.5%

7.4%

Graph 4.22Deposit Structure - Per Nominal Amount

7.4

92.6

70.3

29.7

11.2

88.8

Demand Savings Times Deposits Total

%

75.7

24.3

>100jt<100jt

SavingDemand Deposits Times Deposits

0

20

40

60

80

100%

2003 2004 2005 2006

Graph 4.20Deposit Structure

44


The Impact of Limited Insurance Scheme ImplementationBox 4.3

Commencing September 22, 2005, the blanket

guarantee scheme was phased out and replaced by a

limited deposit insurance scheme provided by the

Indonesian Deposit Insurance Corporation (IDIC). The

phasing out is aimed at reducing budgetary burden to

the state and eliminating moral hazard. On the basis

of Law No 24/2004, IDIC has two functions: (1) to

provide deposit insurance services; and (2) to undertake

resolution of failure bank.

IDIC insures demand deposits, savings, certificate

of deposits, time deposits and all similar deposit items.

To prevent unexpected negative consequences, the

phasing out has been implemented in the following

stages:

September 22, 2005 √ March 21, 2006 - all

deposits are insured.

March 22, 2006 √ September 21, 2006 - deposits

up to Rp5 billion are insured.

September 22, 2006 √ March 21, 2007 - deposits

up to Rp1 billion are insured.

March 22, 2007 - onwards - deposits up to Rp100

million are insured per bank per customer.

By providing insurance coverage of Rp100 million,

the IDIC has insured 98% of assessed deposit accounts.

This is due to the fact that the number of account less

than Rp100 million is 98% of total customer accounts

in banking sector.

There are two potential negative consequences

are identified in the lights of the commencement of

limited insurance scheme:

1. Depositors will break their deposits account into

smaller pieces of amount up to Rp100 billion.

2. Migration risks, as depositors will tend to shift to

the perceived sounder banks from the perceived

less sound bank (switch to quality).

Nevertheless, during the course of the first half

of 2006, the two above-mentioned problems appeared

to be distant. First, deposits with nominal value of Rp1-

5 billion grew rapidly, whilst on the other hand, those

with nominal value of Rp100 million to Rp1 billion

trended downward. Second, the share of high value

accounts remained the same, stayed at 0.02% of total

deposits held by banks. Finally, there was no switch to

quality and fund migration from one to other bank.

Based on bank daily reports, deposit base expansion

occurred not only in the big banks, but also in small

and medium size banks. Moreover, the medium size

banks recorded a rapid growth of deposit base, whilst

on the other hand, deposit base in foreign banks has

been in a declining trend.

Albeit these facts, Bank Indonesia has exercised

strong vigilance to prevent the unexpected outcome of

limited insurance scheme implementation, particularly

to the liquidity risk exposure of banks. On the other

side, banking customers may shift their portfolio away

from banking products to speculative instruments,

rendering financial system in a potential risk. These

notions are based on the following rationales:

a. The phasing out of blanket guarantee will

continue up to March 22, 2007 with limited

coverage of maximum Rp100 million per

customer per bank.

b. Refer to our banking confidence index survey,

large depositors have exercised anticipative

45


Table Box 4.2.1Account Distribution

Sep'05 Dec'05 Jan'06 Feb'06 Mar'06 Apr'06 May'06 Jun'06

< 100 jt 98.19 98.10 98.10 98.14 98.17 97.96 98.00 98.04

100 jt - 1 M 1.69 1.77 1.77 1.73 1.69 1.88 1.84 1.80

1 M - 5 M 0.11 0.11 0.11 0.11 0.11 0.13 0.14 0.13

> 5 M 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

(%)(%)(%)(%)(%)

Graph Box 4.2Ω.1Deposits

Trillions of Rp

165.86

27.12

84.77

52.74

817.14

134.74

22.29

93.47

43.77

828.05

June '06Dec '05

Large Bank

Medium

Small

Foreign

Joint Venture

A rise in deposits occurred not only in large banks

but also in medium and small banks. The medium-

sized banks showed the highest rise. On the other hand,

deposits made at foreign banks are likely to decrease.

Notwithstanding, the near-term effects of the

limited deposit insurance scheme implementation on

bank liquidity risk have to be tightly vigilance,

considering the following factors:

a. Limited deposit insurance coverage will continue

to be phase in until 21st March 2007. However,

thereafter all bank deposits up to Rp100 million

per customer per bank are insured.

b. Survey results indicated that some depositors,

specifically corporations, are beginning to take

various measures to anticipate limited deposit

insurance coverage: (i) more than 50% of the

respondents stated that they will be more selective

in choosing banks, (ii) to save only in government

banks or foreign banks, (iii) to reallocate the

investment portfolio into other products in the

financial sector and non-financial sector.

measures by: (a) exercising extra prudent

procedures in selecting banks; (b) placing deposits

in only state-owned banks; (c) shift their portfolio

in banks to other financial instruments or investing

in non-financial assets.

Market Risk

Amidst high interest rates, banks had capacity to

mitigate market risk, thus preventing instability in the

banking system. Stress test results showed that the

majority of banks were able to absorb market risk,-interest

rates coupled with sharp depreciation of the rupiah-, as

reflected by a stable CAR. In addition, interest rates of

both bank credits and savings began to decline in June

2006 as an effect of the decline in the BI Rate.

Furthermore, stronger rupiah did not lead to banking

instability due to the ability of banks to better mitigate

exchange rate risk. This was reflected by the relatively

controlled overall Net Open Position (NOP) at below

maximum 20% threshold. Nevertheless, since the

maturity profile of banks liabilities were generally in a

short-term maturity gap, banks must remain vigilant of

interest rates rise. This may incite more potential market

Table 4.1Assumptions and Scenarios

Variable

Decline in BI Rate 100 - 500 bps

Increase BI Rate 100 - 500 bps

Depreciation of IDR 1000 - 2500 poin

Volatality of IDR/US$ 65%

Scenario

46


Graph 4.23Deposit - Lending Rate Spread

10

11

12

13

14

15

16

17

18

19

4

5

6

7

8

9

10

11

12

13

14

2006200520042003

Spread

Working CapitalTimes Deposits 1 month

% %

Graph 4.24NII and Certificate of Bank Indonesia Rate

-

1

2

3

4

5

6

7

8

0

2

4

6

8

10

12

14

16

18

20

2000 2001 2002 2003 2004 2005 2006

NII (lhs)CBI 1 month (rhs)

% %

Table 4.4CAR - IDR Depreciation Scenario

18.68% 18.67% 18.67% 18.66% 18.66% 18.66% 18.65% 18.64%

500 bp 1000 bp 2000 bp 2500 bp 3000 bp 4000 bp 5000 bpCAR Initial

risk pressure compared to the movements in exchange

rate and government bonds price.

Table 4.2CAR - BI Rate Increased Scenario

18.55% 18.00% 17.45% 16.89% 16.34% 15.79%

100 bp 200 bp 300 bp 400 bp 500 bpCAR Initialas rupiah depreciated by 5000 points. A well-controlled

Net Open Position (NOP) - far below 20% - formed the

backbone of strong banking capitalization to overcome

exchange rate risk.

Profitability

Although credit risk pressure increased, the

profitability of banks during the first semester of 2006

remained stable. Buoyant income in line with the

persistently high interest rate, especially in credit, BI

Certificates and government bonds, supported such a

condition. The performance of banks is illustrated by the

wide interest spread, reaching 4%, and the significant rise

Table 4.3CAR - BI Rate Declined Scenario

18.55% 19.11% 19.66% 20.21% 20.77% 21.32%

100 bp 200 bp 300 bp 400 bp 500 bpCAR Initial

Stress tests are regularly conducted to measure the

resilience of banks to market risk pressures, particularly to

interest rate as well as exchange rate risks. The stress tests

use the assumptions as in the table. Stress test results

showed that, banks have sufficient resilience to absorb

interest rate risk. With the sharp rise in the BI Rate reaching

500 bps, CAR experienced a decline but still remained

above 8%. Such a condition is related to the structure of

bank assets experiencing relatively modest market risk

exposure. Besides, bank capitalization to cover market risk

was relatively high. In addition, banks have sufficient spread

to anticipate the possibility of drastic rises in domestic

interest rates. Likewise, a dip in interest rates did not

influence the rise of market risk faced by banks, but

conversely, bolstered the structure of the earning assets

of banks. Supporting by interest rates declining cycle, banks

are well-capitalized and have capital structures that are

more resilient to market risk as reflected by solid CAR.

Confront to exchange rate risk, banking capital was

sufficient to insulate the negative impacts. Based on the

stress tests, large banks were resilient despite holding

relatively larger foreign currency portfolios then other

groups of banks. On average, banks CAR declined 3 bps

47


Graph 4.25Cost Efficiency Ratio and ROA

0

20

40

60

80

100

120

140%

2000 2001 2002 2003 2004 2005 2006-8

-6

-4

-2

0

2

4

6%

ER (lhs)ROA (rhs)

in net interest income (NII). Nevertheless, returns on assets

(ROA) remained stable at 2.54% due to an increase in

income as well as assets. The rise in credit risk pressure

caused banks to form somewhat larger provisions

triggering an increase in operational costs. This increase

in operational costs caused the banking efficiency ratio to

decline. However, it significantly improved at the end of

the semester.

In the short term, the profitability of banks is

estimated to improve, mainly due to a drop in the interest

rate and a stable exchange rate. Nevertheless, the

maximum performance of banks is determined by the

capability of banks to manage the risk. The major challenge

of banks is deteriorating credit quality, which raises NPL.

Capital

Banks was resilient to various risk pressures,

supported by substantial capital. Improvement in

profitability contributed solid CAR, reaching 20.5%. The

greater part of the capital is core capital (Tier I) with a

ratio of 17.9%, increased from the previous period 16.4%.

In addition, banks capital improvement was also driven by

a minimum capital of Rp80 billion as stated in the

Indonesian Banking Architecture (IBA) program. This

triggered an increasing core capital (Tier I) as well as CAR.

In line with profitability prospects, the capital of banks

will be determined primarily by the performance of risk

Graph 4.26Komposisi Pendapatan Bunga

0

25

50

75

100

Jun Dec Mar Sep Dec Mar May Jun2004 2005 2006

7.8 6.9 6.8 8.4 8.9 9.8 9.5 9.2

56.4 59.7 63.2 63.2 63.1 59.7 59.3 59.2

26.3 25.1 22.2 21.9 22.0 23.2 22.7 22.9

9.5 8.3 7.7 6.5 6.0 7.4 8.4 8.7

%

LoansSecuritiesBI Others

Graph 4.27Revenue Structure of 15 Large Banks

0

25

50

75

100

Jun Dec Mar Sep Dec Mar May Jun2004 2005 2006

%

6.2 5.0 5.3 6.1 6.4 6.9 6.8 6.5

53.0 56.8 61.1 61.3 61.5 58.5 58.1 58.4

32.7 31.4 27.5 27.8 27.8 29.7 29.2 29.0

8.0 6.8 6.1 4.8 4.3 4.9 6.0 6.2

LoansSecuritiesBI Others

management. In general banks» capital is sufficient and

capable of supporting credit growth as well as credit risk.

However, several banks have marginal CAR exposed to

vulnerable, mainly the threat of credit risk.

In the second semester, the resilience of banking

system is forecast to improve in line with better

macroeconomic condition. Intermediary function is

expected to recover moderately as interest rate rigidity still

exists. This is supported by positive business and consumer

confidences. Declining interest rate cycle, packages of

financial sector policy, investment climate and infrastructure

are expected to boost the intermediary function of banks

and promote credit quality. Bank credits will still

concentrated in working capital, yet credits to corporate

sector are expected to enhance selectively, especially in

infrastructure. This is indicated by the commitment of

48


Graph 4.30CAR as of Bank Peer

15

16

17

18

19

20

21

22

23

24

25

26

2005

%

Large Bank

Other Bank

Industry average

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec2006

Jan Feb Mar Apr May Jun

Graph 4.29Tier 1 to Risk Weighted Asset (June 2006)

0.0

5.0

10.0

15.0

20.0

25.0

30.0%

Tier 1 : RWACAR

Bank

15LB Foreign JV Others IndstAverage

A B C D E F G H I J K L M N O

Bureau and the refinement of the Debtor Information

System will lessen potential credit risk from new debtor.

Nonetheless, NPL will only occur in areas stricken by

disasters, such as the earthquake in Yogyakarta, hot mud

flooding in East Java and the tsunami on the south coast

of Java. This is projected to have insignificant impacts on

banking stability. NPL improvement is supported by an

augmentation of corporate income and stronger

purchasing power in line with the declining inflation and

interest rates.

Bank liquidity is estimated to rise despite the

commencement of limited deposit insurance

implementation beginning in March 2007. It is estimated

that banks will remain the prime outlet option for public

investment funds, considering limited public knowledge

in financial market investment.

banks to provide funds to the amount of Rp100 trillion to

infrastructure development.

Credit risk pressure will alleviate in line with the

macroeconomic improvement that buttress better NPL.

In addition, NPL resolution of two large banks, which is

nearly complete, will also reduce NPL significantly.

Moreover, the establishment of the Credit Information

Graph 4.28Capital Adeguay Ratio

10

12

14

16

18

20

22

24

26

28%

CAR

2002 2003 2004 2005 2006

49


Credit Information Bureau and Debtor Information SystemBox 4.4

The establishment of Credit Information Bureau

(CIB) is one of initiatives under the auspices of the 5th

pillar of Indonesian Banking Architecture (IBA), which is

aimed at building robust infrastructure for banking and

financial sector. Furthermore, the objectives of CIB

development is also to improve the efficiency of bank

and non bank financial institutions» financing and risk

management via the availability of quality debtor

information system.

Prior to CIB, Bank Indonesia had established Credit

Information System (CIS) and developed as Information

System of Funding Provision (ISFD). The units had

relatively the same tasks as existing CIB. Since 2005, the

system has been improved into the Debtor Information

System (DIS), which provides comprehensive information

of individual debtors. The DIS is ultimately aimed at

eliminating information asymmetry. It enhances

effectiveness of banking intermediation by reducing

potential credit risk exposures as lenders have information

of creditworthiness of their potential debtors in advance,

a conditions leading to the stability banking sector in

the long-term. The DIS has the following features:

a. The scope of reporting institutions includes

commercial banks, rural banks, Islamic rural banks,

non-bank credit card issuers, and non-bank financial

institutions. Reporting is mandatory for all banks

with total assets of more than Rp10 billion and

voluntary for non-banks.

b. The report includes all financing by reporting

institutions, starting from Rp1.

c. The monthly reports should be submitted on line

via a web-based system to Bank Indonesia.

d. Sanctions will be applied to those not submitting

the reports and delay submissions.

e. Reporting institutions fully complying with terms

and conditions set in advance are granted access

to the real-time and on line Individual Debtor

Information (IDI). The coverage of IDI includes

information of debtor identity, ownership,

shareholders, loans granted by other banks,

outstanding amount, collateral, and credit quality.

The information is beneficial for banks as the basis

for their credit analysis processes.

The establishment of CID and DIS has the

following benefits:

For Lenders:

Minimize asymmetric information problem. It helps

to expedite the process of credit analysis and

approval, including mitigation of adverse selection.

Comprehensive and accurate information in DIS

buttresses effective risk management. Therefore,

banks have more capacity to prevent and alleviate

non-performing loans.

Reduce dependency on conventional collateral

scheme in financing. Lenders will be stimulated

to assess creditworthiness and reputation of

debtors as one of the main factors for credit

approval.

For Debtors:

Speed up credit approval

New debtors will likely to enjoy wider access to

financing as their credit reference and

creditworthiness are disclosed to all banks and

other financial institutions.

50


Graph 4.31Financial Structure of Multifinance Companies

Trillions of Rp

0

5

10

15

20

25

30

35

40

45

50

2000 2001 2002 2003 2004 2005 2006

Factoring

Credit Card

Consumer Payment

Leasing

NON BANK FINANCIAL INSTITUTIONS

Multi-finance Companies

Stability of the multi-finance industry was

maintained amid upward credit risk and a restrained

source of funds.

Conditions in banking sector during the reporting

period spilled over to the multi-finance industry. Bank

financing, the main source of funds for multi-finance

companies, was restricted in the reporting period. This

decelerated financing expansion despite upbeat business

prospects. As a result, during the first quarter of 2006 the

business volume of multi-finance companies declined

significantly but rebounded by the end of semester I-2006.

Along with the slowdown in economic activities and

consumer purchasing power, risk exposure to multi-finance

companies increased slightly but remained controllable.

The profitability of multi-finance companies declined in

early 2006, however it rebounded gradually. Nevertheless,

fresh capital injection strengthened the solvency of such

companies.

Business Volume

Multi-finance companies are increasingly playing a

greater role in the Indonesian financial sector. The business

activities of these companies have expanded; reflected by

an increasing volume of financing equivalent to 10% of

total credit allocated by banks. During the reporting period,

business activities decreased in early 2006 but rebounded

by the end of semester I 2006. Consumer financing

rebounded whilst other types of financing slowed. Credit

card financing, on the other hand, plummeted in line with

the upward trend of NPL. This was the result of a drop in

repayment capacity commensurate with inflationary

pressures and a rising cost of living.

With the exception of consumer financing, the

slowdown in business activities was accompanied by

persistent upward risk pressures, indicated by an increase

in provisioning for financing losses. However, risk

measurement of multi-finance companies seemed to be

more lenient than of banking institutions, resulting in a

biased risk profile. Nevertheless, the establishment of the

Credit Information Bureau to facilitate the debtor

information system including multi-finance companies, will

reduce asymmetric information. Therefore, the ability multi-

finance companies to mitigate credit risk will significantly

improve.

The vast majority of consumption financing is for

automobile financing, which offers more attractive rates

and procedures than those offered by banks. This is

possible as several multi-finance companies are affiliated

with the automotive industry. Such affiliation has

empowered finance companies to facilitate and provide

affordable financing for customers. In addition, the

domestic market for vehicles, particularly motorcycles,

has shown bright prospects. Fuel price hikes were the

primary factor encouraging the shift towards

motorcycles as the main means of transportation for

low to middle income earners. Furthermore, the

historical performance of consumption financing has

been positive with lower NPL resulting in a more

manageable credit risk profile. Therefore, demand for

this segment is still prospective.

51


Moreover, investment in securities by multi-finance

companies increased significantly, including BI certificates

and government bonds. This development warranted

vigilance as finance companies preferred to shift from their

intermediary function to invest in financial markets.

Source of Funds

Finance companies accumulated balanced funding

from domestic and offshore sources with the vast majority

stemming from banks (67%). With hikes in domestic

lending rates, funding from banks plummeted. In addition,

banks undertook credit rationing to finance companies,

meanwhile, offshore funding dried up. This undermined

financing in some market segments, however, leasing for

heavy equipment and consumption financing remained

prospective. Soaring demand for coal as an alternative

source of energy boosted leasing activities, especially in

East Indonesia. However, high dependency on bank

financing might trigger contagion risk in the banking

system. Conversely, systemic banking crisis will directly

impact multi-finance companies. Compared to banks,

financing allocated by multi-finance companies was

relatively small, totaling 3%.

Alternative sources of funding for multi-finance

companies originated from the non-bank financial system,

including bonds issuance. The use of bonds as an

alternative source of funding began in 2002. Bonds

represent an alternative source of funding amidst

constraints to bank credit. The majority of multi-finance

companies listed in the capital markets are those affiliated

with the automotive industry, which is driven by the

strategy to maintain sustainable vehicle production as well

as meet high demand. All bonds issued in semester I 2006

were by multi-finance companies, totaling Rp3.67 trillion.

These included Summit Oto Finance I, Federal International

Finance VI, Perum Pegadaian XI, Adira Dinamika MF II and

WOM Finance III. Despite the interest rate hikes in 2005,

multi-finance companies continued to issue bonds due to

prospective business, particularly in leasing and

consumption financing.

Multi-finance companies posted a moderate level of

leverage, reflected by a falling debt to total asset ratio

from 0.76 to 0.74. However, the ratio of debt to financing

was 1.07, indicating the dominance of credit. This indicated

Graph 4.32Securities and Loan Loss Provisions

Trillions of Rp

0

1

2

3

4

5

6

2000 2001 2002 2003 2004 2005 2006

ProvisioningSecurities

Graph 4.33Source of Funds

Trillions of Rp

0

10

20

30

40

50

60Bank Loans

Non Bank Loans

Bond Issurance

Subordinated Debt

2000 2001 2002 2003 2004 2005 2006

Graph 4.34Funding Structure

Trillions of Rp

0

5

10

15

20

25

30

35

On shore

Off shore

2000 2001 2002 2003 2004 2005 2006

52


Graph 4.36Capital/Financing

%

0

5

10

15

20

25

30

2000 2001 2002 2003 2004 2005 2006

Capital/FinancingCAR

Graph 4.35Debt/Assets, and Debt/Financing Ratios

0

0.2

0.4

0.6

0.8

1

1.2

1.4

2000 2001 2002 2003 2004 2005 2006

Debt/Assets

Debt/Financing

that the intermediary function of multi-finance companies

exceeded banks. Consequently, multi-finance companies

will demand significant amounts of funding. Nevertheless,

constraints to bank credit temporarily discouraged the

expansion of multi-finance companies.

Profitability and Solvency

Along with the decline in business volume and

mounting credit risk, the profitability of multi-finance

companies declined slightly at the beginning of 2006, but

rebounded gradually in the subsequent period due to

seasonal factors. This was reflected by the return on assets

(ROA), which achieved 1.4% and the return on equity

(ROE) of 10.2%. Furthermore, this boosted the ratio of

capital to total assets from 12.30% (December 2005) to

13.96% (June 2006), whereas the ratio of capital to

financing also increased; to 20.00% (June 2006) from

17.60% (December 2005). Relevant indicators reflected

sufficient ability of multi-finance companies to mitigate

increasing financing risks.

Persistent high demand for consumption financing

is expected to drive the expansion of multi-finance

companies. In addition, relatively attractive investment

financing through capital goods leasing provided generous

opportunities for business expansion. Moreover, multi-

finance companies are likely to issue bonds and raise

offshore funds, as banks delayed cutting their lending rates

in 2006. Consumer purchasing power will not recover

significantly due to low expected economic growth in the

second semester of 2006. Consequently, growth in

consumption financing will remain limited but prospective.

Financing segments that remained promising

include motorcycle financing and leasing in the mining

sector. However, all multi-finance companies must become

more vigilant in expanding their consumption financing

portfolio to offset the probability of default. Regulations

targeting multi-finance companies, namely strengthening

capital structure, enhancing regulatory quality, supervision

and examination, are expected to improve the prudence,

performance and soundness of multi-finance companies

significantly.

CAPITAL MARKET

Equity Market

The Jakarta Composite Index skyrocketed due to

transactions dominated by foreign investors.

Although the equity market faced slight pressures

by the end of semester I 2006, generally, conditions

remained stable.

Foreign investors dominated buying rallies in the

equity market and this boosted stock prices expeditiously.

Notwithstanding, the bullish rallies were neither driven by

fundamental factors nor the performance of issuers. This

53


could indicate a price bubble in the equity market. The

rallies, however, were cut short by the Fed Fund Rate hike,

albeit insufficient to trigger a crash. Prevailing positive

sentiment surrounding yield in the domestic markets

prevented unexpected selling by foreign investors and

subsequent capital outflows. In terms of new issuances,

constraints to banking credit, triggered by interest rate

hikes stimulated corporations to raise funds from the equity

market. The nominal value of initial public offerings (IPO)

in semester I rose significantly over the previous semester.

The equity market is expected to remain bullish, albeit

its pace slower than the previous period. This is supported

by improvements in macroeconomic indicators, a higher

sovereign rating and soaring international commodity

prices, as well as prospective business opportunities in

terms of infrastructure and alternative energy sources.

Equity Market Performance

The equity market enjoyed bullish rallies, however,

corrections occurred at the end of semester I 2006. This

was evidenced by a significant jump in the Jakarta

Composite Index (JCI) during the first five months of the

semester, posting its highest level in history: 1,553.06 (May

2006) from 1,122.37 (December 2005). Foreign investor

transactions and regional factors in emerging market

countries supported the bullishness of the equity market.

Furthermore, the improved sovereign rating of Indonesia

and buoyant global commodity prices also contributed to

the rallies. Political instability in the Philippines and Thailand

benefited the Indonesian equity market as foreign investors

redirected their portfolio. On the other hand, positive

sentiment stemmed from better inflation expectations for

2006 and the postponed hike in the basic electricity tariff.

Over optimistic investors dramatically boosted share prices

and related indices, which was also supported by the

herding behavior of local investors. Real sector and

corporate fundamentals are yet to signal significant

strengthening, which can indicate a price bubble. However,

the rallies mentioned strengthened the rupiah exchange

rate by 11.46% and improved forex reserves.

At the beginning of the semester, domestic and

global interest rate expectations were positive attributable

to a peak in the Fed Fund Rate Cycle at 5%. Nevertheless,

expectations reversed subsequent to the Fed continuing

its rising cycle; a condition that spurred expectations of a

persistent Fed Fund Rate rise. This sparked a capital reversal

from emerging markets, including Indonesia. As a result,

the JCI plunged by 10% within a week, proving the

existence of a price bubble. Violent fluctuations in the JCI

were evidenced by relatively high volatility, peaking in May

2006 at 2%; surpassing average volatility during the first

semester at 0.87%.Source : Bloomberg

600

800

1,000

1,200

1,400

1,600

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

2005 2006

JCI (lhs)

Volume (rhs)

Jan Feb MarApr May Jun Jul Aug Sep Oct Nov Dec Jan Feb MarApr May Jun

Volume Shares-Millions

Graph 4.37Jakarta Composite Index and Volume of Shares

Graph 4.38Foreign Investors Transactions

Source : Bloomberg

(20,000)

(15,000)

(10,000)

(5,000)

5,000

10,000

-

Billions of Rp

600

800

1,000

1,200

1,400

1,600

Net Foreign (lhs)JCI (rhs)

2005 2006Jan FebMarApr May Jun Jul AugSep Oct Nov Dec Jan Feb MarApr MayJun

54


Graph 4.41Foreign Investors Trading

Sources : CEIC and Bloomberg

-

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

600

800

1,000

1,200

1,400

1,600Volume - (lhs)Trading Value (Billion Rp) - (lhs)JCI (rhs)

2005Jan Feb MarApr May Jun Jun Aug Sep Oct NovDec Jan Feb MarApr MayJun

2006

Graph 4.39Volatility of JCI

Source : Bloomberg

0

5

10

15

20

25

30

35

40

(y = 509.23e-0.0013x))

VJSX (lhs)

Expon. (JCI (rhs))

0

200

400

600

800

1000

1200

1400

1600

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

JCI (rhs)

Indonesia remained on the list of pension funds of

the California Public Employee Retirement System

(Calpers). This fostered positive sentiment regarding

investment in the Indonesian equity market, amid

inauspicious global interest rates. Furthermore, positive

signals of the falling BI rate cycle, beginning in May 2006,

helped stabilize the market and stimulate transactions

despite a Fed Fund Rate hike to 5.25% (June 29, 2006).

At the end of semester I 2006, the index closed at

1,301.26, an increase of 147.63 bps (12.70%) over the

end of 2005.

The bullish equity market augmented market

capitalization, which reached its highest ever level of

Rp1,004 trillion in April 2006, despite a subsequent drop

to Rp901 trillion as a result of market risk pressures. A

dramatic rise in transaction value was witnessed in semester

I 2006, reaching record levels in May at Rp61.11 trillion

before nose-diving to Rp29.08 trillion in June 2006.

The rush for blue chip shares in certain sectors, new

IPO and rights issues drove significant market capitalization.

In semester I 2006, six new initial public offerings emerged

by Bakrie Telcom (Rp605 billion), Malindo Feedmill

(Rp53.68 billion), Okansa Persada (Rp9.35 billion), Bank

Bumi Artha (Rp5.4 trillion), Bank Bukopin (Rp295.32

billion), and PT Radiant Utama Interinsco (Rp42.50 billion).

The new IPOs totaled Rp6,38 trillion, exceeding the

previous year of Rp3.50 trillion. Listings by banks were

sound and stemmed from the business plan to meet the

capital adequacy requirement in Indonesian Banking

Architecture.

Several sectors dominated market capitalization,

including mining, agriculture, infrastructure, finance and

retail. The persistent trend of high commodity prices in

global markets, including natural gas, gold and coal, drove

high-return expectations in these sectors. Bullishness in

the mining sector raised the mining index by 20.69%.

Bullish market sentiment contributed to share trading in

the mining sector, including the merger between Bumi

Resources and Energi Mega Persada. Furthermore, share

selling by Bumi Resources provided significant capital

inflows to Indonesian markets. In addition, the resolution

of the dispute between Pertamina and Exxon Mobile over

Graph 4.40JCI and Market Capitalization

Sources : CEIC and Bloomberg

600

800

1,000

1,200

1,400

1,600Billions of Rp

Capitalization (lhs)JCI (rhs)

2005Jan Feb MarApr MayJun Jun Aug Sep Oct Nov Dec Jan Feb MarApr MayJun

2006

600,000

700,000

800,000

900,000

1,000,000

1,100,000

55


the Cepu Exploration Block sparked positive sentiment

concerning mining sector shares.

In addition, initiatives to explore alternative sources

of energy were the main driving factor for investors to

shift their portfolio to the agricultural sector. Unrelenting

high crude palm oil prices in global markets induced buying

rallies of agribusiness shares and, raised the index

dramatically by 34.01% on average. This was

predominantly supported by the soaring share price of

plantations. The telecommunications sector also remained

buoyant with companies like PT Telkom (the largest

telecommunications company in Indonesia), among others,

successfully maintaining their blue chip position. High

demand and positive growth in the telecommunications

industry reflected the bright prospects of this sector and,

consequently, drove investors to take long positions.

The financial sector remained the target of portfolio

diversification, however, its shares no longer dominated

shifts in the composite index. Uncertainty surrounding the

impact of interest rate and foreign exchange risks

encouraged investors to become more prudent when

investing in financial sector shares, and lead to a slowdown

in market capitalization. Soaring interest rates adversely

impacted the asset quality and profitability of banks as

well as limiting their intermediation function. However,

strong investor appetite for banking shares remained due

to robust fundamentals and attractive gains. In addition,

the shares were awarded a higher rating, which attracted

investors to take long positions.

The equity market is expected to remain bullish

attributable to improved macroeconomic indicators

including lower inflation and interest rates, a stronger

balance of payments (BoP) as well as a higher sovereign

rating. Confidence in the Indonesian economy has grown;

therefore, expectations regarding near-term gains will

remain positive. Foreign investors are expected to dominate

transactions until year end. Nevertheless, all authorities

must become more vigilant in terms of capital reversal risks.

In addition, the Fed Fund and BI rates, global commodity

prices and country risks will remain the drivers of price

movements in the near future.

Initiatives to deepen capital markets, including the

merger of the Jakarta Stock Exchange and Surabaya Stock

Exchange, remote trading, refining regulations and e-

reporting, e-licensing, e-registration and e-monitoring, are

expected to attract more investors. To enhance the capital

market as a source of funds for real activities, IPO

procedures for new listings will be simplified. Among

others, key regulatory relaxation includes tax relief for new

listings in the equity markets. In future, initial public

offerings are expected to increase significantly

commensurate with the improved economy and better

performance of the corporate sector.

MUTUAL FUNDS

Mutual funds were stable and innovation supported

industry recovery

The mutual funds industry regained momentum

subsequent to a collapse in 2005. The rebound was

attributable to a variety of product innovations and

improvements to regulations in the market, as well as

more proficient investment managers in terms of

Graph 4.42Sectoral Index and JCI

Source : Bloomberg

-

200

400

600

800

1,000

1,200

1,400

1,600

2005Jan Feb Mar Apr May Jun Jun Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

2006

InfrastructureJCI Mining

Agriculture Various IndustriesConsumption

56


Graph 4.44Type of Mutual Funds

0

2

4

6

8

10

12

14

16

2005Des Jan Feb Mar Apr May Jun

2006

Trillions of Rp

Fixed Inc Shares Mixed Money Market Protected

diversifying mutual funds products. Through innovation

and diversification, investors have the freedom to invest

in mutual funds that correspond to their desired level of

risk. In addition, the outlook for mutual funds remains

positive and is expected improve further due to falling

interest rates.

Performance of Mutual Funds

The mutual funds market began to recover due to

higher asset prices, particularly bond prices. The recovery

was principally supported by the improved capacity of

investment managers to develop and innovate products.

The performance of mutual funds expanded the investor

base to meet specific investor requirements (tailor-made).

In addition, improved regulations in the mutual funds

market restored investor confidence and bolstered market

recovery.

The recovery was evidenced by the increasing net

asset value (NAV) and fewer redemptions. The NAV of

mutual funds rose slightly from Rp28 trillion (December

2005) to Rp33 trillion (June 2006), whereas redemptions

fell from Rp5 trillion (December 2005) to Rp4 trillion (June

2006). Subscriptions jumped to Rp5 trillion (June 2006)

from Rp3 trillion (December 2005). When subscriptions

exceed redemptions, it indicates restored investor

confidence in mutual funds.

Initiatives to develop mutual funds were

implemented through the innovation of structured mutual

funds. Product development was targeted at expanding

the investor base and attracting risk averse investors. There

are two types of structured mutual funds: (1) protected

mutual funds launched in October 2005; and (2) indexed

mutual funds launched in early 2006. Initially, structured

mutual funds were unsuccessful in attracting investors,

however, since 2006 investment increased significantly

pushing up NAV by 111% to a 21% market share. In

addition, indexed mutual funds were launched at the

beginning of 2006 comprising of asset prices which form

the benchmark index. The perceived lower risk of mutual

funds was key to their high demand, however, since mutual

funds are new to domestic investors their net asset value

remained low at Rp 13 billion.

The performance of conventional mutual funds

remained positive along with recovery in the bonds market.

High volatility in the equity market exacerbated the drop

in equity and mixed mutual funds. During the previous

year, investors limited their portfolio of this type of funds

despite high potential returns. Moreover, persistently high

interest rates supported the performance of money market

mutual funds. Amid uncertainty surrounding interest rates,

investors preferred to invest in money market mutual funds,

which provide flexibility without penalties.

Graph 4.43Mutual Fund and Net Asset Values

Trillions of Rp

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

2005 2006Sep Oct Nov Dec Jan Feb Mar Apr May Jun

Redemption Subscription NAV

57


The rebound in NAV is projected to continue and

mutual funds are expected to stabilize. This is attributable

to the following:

Continuous product innovation by investment

managers to develop structured mutual funds,

consisting of protected and indexed type. In addition,

innovation will also include the money market and

mixed mutual funds.

Regulations requiring specific qualifications of

investment managers. The regulations will positively

impact the quality of investment managers and also

enhance accountability as well as supervisor quality

through regulation refinement for marketing and

security agents.

The prospects of an interest rate drop indicated by a

decline in the benchmark BI Rate beginning in May

2006. This may trigger upbeat behavior in terms of

shifting from time deposits to mutual funds.

Such conducive conditions are expected to gradually

rebuild investor confidence leading to a more robust

mutual funds market. In addition, product development

and innovation encourage investors to diversify risks based

on their risk appetite.

BONDS MARKET

The government bonds market remained buoyant

attributable to active foreign investor transactions.

However, the corporate bonds market appeared to

be stagnant.

Despite slight pressures, the bonds market - particularly

government bonds - remained attractive, dominated by

foreign investors. Attractive gains in the government bonds

market stimulated foreign investment and raised their

portfolio in Indonesian bonds. The outlook for the bonds

market is positive in line with the improving macroeconomic

indicators, including fiscal conditions, the sovereign rating

and declining interest rates. Indonesian Retail Government

Bonds (ORI) are expected to boost the intermediary function

of the bonds market. In concurrence with expected

economic recovery and better corporate performance,

corporate bonds will increase in the near-term.

70

75

80

85

90

95

100

105

110

115

120

FR0002 FR0005 FR0019 FR0020

FR0025 FR0027 FR0029FR0023

29Dec

12Jan

26Jan

9Feb

23Feb

9Mar

23Mar

6Apr

20Apr

4May

18May

1Jun

15Jun

29Jun

2005 2006Source: Surabaya Stock Exchange

Graph 4.45Bond Prices - Selected Series

Government Bonds

The government bonds market rebounded, reflected

by the rise in transactions and prices, which had previously

fallen due to interest rates hikes. Nevertheless, foreign

investors and banks dominated transactions with positive

expectations for future prices. Uncertainty regarding the

increasing global interest rate cycle encouraged investors

to adjust their portfolio. This created downward pressure

on bond prices in May 2006 leading to higher volatility by

THAI

%

-2

-1

0

1

2

3

4

5

6

7

1yr 2yr 3yr 4yr 5yr 6yr 7yr 8yr 9yr 10yr 15yr

INDON PHIL INDIA

Source: Bloomberg, process

Graph 4.46Yield Spread of Selected Asian Countries

58


Graph 4.49Corporate Bond

Source: Surabaya Stock Exchange

BBB-2.6% B-

0.1% D/SD10.7%

Not Rated0.6%

AAA3.2%

AA+11.5%

AA-6.8%

AA5.5%

A+14.5%

A9.8%

A-20.6%

BBB+7.2%

BBB7.0%

Individual-Domestic1.25%

Cooperative0.03%

Institution-Domestic- Others0.50%

Pension Fund28.00%Bank

21.65%

Taspen2.86%

Mutual Fund19.09%

Insurance9.78%

Incorporation7.65%

Jamsostek5.60%

Broker1.25%Foundation

2.35%

Source: Surabaya stock exchange

Graph 4.50Corporate Bond Holders

the end of semester I 2006. Market conditions, coupled

with uncertainty surrounding the future prospects of

interest rates, were more attractive for short-term investors.

Exacerbated by non-transparent benchmark pricing,

investors compounded price volatility.

Rising global interest and Fed Fund rates following

FOMC on June 29, 2006 impinged upon the transmission

effects of domestic interest rate cuts. Against this backdrop,

investment yield in rupiah in various maturity bands

temporarily declined by 120-140 bps, however, this quickly

rebounded by 15-20 bps in the second quarter of 2006.

As a result, yield in rupiah was higher compared to

neighboring countries like Thailand, the Philippines and

India. Attractive yield drove investors towards government

bonds, increasing the portfolio share held by foreign

investors from 8% (December 2005) to 12% (June 2006),

which supported market recovery and contributed to

rupiah appreciation.

Corporate Bonds

High yield in the corporate bands market also drove

investors towards corporate bonds. In addition to

domestic investors, foreign investors also showed interests

in selected bonds. Foreign investors accounted for 71.8%

of total corporate bonds, predominantly investment grade

bonds (AAA to A-). However, the vast majority of the

high-rated corporate bond investors were pension funds

whose total share of portfolio accounted for 28% and

are likely to hold bonds as their medium-term investment

outlet. Consequently, the corporate bonds market was

less liquid and active compared to the government bonds

market.

Source: Surabaya Stock Exchange

0

2

4

6

8

10

12

14

16

18%

2004 2005 2006

1 yr 10 yr3 yr

Graph 4.47Government Securities Yield Curve

Graph 4.48Ownership of Government Bond

Billions of Rp

2005 2006

Dec Jan Feb Mar Apr May Jun

Citibank Deutsche HSBC Stanchart Total

0

10000

20000

30000

40000

50000

60000

59


Banks and multi-finance companies remained the

largest group of corporate bond issuers, particularly those

allocating consumption financing. Compared to the

previous year, the issuance of corporate bonds in semester

I 2006 was sluggish due to high interest rates and

uncertainty. Notwithstanding, pricing was non-transparent

constricting liquidity and activity. The stagnant corporate

bonds market was indicated by the falling transaction

value, which during the course of semester I was Rp7

trillion. The amount of bonds issued totaled Rp3.67 trillion

stemming from high demand for consumption financing

and the constraints in bank funding. Infrastructure

companies ranked second in terms of issuing bonds,

totaling Rp1.20 trillion during semester I 2006. As a result,

total corporate bonds issued during the first semester

totaled Rp4.87 trillion. These were issued by Summit Oto

Finance I, Federal International Finance VI, Perum

Pegadaian XI, Adira Dinamika MF II, WOM Finance III, PLN

VIII, PLN Sharia Ijaroh I and Jasa Marga XII

The near-term stability of the government bonds

market appears to be positive due to falling domestic

Graph 4.51Issuer Profile

Source: Surabaya stock exchange

Trade, Service &Investment

6,94%

Finance (Mult, Fin)18,69%

Agriculture5,71%

Basic Industryand Chemicals

10,20%

ConsumerGoods

Industry3,67%

Mining1,22%

MiscellaneousIndustry2,45%

Infrastruc,Utilities& Transportation

22,26%

Finance48,98%

interest rates. In addition, a higher sovereign rating, better

fiscal performance and the issuance of retail government

bonds (ORI) will contribute to higher transactions in the

bonds market. ORI, which will be issued amounting to

Rp2 trillion, has been oversubscribed. In addition, foreign

investors remain upbeat regarding the prospects of

government bonds and, therefore, they will remain

dominant. Foreign investor expectations of attractive

capital gains will encourage investors to play a significant

role in the domestic market. The hitherto continuous Fed

Fund Rate rising cycle appears to have been suspended,

which contributes to the positive outlook for government

bonds.

The corporate bonds market is expected to rebound

in line with declining interest rates, brighter prospects and

positive business expectations. New issuers in the capital

market will be dominated by banking institutions to meet

their capital adequacy requirement. Furthermore, the

relatively constrained intermediary function of banks will

stimulate intermediation in the capital market though the

issuance of bonds. This will be supported by a buoyant

economy and improved corporate performance.

Consequently, demand for investment and expansion is

forecast to increase.

The bonds market is predicted to become more

robust in accordance with better macroeconomic

fundamentals and falling interest rates. Additionally,

foreign investors will become more active. Furthermore,

relatively restrained bank financing will foster active

financing from the bonds market via a longer-term

financing structure.

60



57

Chapter 5 Financial Infrastructure

Chapter 5Financial Infrastructure

58



59


Financial InfrastructureChapter 5

PAYMENT SYSTEM

Supported by the effective implementation of the

National Clearing System, the payment system has become

more robust. Risks, on the other hand, are well-mitigated

by Business Continuity Plan. Increasing volume and

transactions indicated the resilience of payment system as

settlement risk was alleviated. This contributed stability in

the financial system, among others through the

implementation of Failure to Settlement Arrangement

mechanism. This mechanism requires a mandatory pre-

fund by banks in clearing system. Furthermore, Bank

Indonesia continuously enhances regulation related to card

based payment to lessen credit risk and potential loss of

issuers.

Development of Payment System RTGS and

Clearing

Settlements through BI RTGS continued to grow with

average daily transactions of Rp105 trillion (USD 11.5

billion), an annual increase of 22% (y-o-y). Bank customers

accounted for 76% of total transactions, whereas per

transaction purpose, the largest was for monetary

contraction (Bank Indonesia IDR intervention) which

accounted for 19% of total transactions.

As per type of sender, Bank Indonesia, whose

nominal value of transactions accounted for 39.7% of the

total at BI-RTGS, was the largest. Bank Indonesia

transactions included monetary operations, payments

related to government bonds, taxation booking, and

disbursement of the government»s budget. As per

frequency, commercial banks were the most active players,

as they accounted for 21.7% of total transaction frequency.

These banks used bulk transactions for domestic currency

transfers, the inter-bank money market and foreign

exchange transfers.

The trend in transaction volume growth reflected

stronger pubic confidence in security and the versatility of

More robust financial infrastructure amidst increasing settlementsMore robust financial infrastructure amidst increasing settlementsMore robust financial infrastructure amidst increasing settlementsMore robust financial infrastructure amidst increasing settlementsMore robust financial infrastructure amidst increasing settlements

Graph 5.1RTGS Settlements

0

100

200

300

400

500

600

700

800Thousand

Volume Nominal

Trillions of Rp

500

1,000

3,000

1,500

2,000

2,500

02000 2001 2002 2003 2004 2005 2006

60


the BI-RTGS system. Notwithstanding, it is fairly hasty to

conclude that the trend indicated rapid economic growth,

as a substantial fraction of settlements were financial sector

transactions. On the other hand, settlements directly

related to the real economy remained lower than the

financial sector. Thus, the growing trend of large value

transactions did not reflect growth of the real economy.

Retail payment system showed a downward trend.

Unlike the large value payment system, the retail payments

system through clearing dropped by 18.22% (y-o-y). Shifts

to BI-RTGS have become the major factor behind the

downward trend in the retail payment system. As per

clearing region, Jakarta clearing area accounted for 48%

of total settlements with a nominal value of half. This

reflected that economic activities remained centralized in

Jakarta and the surrounding areas.

Bank Indonesia is strongly committed to promote a

robust payment system. To mitigate the risks in the

payment system, the failure to settle arrangement to

eliminate systemic failure has been effectively

implemented. This scheme requires clearing participants

to use a pre-fund and has helped mitigate risks in the

payment system.

CARD-BASED PAYMENTS

Card-based payments have continuously followed

an upward trend. The use of ATM (automated teller

machine), credit and debit cards were 85,4%, 10,4%

and 4,1% respectively. However, by nominal value, ATM

card were 93,8%, whereas credit cards and debit cards

were 4,5% and 1,7% respectively. These figures indicate

a shift in public preference from cash-based payments

towards card-based payments (cashless society). Spike

in the ATM and debit card transactions at the end of

2005, revealed higher cost of living due to soaring oil

price hikes.

In addition, the use of credit cards remained far

below the other means of payment, as the public take

the high interest rates of credit cards into major

consideration. To this extent, Bank Indonesia has been

vigilant over credit card performance. This is due to the

growing number of non-performing loans of credit cards

that have slightly exceeded 10%. To limit the probability

of credit card default, Bank Indonesia has announced a

minimum payment of 10%, by December 2005.

Graph 5.3Clearing Settlements

Million

Volume (lhs) Nominal value (rhs)

Trillions of Rp160

140

120

100

80

60

40

20

--

1

2

3

4

5

6

7

8

9

10

2002 2003 2004 2005 2006

Graph 5.2RTGS Players

Nominal Share

Volume Share

0

5

10

15

20

25

30

35

40

45

50%

ForeignBanks

Joint VentureBanks

State-OwnedBanks

BankIndonesia

RegionalBanks

DomesticPrivate Banks

Non Banks

15.96

20.96

0.03

3.63

41.30

13.19

4.94

46.90

9.6410.66

0.21

23.65

3.625.33

Graph 5.4Value of ATM, Credit and Debit Cards Transactions

-

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

200,000Billions of Rp

Credit Debit ATM

2000 2001 2002 2003 2004 2005 2006

61


PAYMENT SYSTEM DEVELOPMENT

Since the successful implementation of the Jakarta

National Clearing System in July 2005, Bank Indonesia has

gradually commenced operating the National Clearing

System (SKNBI) in the other provinces of Indonesia. Bank

Indonesia has set the target for the BI-National Clearing

System to be implemented in at least 52 clearing regions

in Indonesia by the end of 2006. Indonesia will have a

more efficient domestic clearing system once the BI-

National Clearing System has been fully implemented and

integrated. Consequently, the clearing process will be

faster, safer, and more effective, therefore, supporting

economy activities.

To mitigate risks in the payment system, Bank

Indonesia has prepared a disaster recovery plan for the

payment system that is critically important, predominantly

in the BI-National Clearing System and BI-RTGS. Trials and

tests on the backup of both payment systems are regularly

exercised. Besides, Bank Indonesia examines the backup

infrastructure at the Disaster Recovery Center on a monthly

basis. The preparedness of the backup system supports

the availability of BI-RTGS and the National Clearing System

against all potential disruptions, including natural disasters

and operational failures.

In order to enhance legislation as well as security

and efficiency in payment system operations, Bank

Indonesia has enhanced the legal apparatus of the payment

system complying with international standards and best

practices. Additionally, in efforts to enhance legislation in

inward and outward remittance, Bank Indonesia is currently

preparing regulations pertaining to money remittances in

Indonesia. The regulation will stipulate terms and

conditions as well as define the responsibilities of the

money remittance provider. The regulation is expected to

enhance transparency, security and customer protection.

Furthermore, corresponding to advances in

technology for electronic transactions, Bank Indonesia in

cooperation with the Ministry of Communications and

Information are currently preparing a draft of Information

and Electronic Transaction laws. These laws will stipulate

the use of electronic evidence including money remittances.

With this regulation, it is expected that certainty in law

enforcement for electronic transaction will be assured and,

therefore, help restore public confidence in using electronic

means of payment.

Graph 5.5Volume of ATM, Credit and Debit Cards Transactions

2000 2001 2002 2003 2004 2005 2006

Millions of Transaction

0

10

20

30

40

50

60

70

80Credit Debit ATM

Keterangan : Penyesuaian pengklasifikasian pada triwulan IV 2005

62


10% Minimum Payment for Credit CardsBox 5.1

Bank Indonesia initially regulated the provision

of Payment Means Using Cards via Bank Indonesia

Regulation number 6/30/PBI/2004 dated 28th

December 2004 concerning the Service Provision of

Payment Means Using Cards, featuring for major

articles: 1) Payment System Regulation; 2) Customer

Protection; 3) Supervision; and 4) Prudential

Regulation. This regulation was revoked and

subsequently replaced by Bank Indonesia Regulation

number 7/52/PBI/2005 dated 28th December 2005,

for which the technical guidelines are elucidated in

three circular letters. This regulation itemizes

prudential regulations in more detail, including the

minimum monthly payment of 10% for credit cards.

Effective commencing 28th December 2005 all credit

card issuers must comply with the new regulation.

Some issuers, notwithstanding, have gradually

demanded a 10% minimum payment since 28th

December 2004.

Applying for credit cards is generally less stringent

and hassle free and, therefore, customers can easily

obtain more than one credit card. Nevertheless, credit

card holders seem to be unaware of the high interest

rates charged, effectively 28% - 42.0% p.a. for retail

transactions and 33% - 72% for a cash advance. This

has affected the repayment capacity of holders heavily

indebted by credit card financing. Credit card debts

materialize when the holder does not fully repay retail

transactions or when she/he repays only the minimum

payment. As the vast majority of credit card issuers

only demanded 5%, the holders were finally

overburdened with the compounded interest rates. In

previous cases, customers ended up with overly-

indebted principal and interest arrears which, in turn,

lead to upward credit risk pressures on banks.

Considering these rationales, Bank Indonesia

promulgated a regulation demanding a 10% minimum

payment of the outstanding monthly balance. The

ultimate objective of this regulation is to protect both

the customer and the bank. From the customer»s

perspective, with a 10% minimum payment it is

expected that the customers manage their finance

better and limit their probability of default. Customers

will be able to make fewer, higher value installments

of their monthly outstanding balance and, therefore,

reduce their debt. From the bank»s perspective, this

regulation helps banks mitigate credit risk emanating

from unsecured lending. Additionally, banks are

expected to exercise more prudent selection of the

applicants.

1a

Article I

Ar t icle

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3a

Article I

Article I

Hedge Fund Activities in Developing Countries andEfforts to Maintain Financial Stability

Dwityapoetra S. Besar

BACKGROUND

A high degree of volatility marked the conditions of

financial markets in developing countries. Financial

instability was triggered by a period of high capital inflows

followed by subsequent outflows and a higher cost of

borrowing. The external balance sheet sparked a monetary

crisis in Asia in 1997 and distortions in the Brazilian

economy in 2002. The crises were not only very costly for

emerging countries but also influenced industrial countries

financially linked to the crisis-hit countries and the global

equity market. Understanding the main trigger of volatility

is an important element of judging global and domestic

financial system risk.

This paper discusses the development of investment in hedge funds, especially in emerging market countries

and their impact on financial stability. In general, investment in hedge funds has positive impacts on a country

primarily in creating an efficient equity market. Nevertheless, in practice several criteria must be met in order to

have an efficient market, namely: (i) to monitor potential hedge fund crises; (ii) to monitor the relationship with

banks and financial markets; (iii) to enforce good corporate governance; and (iv) to protect the consumer.

Therefore, in a global context, global consensuses and agreements are required to build global and regional

cooperation. Such cooperation will assist in the monitoring of global hedge fund activity as well as create and

maintain global financial stability.

During the Asian crisis, hedge fund activity was

considered one of the agents which raised volatility and

pressure in the financial system in Southeast Asia. The most

famous being the Soros Quantum Fund. The Prime Minister

of Malaysia called its action amoral, unnecessary and

unproductive. On the other hand, there are suggestions

that hedge funds are critical to maintain liquidity supply in

the forex market. Therefore, hedge fund activities as free

as international equity flows plus fundamental weaknesses

in developing countries indicate that developing countries

must prepare to protect themselves from potential global

crises.

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Article I

THE NUMBER OF HEDGE FUNDS AND FUNDS

UNDER MANAGEMENT

Hedge Funds were initially developed by Alfred

Winslow Jones in 1947 as a group of funds for short and

long position investment, using arbitrage, undervalued

securities, bonds trade or options which are invested in

every combination to achieve yields with low risk. The

improvements gained in assets managed by hedge funds

has sharply risen in the last ten years, from US$257 billion

to more than US$ 1 trillion covering more than 8,000

hedge funds.

The scale and complexity of hedge fund activities are

a concern for regulators because their free flows can distort

financial sectors. Currently, hedge fund activities are classified

into three groups, namely relative value, event driven and

opportunistic. Relative value is an investment with

convertible arbitrage, fixed income arbitrage and equity

market neutral strategy. Event driven is an investment with

risk arbitrage, distressed and CTA managed futures.

These two groups of hedge funds represent

investments which use models to detect a chance for

arbitrage. The activities in these groups are usually followed

by hedging transactions leaving the investment with low

risk. Meanwhile, opportunistic or macro funds generally

operate in global macro, short seller, long specialist,

emerging markets and long/short equity areas. This group

tends to make speculative transactions based on

macroeconomic and financial market analyses.

Assets managed by the hedge fund industry totaled

about US$1.130 billion by the end of 2005. This is a 13%

increase on the previous year and almost double the

amount of assets three years ago. Generally, hedge funds

use leverage at a level 5 to 9 times that of equity. The

number of hedge funds increased by 6% in 2005; reaching

8,500 companies. Research conducted by Tower Group

estimated that hedge fund assets will grow by 15% p.a.

from 2006 to 2008. Based on Alpha Magazine, hedge

funds placed in the top five position, based on assets, are

Goldman Sachs Group, Bridgewater Associates, D.E. Shaw

Group, Farallon and ESL Investments.

Funds under Management

Based on hedge fund research regarding strategy

over the last 15 years, there has been a significant change

in the composition strategy of fund management. In the

1990s, macro funds were considered as the most active

hedge funds with a share of 70% from total fund

management, followed by Relative Value Arbitrage with a

share of 10%. This differs widely from conditions in 2005,

where Equity Hedge Funds were dominant with a 30%

share, followed by Event Driven Funds with 14%. In

addition, Macro Funds only commanded an 11% share.

Graph A1.2Global Hedge Funds

0

50

100

150

200

250

300

350

400

(25.00)

(20.00)

(15.00)

(10.00)

(5.00)

0.00

5.00

10.00

15.00

Hedge Fund Index

Stock Market Indices

Source: Bloomberg

Jan Apr Jul Oct Jan Apr Jul Oct1997 1998 1999 2000 2002 2003 2004 2005

Graph A4.1Stock Market Indices and Hedge Funds

at Emerging Countries

0

200

400

600

800

1000

1200

1400

0

2000

4000

6000

8000

10000

Source: Hennessee Group LLC;IFSL 2005, Van Hedge 2006

1995 1997 1999 2001 2003 2005

Asset

Total

Asset USD billion

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Article I

This indicates that hedge fund activities have not only

become relatively stable but also over a longer horizon.

Nevertheless, macro fund strategy still requires attention

globally and from developing countries too.

Hedge Fund Investment in Developing Countries

The hedge funds industry is predicted to decline in

the future. An indicator of this is stock market stability

over recent years, which undermines hedge funds

speculation. Besides, high competition and tight regulation

by the supervisory authorities in US and UK have pushed

hedge fund activities towards developing countries.

The relative value strategy adopted gives the

prospect of lower returns. Some hedge funds in recent

times have reported a low rate of return, oftentimes close

to the initial equity. Meanwhile, 25 hedge funds in Asia

have successfully raised their assets to a value of US$22.6

billion. This highlights the switch in the hedge funds

industry to developing countries, especially in Asia.

Although the size of the Asian market is relatively small

compared to USA and Europe, opportunities remain wide

open, such as in the stock and commodity markets. Japan

and Australia lead the Asian hedge funds market,

including Sparx Asset Management located in Tokyo,

which manages funds totaling US$5.2 billion.

Over the next three years, global hedge funds will

return to Europe (26%) and Asia (10%). Hedge funds

markets will grow more rapidly in developing countries

due to weaker regulations and poorer legal framework.

Hedge funds located in Australia will remain the prime

investor in Asia Pacific. In 2005, 25% of total assets,

totaling US$115 billion, were managed in Australia. Other

countries which invest in hedge funds in Asia are Japan

(20%), Hong Kong (14%), USA (23%) and UK (16%).

Developing countries, especially in Asia have to

prepare themselves to avoid risks and minimize the

chance of hedge fund crises. Hedge funds activities

require regulation and supervision in order to create an

efficient, liquid and sound financial market towards the

ultimate goal of financial stability.

Graph A1.3Global Hedge Fund Investment - Per Region

Others Asia Europe US

86

62

9

26

1023

2

0

20

40

60

80

100

2002 2005

Source: IFSL, Hedge Funds, March 2006

%

Strategy

Equity hedge 5.3 (3) 30.0 (1)

Event driven 3.8 (4) 13.8 (2)

Relative value arbitrage 10.1 (2) 11.8 (3)

Macro 71.1 (1) 10.7 (4)

Fixed income 3.2 (5) 7.9 (5)

Sector 0.2 (12) 4.8 (6)

Distressed securities 2.4 (6) 4.7 (7)

Equity non-hedge 0.6 (8) 4.5 (8)

Emerging markets 0.4 (11) 4.0 (9)

Convertible arbitrage 0.5 (10) 3.3 (10)

Equity market neutral 1.7 (7) 2.2 (11)

Merger arbitrage 0.6 (9) 1.4 (12)

Market timing 0.4 (13)

Short selling 0.1 (13) 0.3 (14)

Regulation D 0.2 (15)

Fund of Funds 4.9 35.7

Table A1.1Hedge Fund Strategy

1990 2005

% of Total Managed Funds

THE IMPACT OF HEDGE FUNDS ON FINANCIAL

STABILITY

Hedge funds in the 1990s grew rapidly earning high

yields. This was the result of good hedging performance,

access to modern techniques and markets as well as high

flexibility in hedge funds activities. This condition is to be

considered as ideal and made hedge funds a firm

6a

Article I

institution. Nevertheless, such characteristics and the

strategies adopted for hedge funds transactions created

instability. One such strategy that triggered high volatility

was global macro. Global macro uses a top down global

approach investing in many instruments to generate profit

from inaccuracies in market price movements stemming

from global economic shifts, geopolitical conditions, global

imbalances and other significant changes.

In addition, the high level of leverage behind hedge

funds activities exacerbated the risks associated with hedge

funds activities. High leverage is raised to boost the position

and potential return assuming that the potential return is

higher than the level of leverage. Hence, the hedge funds

industry looks for the highest return neglecting to pay

attention to the soundness of economy fundamentals and

financial stability. Nevertheless, this condition will not

persist because, in the long run, returns decline due to

capacity constraints, dynamic market movements, systemic

risk and better regulation. This situation motivates

developing countries to minimize the negative impacts.

Foreign Exchange and the Jakarta Composite

Index (JCI) as Financial Instability Indicators

Assessments are performed to observe distortions

in financial stability by monitoring the foreign exchange

and stock markets. One of the main indicators in countries

that are suffering a crisis is when the level of foreign

exchange surpasses its fundamental value (Goldstein,

Kaminsky and Reinhart, 2000).This condition encourages

hedge funds in the foreign exchange market which puts

pressure on a country»s currency.

Meanwhile, the stock market can describe the

intensity of hedge funds investments, which require a high

level of return and portfolio diversification. Hence, positive

movements in JCI should be in line with hedge funds

indices of other developing countries that invest in the

Indonesian stock market. A country should be able to

predict and prepare for risk and potential crises that result

from hedge funds activities. Monitoring disturbances and

hedge funds exposure is crucial to limit the possibility of

financial crisis risk and alleviate the impact of a crisis. As

an initial idea and reference, this can be performed by

analyzing the relationship between the change in the

hedge funds index in developing countries and the change

of foreign exchange and JCI.

Correlation of Hedge Funds Index Growth in

Developing Countries, JCI Performance and

Rupiah Foreign Exchange

Currently the global stock exchange has collected

investment funds totaling more than US$1 trillion. Hedge

funds tend to seek portfolios that have a lower correlation

with stock index (which is well diversified) but this entails

high risk, especially in variance between hedge funds and

the type of portfolio and its investor. Hence, hedge fund

investors have to chance high risks by choosing portfolios

suffering of loss (Malkiel and Saha, 2005).

The correlation between hedge funds indices in

developing countries with foreign exchange and JCI shows

a similar relationship pattern, except for foreign exchange

and JCI during a crisis period. This difference is primarily

attributable to extensive stock selling and dollar buying by

investors. Movements in the hedge funds indices of

developing countries is in line with the JCI and rupiah

exchange rate to the US$. This is because the JCI forms

part of the hedge funds indices of developing countries

and, therefore, a change in investment pattern does not

negatively impact foreign exchange. In other words, there

is a significant positive correlation between the hedge

funds indices of developing countries, the JCI and rupiah

foreign exchange, which indicates the domination of hedge

funds in emerging markets. The high level of hedge funds

transactions in Indonesian stock market is also reflected

by material correlation, however, not in the foreign

7a

Article I

exchange market. This strategy of hedge funds transactions

is defined by the level of yield and tends to be short term.

Furthermore, it is highly susceptible to a sudden capital

reversal which can spur financial instability. This condition

should be anticipated. Preparations must be made to

prevent financial instability, therefore, dissipating the

pressures on financial markets in Indonesia and other

emerging market countries.

FACTORS THAT IMPROVE FINANCIAL STABILITY

In terms of the financial market, strong correlation

is evident between investment through hedge funds and

a country»s financial market, including in developing

countries. In order to maintain financial stability, several

important aspects require attention, namely (i) hedge funds

crisis; (ii) its impact on banks and the financial market; (iii)

good governance; and (iv) consumer protection.

Hedge Funds Crisis

A decline in hedge funds is a serious concern,

especially for developing countries with weak

fundamentals and susceptible to global capital

movements. Generally, regulations in developing

countries are relatively weak, leaving the country open

to huge contagion risk. Different from mutual funds,

hedge funds can include speculation in many instruments,

from real estate to future energy. In order to ensure a

high return, hedge funds management use a strategy

that entails high risk, for example by using loans to add

investment strength and regularly selling short (if the asset

price will drop). A strategy which has high risk can earn

a high return but can also incur losses. One such

experience was found in Connecticut, by Long Term

Capital Management (LTCM), which suffered high losses

in 1998. Despite the guidance of a Noble Prize winner in

economics and expertise from Wall Street, LTCM carried

out massive speculation on bonds until the price

plummeted. In order to avoid further chaotic financial

conditions, a coalition of banks on Wall Street sponsored

by The Federal Reserve bailed out LTCM.

Such a disastrous drop is prices provided an invaluable

lesson for other market agents. Nevertheless, the extensive

number of hedge funds seeking high gains, not backed

up with good quality, caused market instability. This is often

followed by financial scandal and insider trading, which

happened to KL Financial (US$200 million loss), Bayou

Management LLC (US$300 million loss) and Man Group.

A decline in hedge funds is also caused problems

affecting its counterparty. One major event was when the

settlement of futures transactions was postponed due to

problems in Refco, which is under the supervision of the

Securities Exchange Commission (SEC) and the Financial

Services Authority (FSA). As a result, Refco is forbidden to

settle transactions.

Capital flows from large investors affect hedge fund

performance and conditions. Based on Chicago»s Hedge

Fund Research Report in December 2005, up to September

2005, there were 484 hedge fund defaults (6%). Although

there are no hedge fund defaults in the most recent report,

Sample (1997-2006)Global Hedge Fund Index 70.7 -9.4 38.2

EM Hedge Fund Index -8.3 32.9

USD/Rp -4.0

Crises Periode (1997-98)Global Hedge Fund Index 71.7 -7.3 61.6


USD/Rp 20.4

Post Crises (2000-06)Global Hedge Fund Index 73.0 -15.9 28.0


USD/Rp -41.2

Table A1.2Correlation of Hedge Fund Index, Exchange Rate and

Jakarta Composite Index

Hedge FundIndex

ExchangeRate

Rp/USDJCI

Sumber: Bloomberg, MSCI

%%%%%

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Article I

more are predicted. This period has therefore become

known as a hedge fund recession.

The fall in hedge funds and its impact on other

market agents requires more attention in terms of financial

system stability in developing countries. This is because

global hedge fund exposure is much greater than for forex

reserves and the financial markets.

A significant drop in hedge funds can spark market

panic. If hedge funds are sold in a declining market, the

market can spiral into crisis. This is even more important

in markets which suffer from herding behavior, which

generally occurs in developing countries. Besides, stocks

crises influence other parts of the financial markets,

especially the foreign exchange market.

The Influence on Banks and Financial Markets

Hedge fund activity strongly influences other activities

in the financial markets. The requirement for increasing

returns for hedge funds supports a rise in debt, which is

borne by banks and other creditors. Some large size banks,

such as JP Morgan Chase, Deutsch Bank, UBS and Credit

Suisse are the primary lenders for hedge funds to the tune

of US$500 billion. This is a problem if hedge funds are

invested speculatively, leaving the creditor»s bank with the

risks.

A hedge fund crisis affected Refco, a futures trader,

which was almost bankrupted due to high bank debt.

Supervisory and regulator assistance was required to

protect the financial system from systemic risk.

Furthermore, hedge funds are also influenced by

ownership. In order to gain high returns, an exact strategy

is applied to hedge funds, including buying long-term

stocks. For example, Hedge Fund Toscafund and

Lansdowne Partners purchased stocks of one of the largest

banks in Germany, Commerzbank. In the transaction, they

did not acknowledge themselves as the investor-owner.

This phenomenon will expand through buying bank stocks,

such as BNP-Paribas, Royal Bank of Scotland, or Spanish

owned banks. Such stock purchases are mainly based on

the interest of foreign investors in bank acquisition, which

improves the gains on hedge funds from the stock price

spread.

Buying bank stocks through hedge funds is a

challenge for bank supervisors and regulators. From the

supervisory side, it is difficult to supervise an indistinct

hedge fund or a hedge fund unwilling to increase equity.

In addition, if the hedge fund owns more than 51%, its

financial report can not be supervised through

consolidation.

Emerging market countries should decide upon

specific requirements for hedge funds seeking to buy bank

stocks.

Governance must be Improved

Unregulated hedge fund activities give rise to illegal

activities. Even in countries such as the United States of

America and United Kingdom, which are well regulated

and practice good governance for hedge funds, illegal

activities occur. Such instances evidence that hedge fund

regulations and supervision are crucial. Generally, cases

involve insider trading and market manipulation, such as

Hedge Fund Pequot Capital Management which involved

Executor Morgan Stanley. As a result, the supervisory

authority agent, such as Financial Service Authority (FSA)

in United Kingdom, refines regulations to avoid hedge

funds from speculative or deceitful transactions. This action

is important to reduce insider trading and market

manipulation.

The case of the Canadian Imperial Bank of Commerce

(CIBC), which extended loans to hedge funds using late

trading and market timing, shows how law enforcement

a good governance are important. Another case is

highlighted by Hedge Fund Wood River Partners LP and

Wood River Partners Offshore Ltd managed by John

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Article I

Whittier, which caused millions of dollars of financial loss

for the investor. In this case it was attributable to a poor

audit process and bad investment fund management.

Good governance, sound implementation and firm

supervision are required to ensure healthy hedge fund

activities in developing countries. These three points are

important to create an efficient market, protect investors

and stabilize the financial system, not only in developing

countries but in the global markets.

Customer Protection

In recent years, capital flows from large investors

(institutions) have declined by 44% compared to the first

quarter of 2005. Therefore, hedge fund managers have

begun to market their products through banks and pension

funds. The minimum amount for investment has

consequently dropped to just US$25,000. This condition

must be supervised because it can trigger systemic risk

and losses for the customer, especially retail customers.

Based on research by the Fund Research Institute, in

1990 there were 600 hedge funds with total managed

assets of US$38 billion. In 2006, it increased to 8,500

hedge funds with more than US$1 trillion. However, the

amount invested has halved from US$24.6 billion to

US$11.6 billion.

In the United States of America during 2005, based

on research by Securities and Exchange Commission (SEC),

there were 51 cases of investor loss totaling more than

US$1 billion. In developing countries, this represents a

challenge because hedge fund activities are neither well

regulated nor supervised. In addition, regulators have to

expand their comprehension of hedge fund transactions.

Ponzi Scheme is an example of deception. Bret

Grebow from HMC International LLC caused the investor

to suffer a US$5.8-million loss. Manipulation of documents

and investment reports by Kirk Wright caused 500 investors

to loose a total of US$185 million.

Another deception case involves Samuel Israel III

from Bayou Hedge Fund, which triggered losses of

USD1.5 million. In this case, SEC as the supervisor and

regulator has initiated court action against the

perpetrators.

Besides, limited comprehension in terms of

projection calculations can affect small/retail investors.

In such cases, profit projections are calculated by the

Sharpe ratio formula and method. This method differs

from the usual method because the calculations are based

on average values and normal distributions in rate of

return model, which creates more favorable results than

can be expected in real terms.

Generally, investment in hedge funds follows the

principle that the higher the risk the higher the return.

Therefore, investors tend to be more speculative. However,

they have to realize the risks and the impacts of their

investment. Furthermore, regulators have to protect small

investors.

CONCLUSION

Hedge fund performance in the 1990»s was

considered well developed with high potential returns

supported by hedging, accessibility to modern markets and

less regulation. Hedge funds were considered a firm

institution. However, these characteristics and certain

strategies taken caused instability in the respective market/

country.

One strategy that triggers high volatility is global

macro. Hedge fund managers use the strategy by applying

a top-down global approach and investing in various

instruments in order to profit from market price

inaccuracies. There is a strong correlation between hedge

fund investment in the money market and capital market,

including developing countries.

Therefore, in order to maintain financial stability, we

must pay attention to several important aspects, such as

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Article I

(i) avoiding hedge fund crises; (ii) minimizing negative

impacts on banks and financial markets; (iii) expanding

the implementation of good governance; and (iv)

protecting the customers, especially retail investor. In

addition, global commitment is required to form global

and regional cooperation in order to supervise global

hedge fund activities. A balance must be struck between

legal protection and high performance so that hedge

funds can develop and support a liquid market and

maintain global stability. Emerging market countries must

regulate hedge fund activities in order to create sound

financial conditions.

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Article I

1. Amin, G. dan H. Kat (2003),ΔStocks, Bonds and

Hedge Funds: Not A Free Lunch!,Δ Journal of Portfolio

Management, Vol. 29, No. 4, (Summer): 113-120.

2. Berg, Andrew, dan Catherine Pattillo , (1999),ΔAre

Currency Crises Predictable: A Test,Δ IMF Staff Papers

46(2): 107-138.

3. Caprio, Gerard, dan Patrick Honohan,

(2000),ΔFinance and Growth: Policy Choices in a

Volatile World. Washington DC: World Bank.

4. Drury, Giles (2006), ≈Hedge Funds: A Catalyst

Reshaping Global InvestmentΔ, KPMG.

5. Eichengreen, B. dan Mathieson, D (1999), ≈Hedge

Funds: What Do We Really Know?,Δ International

Monetary Fund, September 1999.

Reference

6. Fung, William, dan David Hsieh, (1999),ΔA Premier

on Hedge Funds,ΔJournal of Empirical Finance, Vol.

6, No. 3 (September): 309-331.

7. Goldstein, Morris, Graciela Kaminsky, dan Carmen

Reinhart, (2000),ΔAssessing Financial Vulnerability: An

Early Warning System for Emerging Markets,Δ

Washington DC: Institute for International Economics.

8. Malkiel, Burton G. dan Saha, Atanu (2005), ≈Hedge

Funds: Risk and Return,Δ Financial Analyst Journal,

Volume 61, No. 6.

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Article II

The Efficiency of Indonesian Foreign Exchange Market

Bagus Santoso1, Pungky P. Wibowo2

I. INTRODUCTION

The concept of efficiency has a vital meaning in the

financial market. It is used to explain the market condition

in which the relevant information is perfectly reflected in

financial asset prices. Market efficiency is very much related

to the market responses which involves the new

information (public and private information).

Melvin (1995) argued that market is considered as

efficient should the price is able to reflect all available

information. In the case of foreign exchange market,

market efficiency would be established if the exchange

rate of spot and forward could adjust the new information

in the very short-term. According to market efficiency, the

forward rate would be different with the expected future

spot rate; this difference is called risk premium. However,

should the available information do not change the

This paper outlines the test of forward market efficiency in Indonesia employing spot and forward rates of

Rupiah against US$-5 days for a week delivery covering period of 4th September 1996 up to 7th October 2005.

The result estimation indicates a possibility of biased forward exchange rate in the short-term. Nevertheless, in

the long-term, forward rate is unbiased predictor for spot exchange rate.

forward rate and the forward rate reflects the spot rate in

the future, then the market could be considered as efficient.

On the other hand, if all available information could predict

future spot rate in a better way than in predicting forward

rate, then, the market could be considered as not efficient

yet.

Market is efficient should no agent is able to gain

some extra profit from the transaction based on the

available information (Jensen, 1978; Levich, 1985; Ross,

1987). Should a market, particularly financial market, is

considered as efficient, then the market agents are not

able to predict the foreign exchange rate and also not able

to set a trading model that may give extra profits for

themselves. In this case, the basic problem is about the

market dynamic factors and the redefinition of market

efficiency.

The characteristics of market efficiency based on the

conventional economists is a situation which there unable1 Lecturer at Gajah Mada University; [email protected] Senior Bank Researcher at Financial System Stability Bureau √ Directorate for Banking

Research and Regulation, Bank Indonesia; [email protected]

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Article II

the possibilities of market agents to gain excess return

through their trading transactions. Such condition is caused

by the assumption that all investors (market agents) refer

to the rational expectation model. The efficient market

transpires if each market agent can find partner which is

suitable in every transaction; including the time and the

price which are not biased by the hidden information.

Therefore, market could be considered as efficient should

follow two requirements: First, all information are available

for each market agent and the decision maker. Second,

the possibility in the differences in dimension or time scale

and the heterogeneous expectation from the market

agents.

This paper analysis aims to test the unbiasedness and

efficiency of forward market exchange rate in Indonesia.

Therefore, banking and financial control in order to

maintain the stability of financial system will be developed.

The structure of the paper could be organized as follows:

Chapter 1, it would discuss the background of market

efficiency. Chapter II, it would present the literature review.

Chapter III will conduct the discussion about research

method. In this Chapter III, it explains about the data and

research model which employed in order to test the

unbiasedness and efficiency of forward market. Chapter

IV presents the estimation and analysis results. The

conclusion will be presented in Chapter V.

II. EFFICIENT MARKET HYPOTHESIS

(SAMUELSON-FAMA EFFICIENT)

Based on the EMH approach, we have to concern

about the concept of Martingale Process. The concept of

Martingale Process is useful in the time series observation

which is mutually dependent. As an example, when our

observations are acquired from the feedback process; when

the dynamic process is nonlinear; and when the

information set increases since there is observation

accumulation.

A Martingale Discrete could be understood as

sequence of the value from the conditional events. The

value sequence could increase or decrease in the time

sequence. Mathematically, the Martingale Process could

be written as follows:

For the sequence: (X(t) : T = 1,2,...........), if,

E{X(t + 1) X(1), X(2),...., X(t)} = X(t),

Then sequence {X(t)} is considered as Martingale.

The Martingale Process involves sub-Martingales and

super-Martingales. A random process (X(t), Gt : t ∈ Τ) is

considered as sub-Martingale process if:

{|X (t)|} < ∞ and

E {X(t) | Gs} > X

s a.c., s < t; s, t ¤ T

Meanwhile the process is considered as super-

Martingale process if,

E {X(t) | Gs} ≤ X

s a.c., s < t; s, t ¤ T

Therefore, a Martingale process involves sub-

Martingale process and super-Martingale process.

If Gt is the historic information in which the Martingale

process is conditioned, we could define a Martingale-

Difference. A random process {X (t), Gt: t ¤ T} is considered

as Martingale-Difference (MD) if,

X (t) = Y (t) – Y (t-1), X(1) = Y(1)

In the random process {X (t), Gt : t ¤ T} is

Martingale. Besides that, the MD process could be defined

as E { X (t) | Gt-1

} = 0 if,

E { X (t) | Gt-1

} = E { Y (t) – Y (t-1) | Gt-1

}

= E { Y (t) | Gt-1

} - E { Y (t-1) | Gt-1

}

= Y (t-1) - Y (t-1) = 0

The MD process was employed by Samuelson (1965)

and (1970) in order to define the efficient market pricing

which assumed the independence and the stationary.

However, the critics from Mandelbrot (1966) stated that

MD process posses a limitation in explaining the efficient

of empirical speculative market.

Following Fama»s definition of market efficiency,

foreign exchange market will be efficient if exchange rates

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Article II

reflect all information available perfectly. Market efficiency

theory utilizes expectation since it deals with information.

Moreover, using rational expectation principles which states

there are no systematical errors in forecasting implies price

change is not predictable. However, efficiency does not

require prices or rate of returns follow a random walk with

zero mean or constant drift.

The Development of Market Efficiency

Definition

The idea about the heterogen expectation from the

market agents become the main issue in the theory of

market efficiency which is observed by the economists.

Shiller (1989) stated that most of the bond market agents

do not follow the rational expectation model. They tend

to follow the trend and format that has occurred. Frankel

and Foot (1990) also stated that foreign exchange market

involves the speculative aspects and the impacts of tecnical

analysis on the strategy of foreign exchange trader.

Therefore, the possibility of time expectation, which is

different, become the main focusamong the researchers

in expalining the theory of market efficiency. The other

efficiency concept is speculative efficiency. This concept

considers no possibility of unexploited speculative profit.

Degree of Market Efficiency

The identification of the degree of market efficiency

is not only useful in the accuracy of identification,

measurement, analysis and the risk management of

financial market, but also used to determine the accuracy

in financial instrument valuation and pricing; either both

fundamental or derivative.

The basic assumptionto measure the market

efficiency is whether the forecaster could predict accurately

either the return or the risk taht may occur in a market

(Cowless, 1933). Houthakker (1957) found that there was

a market significancy which is not efficient menemukan

adanya signifikansi pasar yang tidak efisien. Houthakker

analysed future price from the clothes, corn, and wheat.

He found that the profit could be gained by taking the

long position; or in the other word, the profits could be

gained from the investment on the assets which posse

the positive systemic risk; and consequently the today

price from the future price could be predicted by

expectation value of future spot price on the maturity date.

Moreover, Keynes (1930) and Hicks (1939) have

discussed a situation which is called as normal

backwardation. It is defined the backwardation occurs

when the speculator has tenedency to take long position,

while hedger has tendency to take short position. This

situation could occurr since the speculator needs

compensation from the market risk that they may have.

On the other side, hedgers would loose their average

profits. Hedger would receive this situation since the future

contract could decrease rge posibility risks that may occur.

Types of Market Efficiency

There are three types of market efficiency (Asal,

2000):

1. Weak form efficiency, where prices reflect all

information contained in the past prices. Therefore,

it is impossible to earn superior returns by looking

for patterns in prices. Testing the weak form efficiency

could be done by using filter test and serial correlation

test.

According to the Granger representation theorem,

returns for at least one currency in the co-integrated

system is predictable based on the error correction

term under the co-integrating systems of spot

exchange rates. This predictability implies a violation

of the weak-form market efficiency hypothesis. It also

means that non-stationarity of the currency risk

premium would imply inefficiency of the foreign

exchange market efficiency (Barkoulas et. al, 2003).

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Article II

Weak-form efficiency can be tested by using the

random walk model

yt = y

t-1 + εt (1)

Martingale and random walk theory of market

efficiency imply that since information affects exchange

rates randomly, therefore spot rates are unpredictable.

In addition, since new information is independent to

all previous information, the price changes cannot be

predicted by the past price changes.

In previous studies, random walk model is used to

analyzed observed price behavior in speculative

market, the martingale model posits that market

equilibrium only can be described in term of expected

yields or price changes, and the random walk model

entails that yields or price changes are identically

independently distributed. Theoretically, random walk

model requires stricter condition than Martingale

condition.

Early research concentrated on the autocorrelation

due to technical difficulties, so it is more concerned

on martingale properties than random walk. Feature

that distinguishes exchange rates markets to any other

markets are they are also determined by speculators

and central banks behavior. It is difficult to determine

whether inefficiency is because of the destabilizing

or central bank»s interventions.

Studies on exchange market efficiency by Poole (1967)

was carried out by using autocorrelation test and filter

rules found serial dependence. Dooley and Schafer

(1975) rejected the random walk hypothesis in their

study.

(Barkoulas et. al, 2003) test the unit-root hypothesis

they use a panel multivariate unit-root test, the

Johansen likelihood ratio (JLR) test for 1, 3, 6 and 12

month contract maturities under the condition of risk

aversion. The study uses six major currencies started

from 01/02/1980 to 12/31/1998. The results shows

that the forward premiums for six major currencies

are stationary and therefore support the efficient

market hypothesis.

2. Semi-strong form efficiency, where by including all

the public information available. The form of this test

is based on the degree of sensitivity or market

response to news or information announcement.

Investor does not get superior profit by using all public

information available.

Geweke and Feige divide semi-strong form efficiency

into:

a. Single market efficiency: all public information for

a single exchange rate is in the information set

b. Multi market efficiency: the information set

contains all information including information for

other exchange rates.

The semi-strong efficiency test could be conducted

by event study and by analyzing the abnormal return.

In the event study, it is analyzed how the market

responds to certain event which is announced to the

public. While, in the abnormal return analysis, market

is considered to be not efficient should there is one

or several market agents who experience abnormal

return in the long period based on the past

information and public information.

3. Strong form efficiency, where by including all the

private information, it is not possible for a market

participant to make abnormal profits.

In the strong form market efficiency, the price has to

reflect all available information. This kind of test

analyses whether specific investors or certain groups

have private information in order to get profit or not.

A group of information contains all information that

includes private information and market insider

trading which is not profitable.

All the profesionals manage their portfolios by

employing resources in order to get and use the

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Article II

personal or private information. The strong form

market efficieny is conducted by testing portfolio

performance in reflecting personnal or private

information.

In the strong form market efficiency, the test is

conducted based on the available private information

which may be possesed by market agents. The market

agents who may possess such information are insider

trading, securities analysts and finance managers.

Efficient market hypothesis have strict assumption i.e.

frictionless world, no transaction costs, and traders

have homogeneous expectation. Some researches

have proved that efficient market hypothesis is not

compatible when the assumptions are relaxed,

therefore they also have attempted to impose less

stricter assumptions.

Common claim perceived that nominal exchange rate

follows random walk behavior, therefore it can be

tested by unit root test, AR, and ARIMA. The concept

of co-integration is also used to test whether there

are long run association among spot rates and/or

forward exchange rates. For instance, the existence

of co-integration opposes the market efficiency

hypothesis, since a co-integrated system of spot rates

implies predictability of returns in at least one currency

(Barkoulas, et.al. 2003). Another early test of market

efficiency is autocorrelation test, either using

portmanteau statistics or modified portmanteau

statistics.

In foreign exchange market, the efficient market

hypothesis necessitate that the forward rates is the

best predictor of future spot rates. Following Bernhard

and Leblang (1999) this proposal are formulated

below:

ft,t+k

= Et (S

t+k) (2)

The equation means that the forward exchange rate

(f) at time t for delivery at time t+k should equal the

expected spot exchange rate (s) at time t+k (all

variables are in logarithms). Equation (3) states that

expected exchange rate is the best predictor of the

actual exchange rate:

St+k

= α + β [Et, (S

t+k)]+ ε

t+k(3)

where et is a random error which is uncorrelated to

the information set at time t and substituting (2) into

(3) yields:

St+k

= α + β ft,t+k

+ εt+k

(4)

To avoid non-stationary variables, both the spot and

the forward exchange rates are written as first

differences:

St+k

– St = α + β [ f

t,t+k – S

t ] + ε

t+k(5)

If a time-varying risk premium has the same

stochastic properties with the error-correction term

from the co-integrated system under risk aversion

conditions, then the foreign exchange market is

efficient, in other words it must be covariance

stationary. The risk premium can not be observed,

however they depend on the order of integration

of the forward premium. Thus, stationarity of

forward premium would directly imply stationarity

of the currency risk premium. Furthermore, it is in

line with the temporal behavior of the error

correction term in a co-integrated system of spot

exchange rates (Barkoulas, et.al. 2003).

Unbiased Forward Rate Hypothesis

The alternative method to measure exchange rate

expectation is conducted by employing forward exchange

rate since forward exchange rate is viewed as unbiased

predictor for forward spot rate. Based on the rationality

assumption, forward rate would be the same to the

expectation of future spot rate.

se

t+1 = f

t(6)

Equation (5) could also be written as follows:

E[ St+1

– ft I

t ] = 0 (7)

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Article II

Equation (7) states that forecast error employs

forward rates based on the average equal to zero.

Composite Efficiency Hypothesis

This hypothesis incorporates the previous two

hypothesizes which are Random Walk Hypothesis and

Unbiased Forward Rate Hypothesis. The expectation of

future spot rate is the weighted average of spot rate.

se

t+1 = ϖs

t + (1 – ϖ) / f

t(8)

This equation involves two kind of information which

are past information ( st ) and future information or rational

expectation ( ft ).

Forward Premium Puzzle

In efficient forward market, forward rate should be

a good predictor for the future spot rate. In line with this,

there is a concept called Forward Premium Puzzle. Forward

Premium Puzzle is explained as follows.

Δst = α + β ( f

t-1 – s

t-1 ) (9)

Based on efficient market hypothesis (EMH), Equation

(10) requires α = 0 and β =1 (nil hypothesis). This hypothesis

has repeatedly tested for different currency and period.

The results mainly suggest no rejection of nil hypothesis,

even β is negative for some cases. This condition indicates

forward premium puzzle.

Previous Studies

The study which considered the state financial

condition was developed by Asal (2000). This research is

conducted by Asal by analyzing stock market efficiency in

Egypt and testing weak-form efficiency. The data which

was employed to test weak-form efficiency are daily returns

data since 1st January 1992 up to 15th March 1997. The

employed data are data in index form in order to capture

the impact of changes in regulation switching on the

market as a whole. The analysis result which employed

three methods above indicates that Egypt stock market

was not efficient. In this regard, the analysis was done

within yearly interval. The analysis based on the yearly data

also concludes the same result which employed the whole

data.

III. METHODOLOGY

The Research Model

In an unbiased forward exchange market, the

forward transaction in t for t+1 delivery is equal to the

spot rate at t+1. In terms of weekly data, the forward rate

of today transaction should equal to spot rate of the

following week.

St+1

= β0 + β

1F

t + β

2Z

t + μ

t(10)

The analysis is focused on weak-form market

efficiency test. Therefore, the Z variables on the Equation

(8) are the the past values of spot rate and forward rate.

Data in financial sector are mainly not stationary. Due to

stationary reason, the above equation is modified to be

Equation (12).

ΔSt = α + β

1 (F

t 1 - S

t 1) + β

2Z

t(11)

H0: α = 0, β1 = 1

The Steps in Analyses

In order to test the unbiasedness and efficiency in

forward market, it would conduct the graphics and

econometric analysis. In the graphics analysis, it would

evaluate the development of spot exchange rate and

forward exchange rate. Besides that, it would also

analyze the forward premium and exchange rate

volatility.

In the econometric analysis, it would conduct

several tests, either for unit root test and co-integration

test. ARCH, GARCH and ADL model are also employed

to test the unbiasedness in forward market. The sample

period is also divided in order to evaluate whether there

us a structural break before and after the 1997 financial

crisis.

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Article II

IV. ANALYSES RESULTS

Graphical Analysis

Econometrics Analysis

Furthermore, the test of unbiasedness and the

efficiency of forward market are continued with

econometric analysis. The results could be presented as

follows:

1. Unit Root Test

2000

4000

6000

8000

10000

12000

14000

16000

18000

97 98 99 00 01 02 03 04 05

ST FT_1

Graph A2.1Spot and Forward Rate (One Week delivery)

Graph A2.2Forward Premium

-,06

-,04

-,02

,00

,02

,04

,06

1997 1998 1999 2000 2001 2002 2003 2004 2005

Log (FT_1/ST_1)

Based on graph A2.1, the forward rate for one week

delivery is seen coincided. In Figure 1, forward premium,

which is the rate of change of forward rate to spot rate, is

fluctuated around zero. This means that the ratio of

forward rate to spot rate is nearly one.

Graph A2.2 describes the forward premium or rate

of change of forward rate to spot rates. The time horizon

in this research indicates that forward rate ratio against

spot rate is almost equal to 1 (in the logarithm, it is almost

close to zero), even though the volatility looks very high.

However, this forward premium volatility is relatively smaller

than exchange rate volatility as indicated by graph A2.3.

The exchange rate volatility occurred mainly since 1997

financial crisis.

Graph A2.3Changes in Spot Rate Vs Forward Premium

-,4

-,2

,0

,2

,4

,6

1997 1998 1999 2000 2001 2002 2003 2004 2005

Log (FT_1/ST_1) Log (ST_1/ST_1)

The unit root test of spot exchange rate and forward

exchange rate are conducted in logarithm form. Table A2.1

describes that the result of unit root test on exchange rate

is not stationer, either conducted by Augmented Dickey-

Fuller (ADF) test, Phillip-Perron test and Kwiatkowski,

Phillips, Schmidt, and Shin (KPSS) Test. Both series has order

1, I(1), since they become stationer after they are converted

into first difference. Table A2.1 also indicates that series

LSt-LSt_1 (rate of change spot rate in period t deducted

Table A2.1Unit-Root Test

LSt All -2.5749 -2.5179 2.3958 Non

Stationary

LFt All -2.5034 -2.5015 2.3639 Non

Stationary

D(LSt) All -17.3639 -48.2007 0.3136 Stationary

D(LFt) All -20.8401 -48.6332 0.3072 Stationary

LSt-LSt_1 All -7.6321 -13.3654 0.2716 Stationary

LFt_1-LSt_1 All -9.0448 -38.0330 0.1828 Stationary

Variable Sample ADF PP KPSS Conclusion

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Article II

by rate of change spot rate in period t-1) and LFt_1-LSt_1

(rate of change forward rate deducted by rate of change

spot rate in period t-1) are stationer.

2. Vector Autoregressive (VAR)

Furthermore, VAR method was employed in order

to determine the optimum lag. The test is conducted by

employing LR, Forecast Prediction Error (FPE), Akaike info

criterion (AIC), Schwarz criterion (SC), and Hannan-Quinn

criterion (HQ) methods. The test was started since the long-

lag which is lag 60. The estimation results in Table A2.2

indicates optimum lag which is different in every test

method, except for the results of FPE and AIC which gave

the same optimum lag that is lag 32.

normalized co-integrating coefficients which posses 1 as

its value. It implies that in the long-term, any 1% change

in forward exchange rate would be followed by the

changes in spot exchange rate by 1%. Therefore, in the

long-term, forward exchange rate is unbiased estimator

from spot exchange rate.

Table A2.2Optimal VAR Lag Length LSt and LFt_1

51 32 32 7 10

LR FPE AIC SC HQ

3. Johansen Cointegration Test

Based on the results of optimum lag that are

conducted by all five methods above, it is also conducted

the co-integration test by employing the Johansen Co-

integration and forward exchange rate. The test results

could be followed in Table A2.3 and A2.4.

The test results indicate that there is one-to-one

relationship between spot and forward exchange rate.

This finding is described by long-run coefficient and

None ** 0.0100 31.1174 15.4100 20.0400

At most 1 ** 0.0033 7.7233 3.7600 6.6500

No. of CE(s) Eigenvalue Statistic Critical CriticalValue Value

Hypothesized Ω Trace 5 Percent 1 Percent

1 Cointegrating Equation(s): Log likelihood 14941.24

Normalized cointegrating coefficients (std.err. in parentheses)

LST LFT_1

1.0000 -1.0011

Std Error 0.0015

T-Stat -0.7047

Table A2.4Johansen Cointegration Test LSt and LFt_1

Table A2.3Johansen Cointegration Test between LSt and LFt_1

Lags interval: 1 to 31 Ω Ω Ω Ω

Selected (5% level) Number of Cointegrating Relations by Model

(columns)

Data Trend: None None Linear Linear Quadratic

Rank or No Intercept Intercept Intercept Intercept Intercept

Trace 1 1 2 1 2

Max-Eig 1 1 2 1 2

No. of CEs No Trend No Trend No Trend Trend Trend

Table A2.5Unbiased Forward Rate Test (1), All Sample

C 1.00497 0.17671 5.68715 0.00000

LFT_1(-1)/LST_1(-1) -0.00458 0.17669 -0.02594 0.97930

Variable Coefficient Std. Error t-Statistic Prob.

Dependent Variable: LST/LST_1

Method: Least

SquaresΩ

Sample(adjusted): 9/12/1996 10/03/2005

R-squared 0.00000 Mean dependent var 1.00038

Adjusted R-squared -0.00042 S.D. dependent var 0.00546

S.E. of regression 0.00546 Akaike info criterion -7.58137

Sum squared resid 0.07042 Schwarz criterion -7.57649

Log likelihood 8959.39371 F-statistic 0.00067

Durbin-Watson stat 0.35581 Prob(F-statistic) 0.97930

4. The Test of Unbiased Forward Exchange Rate

in the Short-Term

In the short-term, Indonesian forward market

experiences forward premium puzzle. In this regard, the

coefficient in premium forward in Table A2.5 is very far from

1 and is also not significant. Meanwhile, the hypothesis,

which states that the coefficient is equal to zero, is rejected

since the coefficient is significant. This result is not really

21a

Article II

accommodate the possibility of overlapping data. The

estimation results could be followed in Table A2.7.

In Table A2.7, it could be seen that the coefficient of

both forward premium or the lag of forward premium is

significant but far away from 1. This situation indicates

the forward premium puzzle. Meanwhile, the lag of spot

rate changes indicates the coefficient which is relatively

bigger and significant. Therefore, in the short-term, the

dominant that would affect the rate of change in the spot

exchange rate is the past value from the rate of change in

spot exchange rate itself.

Furthermore, the components of ARCH and GARCH,

which are significant and have bigger values than 1,

indicate the event of non stationary variance. In this case,

it could be concluded that Indonesian foreign exchange

market is very volatile.

The situation above is not really different whether the

sample observation is limited only in the 2001-2005 period

as described in Table A2.8. It indicates that in the short-

term, the rate of change in spot exchange rate is more

dominated by the rate of change in spot exchange rate

itself; while the impact of forward premium is relatively small.

different, should it only employ the observation sample since

2002 up to October 2005 (Table A2.6).

Furthermore, should it is analyzed more deeply, the

estimation results indicates autocorrelation problem. This

result is confirmed by the score of Durbin-Watson test

which indicates a quite high positive autocorrelation.

Table A2.6Unbiased Forward Rate Test (2), Sample 2002 - 2005

C 0.9432 0.0590 15.9741 0.0000

LFT_1(-1)/LST_1(-1) 0.0568 0.0590 0.9628 0.3359

Dependent Variable: LST/LST_1Ω Ω Ω

Method: Least

Squares

Sample(adjusted): 1/01/2002 10/03/2005

Variable Coefficient Std. Error t-Statistic Prob.


Adjusted R-squared -0.0001 S.D. dependent var 0.0013





5. Autoregressive Conditional Heteroscedascity

(ARCH) and Generalized ARCH

Due to the autocorrelation problem, then the ARCH

and GARCH tests are conducted. These tests are based on

the assumption that in the financial time series, the residual

values are often correlated to the residual values from the

previous period. In this case, it also examined whether there

are different behavior o results should the sample period

is differentiated.

The ARCH and GARCH components, which are

incorporated into this model, could be used to

accommodate volatility especially the conditional variance.

In the ARCH, conditional variance of the dependent

variable is modeled as a function from the past value of

dependent and independent variables. While, in the

GARCH, the past value of conditional variance is added to

the ARCH model. In this estimation, it is also incorporated

the component of moving average (MA) in order to

Table A2.7Unbiased Forward Rate Test (3), all sample

C 0.00010 0.00012 0.82737 0.40803

LOG(ST(-1)/ST_1(-1)) 0.73668 0.01433 51.41477 0.00000

LOG(FT_1/ST_1) 0.21379 0.02689 7.95136 0.00000

LOG(FT_1(-1)/ST_1(-1)) -0.10737 0.03834 -2.80061 0.00510

MA(1) 0.20051 0.02529 7.92951 0.00000

Coefficient Std. Error z-Statistic Prob.


Adjusted R-squared 0.67911 S.D. dependent var 0.04876





Inverted MA Roots -0.20000

Variance Equation

C 0.00000 0.00000 2.13283 0.03294

ARCH(1) 0.12360 0.00419 29.47307 0.00000

GARCH(1) 0.90761 0.00182 499.40433 0.00000

22a

Article II

6. GARCH Model; General to Specific

Moreover, the GARCH model is employed again by

the starting lag which is quite long; in this regard, it is 40

lag. The selection of this optimum lag is based on the

theory of reduction, where a insignificant lag is excluded

sequentially from the model. Several lags, which are not

significant, are still incorporated into the model since they

are still relevant. In this model, any changes in forward

premium (dLFt) are treated as fixed variable. It is conducted

in order to test whether this variable is 1 or not.

The estimation result in Table A2.9 indicates again

that there is forward premium puzzle since the coefficient

of forward premium is just 0,03 and also not significant.

The variables which determine the rate of change in spot

exchange rate are past values in the rate of change of

spot exchange rate (dLSt_1), with the coefficient of 0,975.

Table A2.8Unbiased Forward Rate Test (4), Sample 2001 - 2005

C 0.00025 0.00012 2.11562 0.03438

LST(-1)-LST_1(-1) 1.20774 0.05110 23.63663 0.00000

LST(-2)-LST_1(-2) -0.39240 0.04236 -9.26456 0.00000

LFT_1-LST_1 0.21076 0.02884 7.30821 0.00000

LFT_1(-1)-LST_1(-1) -0.17913 0.03533 -5.07055 0.00000

MA(1) -0.34335 0.06420 -5.34847 0.00000







Inverted MA Roots 0.34000

Variance Equation

C 0.00001 0.00000 12.57865 0.00000

ARCH(1) 0.49898 0.02543 19.61993 0.00000

GARCH(1) 0.54671 0.02316 23.60178 0.00000


Dependent Variable: LST-LST_1 Ω Ω Ω

Method: ML - ARCH (Marquardt) Ω

Date: 12/26/05 Time: 13:53 Ω

Sample(adjusted): 1/01/2001 9/30/2005

Included observations: 1240 after adjusting endpoints

Convergence achieved after 113 iterations Ω

MA backcast: OFF, Variance backcast: OFF Ω Ω

7. Autoregressive Distributed Lag (ADL)

The variables that are tested in table A2.9 are in the

first-difference form. This is done in order to avoid the

possibility of spurious regression. The ADL model enables

us to conduct the estimation on the level without worry

about spurious regression problem. Therefore, the next

estimation employs ADL model then applying the theory

of reduction. The estimation results with ADL model could

be followed in Table A2.10.

Table A2.9GARCH Model: General to Specific

dLSt_1 0.9753 0.0163 0.0249 39.2000 0.0000

dLSt_3 -0.0118 0.0216 0.0257 -0.4610 0.6450

dLSt_5 -0.8409 0.0273 0.0377 -22.3000 0.0000

dLSt_6 0.8515 0.0291 0.0412 20.7000 0.0000

dLSt_8 -0.0303 0.0262 0.0349 -0.8680 0.3860

dLSt_9 -0.0108 0.0223 0.0320 -0.3380 0.7350

dLSt_10 -0.6906 0.0341 0.0525 -13.1000 0.0000

dLSt_11 0.6956 0.0321 0.0559 12.4000 0.0000

dLSt_13 -0.0263 0.0203 0.0266 -0.9880 0.3230

dLSt_15 -0.5832 0.0327 0.0589 -9.9100 0.0000

dLSt_16 0.6581 0.0360 0.0921 7.1500 0.0000

dLSt_17 -0.0853 0.0235 0.0478 -1.7900 0.0740

dLSt_20 -0.4562 0.0303 0.0633 -7.2100 0.0000

dLSt_21 0.5543 0.0359 0.1147 4.8300 0.0000

dLSt_22 -0.1811 0.0280 0.0733 -2.4700 0.0140

dLSt_23 0.0211 0.0167 0.0245 0.8610 0.3890

dLSt_25 -0.2803 0.0274 0.0623 -4.5000 0.0000

dLSt_26 0.3974 0.0323 0.1074 3.7000 0.0000

dLSt_27 -0.1444 0.0238 0.0596 -2.4200 0.0150

dLSt_30 -0.1489 0.0199 0.0466 -3.2000 0.0010

Variables Coefficient Std.Error robust-SE t-value t-prob

dLSt_31 0.2371 0.0244 0.0815 2.9100 0.0040

dLSt_32 -0.1007 0.0173 0.0470 -2.1400 0.0320

dLFt 0.0346 0.0265 0.0239 1.4500 0.1480

alpha_0 0.0000 0.0000 0.0000 2.0000 0.0460

alpha_1 0.1517 Ω

beta_1 0.8483 Ω Ω 23.7000 0.0000

Variables Coefficient Std.Error robust-SE t-value t-prob

log-likelihood 7407.0042 HMSE 21.689mean(h_t) 0.0005 var(h_t) 2.771E-06no. of observations 2331.0000 no. of parameters 26.000AIC.T -14762.0084 AIC -6.333mean(dLSt) 0.0032 var(dLSt) 0.002alpha(1)+beta(1) 1 alpha_i+beta_i>=0, alpha(1)+beta(1)<1

23a

Article II

Based on the Table A2.10, the variables that influence

on the rate of change of spot exchange rate are past value

of the rate of change from the spot exchange rate. Such

condition is described by AR(1) which is significant. Even

though LST_1(-1), the value of the logarithm of the spot

exchange rate for the previous one week, is incorporated

into the model, the coefficient of AR(1) is bigger than

LST_1(-1). This situation indicates that the most influential

variable on the rate of change of spot exchange rate is

the rate of change on the spot exchange rate from the

previous one-day. Therefore, this estimation model World

gives the same result with the previous estimations.

In that model, it s also incorporated the component

of threshold (asymmetric) ARCH (TARCH). If the coefficient

of TARCH, which is (RESID<0)*ARCH(1), is not positive

significantly, therefore there wont be asymmetric effects.

On the other hand, if (RESID<0)*ARCH(1) is positively

significant, therefore it indicates that there us a leverage

effect in the conditional variance.

In the application, the value (RESID<0)*ARCH(1),

which has negative value in Table A2.10 above, indicates

that the volatility decreases. In this regard, if the market

agents predict the exchange rate by punishing the market

in such away until its prediction is above its actual value,

then in the next period, it won»t predict as high as in the

previous period. Therefore, it would be stabilization process

until the volatilities decreased.

8. The Structural Break Test

The issues about outliers and seasonality are also

incorporated into estimation. This condition is conducted

by employing the Dummy variable into the model. In this

regard, the structural break test is conducted by using

Chow test. The estimation result indicates that this model

is robust enough and does not involve any structural break

(Table A2.11).

Table A2.10Model ADL

C 0.0079 0.0077 1.0272 0.3043

LST_1 0.3139 0.0052 60.7839 0.0000

LST_1(-1) 0.2980 0.0030 100.9150 0.0000

LST_1(-2) 0.2648 0.0146 18.1129 0.0000

LFT_1 0.0214 0.0163 1.3112 0.1898

LFT_1(-1) 0.0480 0.0151 3.1783 0.0015

LFT_1(-2) 0.0530 0.0123 4.3095 0.0000

AR(1) 0.8432 0.0116 72.6997 0.0000

MA(1) 0.2747 0.0202 13.6077 0.0000


Dependent Variable: LST Ω Ω Ω

Method: ML - ARCH (Marquardt) Ω

Sample(adjusted): 9/16/1996 9/30/2005 Ω

Included observations: 2360 after adjusting endpoints Ω

Convergence achieved after 362 iterations Ω

MA backcast: 9/13/1996, Variance backcast: ON Ω Ω

Variance Equation

C 0.0000 0.0000 0.7516 0.4523

ARCH(1) 0.1233 0.0050 24.6745 0.0000

(RESID<0)*ARCH(1) -0.0832 0.0068 -12.3133 0.0000

GARCH(1) 0.9369 0.0012 764.4719 0.0000







Inverted AR Roots 0.8400

Inverted MA Roots -0.2700

Table A2.11Specific Model of Log Spot Rate

Constant 0.0166 0.0050 3.3130 0.0009

LFT1_18 -0.0570 0.0143 -3.9800 0.0001

LFT1_26 -0.0594 0.0150 -3.9520 0.0001

LFT1_27 0.0609 0.0148 4.1080 0.0000

LFT1_29 -0.0406 0.0084 -4.8610 0.0000

LST_1 1.0326 0.0101 101.8510 0.0000

LST_3 -0.0925 0.0177 -5.2370 0.0000

LST_4 0.0684 0.0191 3.5860 0.0003

LST_5 0.0539 0.0200 2.6970 0.0070

LST_6 -0.0472 0.0195 -2.4210 0.0155

LST_7 0.0555 0.0192 2.8900 0.0039

LST_8 -0.0603 0.0138 -4.3800 0.0000

Variables Coeff StdError t-value t-prob

LST_13 0.0468 0.0142 3.2870 0.0010

LST_14 -0.0892 0.0183 -4.8860 0.0000

LST_15 0.0432 0.0159 2.7110 0.0068


24a

Article II

RSS 0.3008 sigma 0.0116 Ω

LogLik 10448.0000 AIC -8.8826 Ω

T 2333.0000 p 86.0000 Ω

R^2 0.9993 Radj^2 0.9993 Ω

HQ -8.8053 SC -8.6704 Ω

FpNull 0.0000 FpGUM 0.6140

value prob Ω Ω

Chow(1202:1) 0.2160 1.0000 Ω

Chow(2135:1) 0.1987 1.0000

LST_17 -0.0461 0.0155 -2.9660 0.0030

LST_18 0.0829 0.0183 4.5380 0.0000

LST_19 -0.0453 0.0139 -3.2590 0.0011

LST_24 0.0486 0.0132 3.6890 0.0002

LST_29 0.0432 0.0102 4.2520 0.0000

With Dummy OutliersΩ


Table A2.11Specific Model of Log Spot Rate (cont.)

9. Long Run Coefficient

indicates that the coefficient Ft-1 is close to 1; while the

value of the constantan is close to zero. This result is similar

to the estimation result by employing VAR model.

Therefore, it is concluded that in the long-term, forward

exchange rate is not bias.

V. CONCLUSION

The result estimation indicates a possibility of biased

forward exchange rate in the short-term. The coefficient

β=1 and α=0, therefore, it would create forward premium

puzzle. However, in the long-term, forward exchange rate

is unbiased predictor for spot exchange rate. Therefore, it

concludes that Indonesian forward market is not efficient

since the shock is not responded yet instantaneously. The

Shocks are only responded in the long-term.

Realizing that Indonesian forward market is very thin,

this is a quite normal result, as exists in other countries

such as New Zealand and Russia. Therefore, the role of

government is expected to encourage the forward market

in order to enable more players in forward market. As a

result, it would increase the activities in forward market

and creating market efficiency.

Table A2.12Dynamic Analysis Long Run Coefficient

Ft_1 1.019 0.007 B=1 2.754

Constant -0.176 0.062 B=0 -2.845

Variable Long-run Coef SE Ho t

From the ADL estimation ADL, the long run

coefficient Ft-1 on St (Table A2.12) is calculated. That result

25a

Article II

References

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Market EfficiencyΔ.

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Baillie, Richard T. and Rehim Kihc. 2005. ≈Do Asymmetric

and Nonlinear Adjusments Explain The Forward

Premium AnomalyΔ.

Benhard, William dan David Leblang. 1999. ≈Political

Processes and Foreign Exchange MarketΔ.

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American Political Science Association.

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Policy and Long-Horizon Uncovered Interest ParityΔ.

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Future Market Efficiency using Adaptive EstimationΔ.

University of Texas at Arlington.

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Interest Parity in The LaboratoryΔ.

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Market EfficiencyΔ. Harvard Institute of Economic

Research (HIER).

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Oil Prices, And International Spillovers On Russian

Financial MarketsΔ.

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Techniques to Central BanksΔ.

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Regarding Market EfficiencyΔ. Journal of Financial

Economics, Vo. 6 Nos. 2/3.

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and The Currency Crisis in KoreaΔ.

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Efficient Markets and the Forward Exchange RateΔ.

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26a

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27a

Glossary, Abbreviation, Appendix

Glossary, Abbreviation,Appendix

28a



29a


Bearish : A market has a bearish trend when prices are falling in a prolonged

period of time

Bullish : The opposite situation of bearish market

Bubble : A situation in which a wave of public enthusiasm causes an exaggerated

bull market. When such a bubble takes place, market price of asset

(listed stocks, property or other securities) rise dramatically, making

them significantly overvalued by any measure of stock valuation.

Generally asset market bubbles are followed by market crashes.

Capital Adequacy Ratio : The ratio of a bank»s capital to its risk-weighted credit exposure.

International standards recommend a minimum for this ratio, intended

to permit banks to absorb losses without becoming insolvent, in order

to protect depositors.

Capital Outflow : A net flow of capital, real and/or financial, out of a country, in the

form of reduced holdings of domestic assets by foreigners and/or

increased purchases of foreign assets by domestic residents. Recorded

as negative, or a debit, in the balance on capital account.

Competitive Advantage : Competitive advantage is a position attained by a firm when it occupies

in its competitive position. Competitive advantage is attained when a

company makes economic earnings exceeding their costs (including

cost of capital). This means that normal competitive pressures are not

able to drive down the firm»s earnings to the point where they cover

all costs and just provide minimum sufficient additional return to keep

capital invested.

Contingency Plan : A plan involving suitable backups, immediate actions and longer term

measures for responding to computer emergencies such as operational

failure, for backup procedures, disaster recovery. It is also plans

maintained for emergency response, backup operations, and post-

disaster recovery for an information system, to ensure the availability

of critical resources and to facilitate the continuity of operations in an

emergency situation.

Debt Swap : Transaction involving exchanges existing bonds (or other debt

Glossary

30a


instruments) for newly issued stock (equity). A debt-equity swap can

help a company that is in financial trouble by canceling some of its

outstanding debt.

Disaster Recovery Center : Preventative measures using redundant hardware, software, data

centers and other facilities to ensure that a business can continue

operations during a natural or man-made disaster and if not, to restore

business operations as quickly as possible when the calamity has passed.

Downsizing : Employee reassignment, layoffs and restructuring in order to make a

business more competitive, efficient, and/or cost-effective

Emerging Countries : The markets of countries which have a low per head income compared

with the developed world. Emerging markets attract because the

potential for rapid economic growth in emerging market countries is

better than in more mature markets. However, the risks, both economic

and political, are high.

Good Corporate Governance : The set of processes, customs, policies, laws and institutions affecting

the way a corporation is directed, administered or controlled. Corporate

governance also includes the relationships among the many players

involved (the stakeholders) and the goals for which the corporation is

governed.

Financial Deepening : Financial deepening refers to the increased provision of financial services

with a wider choice of services geared to all levels of society.

Hedge Fund : A hedge fund is a private investment fund charging a performance

fee and typically open to only a limited number of investors, e.g.,

those in the United States, hedge funds are largely open to limited

investors only. Hedge funds are not currently subject to any direct

regulation by the SEC, the NASD, or other federal regulating

commissions, unlike mutual funds, pension funds, and insurance

companies.

Niche Market : A niche market is a focused, targetable portion (subset) of a market

sector. By definition, then, a business that focuses on a niche market is

addressing a need for a product or service that is not being addressed

by mainstream providers. A niche market may be thought of as a

narrowly defined group of potential customers.

Non Performing Loans (NPLs) : Loans that are in default or close to being in default.

31a


Risk-Based Supervision : The risk based supervision approach entails the monitoring of banks

by allocating supervisory resources and focusing supervisory attention

according to the risk profile of each institution. The instruments of risk

based supervision will be by way of enhancements of the supervisory

tools traditionally used, viz., off-site monitoring and on-site examination

supplemented by a market intelligence mechanism.

Wealth Effect : An increase in spending that accompanies an increase in \o ≈WealthΔ

wealth

32a


ARO : Automatic Roll Over

ATM : Anjungan Tunai Mandiri

BoP : Balance of Payment

CAR : Capital Adequacy Ratio

CIB : Credit Information Bureau

CIS : Credit Information System

DCS : Direct Cash Subsidy

DER : Debt to Equity Ratio

DIS : Debtor Information System

DRC : Disaster Recovery Center

ER : Efficiency Ratio

FSN : Financial Safety Nets

GCG : Good Corporate Governance

GDP : Gross Domestic Product

IBA : Indonesian Banking Architecture

IDI : Individual Debtor Information

IDIC : Indonesia Deposit Insurance Corporation

IFSD : Information System of Funding Provision

IPO : Initial Public Offering

JCI : Jakarta Composite Index

LDR : Loan to Deposit Ratio

MSME : Micro Small and Medium Enterprises

NAV : Net Asset Value

NCD : Non Core Deposit

NII : Net Interest Income

NOP : Net Open Position

NPL : Non Performing Loan

ORI : Obligasi Ritel Indonesia

ROA : Return on Asset

ROE : Return on Equity

Abbreviation

33a


RTGS : Real Time Gross Settlement

RWA : Risk Weighted Asset

SBI : Sertifikat Bank Indonesia

SKNBI : Sistem Kliring Nasional Bank Indonesia

SUN : Surat Utang Negara

34a


Table - Appendix 1Banking Key Indicators

2002 Jan 1,042.13 351.50 791.91 1.042.47 3.30Feb 1,086.44 351.82 789.43 1.035.17 3.21Mar 1,064.60 350.59 783.36 1.022.70 3.42Apr 1,056.45 350.12 785.05 1.020.70 3.38May 1,053.44 346.91 787.01 1.016.23 3.35Jun 1,048.06 357.43 791.06 1.013.19 3.55Jul 1,072.55 369.05 808.80 1.039.03 3.66Aug 1,077.41 377.04 811.16 1.041.00 3.82Sep 1,092.50 387.69 814.97 1.049.73 3.71Oct 1,104.30 394.27 821.53 1.053.60 3.65Nov 1,095.79 402.18 815.36 1.041.15 3.85Dec 1,112.20 410.29 835.78 1.023.60 4.01



2005 Jan 1,258.39 590.72 950.06 1.147.29 5.81Feb 1,262.63 601.82 948.83 1.156.61 5.43Mar 1,280.57 617.79 959.25 1.128.41 5.99Apr 1,312.75 629.68 978.62 1.207.65 5.96May 1.324.74 650.78 986.74 1.222.41 5.57Jun 1,344.60 664.30 1.011.01 1.239.93 6.13Jul 1,353.19 677.61 1.015.99 1.257.73 5.72Aug 1,346.61 702.22 1.046.82 1.290.53 6.04Sep 1,418.62 715.28 1.077.54 1.283.34 5.90Oct 1,420.29 719.86 1.071.10 1.279.54 6.00Nov 1,428.08 722.44 1.091.33 1.283.30 6.17Dec 1,469.83 730.16 1.127.94 1.353.21 6.22

2006 Jan 1,465.64 714.22 1.116.19 1.354.52 6.90Feb 1,466.34 714.69 1.123.69 1.346.15 5.60Mar 1,465.30 722.74 1.123.87 1.346.59 6.82Apr 1,466.92 733.43 1.123.16 1.360.64 6.49May 1,514.92 747.58 1.160.61 1.400.54 7.17Jun 1,519.44 757.35 1.168.25 1.405.96 7.58

Total Assets Credits Deposits Earning AssetsPeriod

Trillions of Rp

Net InterestIncome

35a


Table - Appendix 2Key Indicators of Multi Finance Companies

2002 Jan 15,623,442 825,002 12,344,428 4,527,869 √ 508,660 3,424,238Feb 30,697,389 1,616,754 17,458,489 11,237,392 746,438 2,019,053 6,897,839Mar 30,326,515 1,632,855 17,172,177 10,409,834 746,597 1,983,866 6,976,972Apr 30,431,436 1,626,587 17,328,451 10,018,803 746,957 2,018,329 6,980,137May 30,440,907 1,800,165 17,432,047 9,019,175 1,122,901 1,928,227 6,967,312Jun 31,142,647 1,965,286 17,056,838 9,629,097 1,423,963 1,891,852 7,043,242Jul 31,481,849 1,896,363 17,455,779 10,040,435 1,424,565 1,983,870 6,879,451Aug 32,263,648 1,929,989 17,776,589 9,913,796 1,425,168 1,932,952 7,113,087Sep 32,946,620 1,928,571 18,042,553 9,896,032 1,725,770 1,923,246 7,268,456Oct 33,331,760 1,942,874 18,039,650 10,103,689 1,719,181 2,007,575 7,596,971Nov 33,267,621 2,024,035 17,593,247 9,776,885 1,678,995 2,007,860 8,532,375Dec 32,938,949 2,086,276 16,615,726 9,794,781 1,676,809 1,974,889 8,570,361

2003 Jan 32,979,169 2,043,991 16,362,436 9,751,022 1,642,058 2,009,823 8,727,794Feb 32,829,258 2,268,475 16,391,746 9,700,099 1,643,092 2,014,849 8,775,364Mar 31,011,949 1,461,818 13,615,445 9,917,301 1,344,124 2,002,213 8,729,636Apr 33,303,991 2,128,351 16,346,185 9,559,602 1,344,888 2,314,212 9,367,443May 33,495,759 2,177,168 15,590,878 9,125,517 2,716,153 1,939,099 9,457,917Jun 34,599,934 2,303,616 15,930,444 9,006,324 2,700,111 1,933,575 8,876,622Jul 36,179,693 2,328,708 16,589,037 11,644,034 2,899,223 1,967,976 9,031,278Aug 36,079,019 2,278,684 16,472,976 11,143,451 3,396,464 1,970,407 8,957,974Sep 37,072,526 2,349,824 16,646,349 11,778,433 3,375,734 1,688,960 9,061,156Oct 38,615,465 2,029,741 17,127,971 12,038,187 3,556,619 1,704,654 9,138,407Nov 39,688,224 1,861,639 17,783,741 11,955,673 4,000,489 1,792,090 9,009,298Dec 38,386,223 1,141,633 15,633,119 11,688,392 4,003,093 1,932,805 9,026,329

2004 Jan 40,616,426 1,913,262 17,720,248 12,625,854 3,989,726 1,885,432 9,581,229Feb 41,306,912 1,376,444 16,258,604 13,257,433 4,921,270 1,885,546 9,963,667Mar 43,789,745 2,090,052 18,030,256 14,084,379 6,431,529 1,898,598 10,318,841Apr 44,211,281 1,883,949 17,716,796 14,134,521 6,915,734 1,826,846 10,156,847May 45,943,843 1,920,998 18,777,519 17,025,930 6,481,879 1,927,854 10,282,204Jun 47,939,833 2,013,740 20,027,191 18,000,304 6,809,129 1,924,222 10,379,378Jul 48,813,559 2,055,190 20,358,809 17,550,821 6,789,449 2,276,476 10,322,807Aug 49,781,802 2,175,215 21,298,497 19,351,608 6,512,670 2,074,503 10,347,518Sep 49,926,060 2,107,179 21,755,980 19,665,735 6,910,873 2,130,472 10,465,181Oct 53,307,707 2,305,539 22,556,282 21,526,613 8,850,107 2,097,092 10,575,232Nov 54,479,821 2,198,896 22,493,852 22,710,039 8,785,520 2,101,520 10,613,569Dec 55,753,031 2,323,800 23,951,479 22,969,003 8,861,444 2,158,183 11,032,370

2005 Jan 55,822,974 2,396,475 23,107,640 23,466,301 9,844,906 2,119,916 10,943,456Feb 57,638,201 2,347,439 23,240,433 24,839,796 10,762,861 1,321,625 11,013,741Mar 59,263,126 2,395,036 24,544,118 24,745,033 10,442,356 2,223,494 11,069,118Apr 60,829,807 2,383,116 24,663,125 25,991,791 10,828,055 2,234,106 11,108,723May 59,864,976 2,501,725 25,117,762 25,091,604 9,879,550 2,218,547 11,162,620Jun 64,168,381 2,932,585 26,190,619 26,057,043 11,410,168 2,273,498 11,525,673Jul 66,113,680 3,067,969 28,039,150 27,349,112 11,621,463 1,547,447 11,629,819Aug 67,702,266 2,662,812 29,489,168 29,006,200 11,415,892 1,554,018 11,252,270Sep 67,702,266 2,718,988 29,489,168 29,603,478 10,809,675 1,554,018 11,619,922Oct 68,221,489 2,469,350 29,144,575 29,983,952 10,416,697 1,536,605 11,541,151Nov 67,443,676 2,401,562 28,935,212 31,474,348 10,219,178 355,934 11,791,744Dec 67,646,734 2,480,054 29,503,054 31,305,050 10,171,490 358,453 11,877,424

2006 Jan 66,844,223 2,016,302 29,019,441 30,521,664 9,673,961 153,257 1,2165,632Feb 65,708,529 2,101,404 27,495,880 30,664,698 9,508,380 154,380 12,292,602Mar 64,870,643 1,941,163 27,550,936 30,010,949 10,342,049 152,878 13,023,882Apr 65,487,852 2,209,401 27,144,550 30,125,792 10,740,741 145,853 13,020,999May 66,789,425 1,733,501 27,854,449 32,016,633 10,336,417 151,167 13,595,480Jun 68,201,883 1,699,523 27,128,551 31,891,260 12,386,364 146,120 13,677,109

PeriodFinancingAmount

CurrentLiabilities

On ShoreLiabilities

Off ShoreLiabilities Bonds

SubordinatedLoans Capital

Millions of Rp

36a


Table - Appendix 3Indicators of Equity Market

2002 Jan 451.64 272.88 0.473Feb 453.25 282.49 -0.223Mar 481.78 318.70 0.232Apr 534.06 344.78 0.404May 530.79 332.60 0.033Jun 505.01 315.76 -0.053Jul 463.67 285.40 1.001Aug 443.67 276.31 0.083Sep 419.31 260.23 0.875Oct 369.04 234.52 0.324Nov 390.43 246.74 -0.017Dec 424.95 268.78 4.780

2003 Jan 388.44 238.59 0.152Feb 399.22 250.86 -0.002Mar 398.00 251.58 0.008Apr 450.86 284.29 0.010May 494.78 320.72 0.001Jun 505.50 339.73 0.060Jul 507.99 345.73 1.488Aug 529.68 356.54 0.103Sep 597.65 396.02 2.125Oct 625.55 407.31 2.382Nov 617.08 411.67 0.999Dec 691.90 460.37 2.551

2004 Jan 752.93 501.17 1.827Feb 761.08 509.31 2.459Mar 735.68 492.51 2.117Apr 783.41 529.81 1.694May 732.52 493.27 -0.325Jun 732.40 495.80 0.108Jul 756.98 514.61 0.849Aug 754.70 514.19 0.177Sep 820.13 558.76 2.223Oct 860.49 585.93 1.300Nov 977.77 667.42 4.262Dec 1,000.23 679.95 2.147

2005 Jan 1,045.44 710.37 2.006Feb 1,073.83 731.36 0.634Mar 1,080.17 735.81 -19.070Apr 1,029.61 701.83 0.798May 1,088.17 740.30 -17.986Jun 1,122.38 765.81 2.344Jul 1,182.30 805.45 2.064Aug 1,050.09 721.22 2.899Sep 1,079.28 757.45 3.228Oct 1,066.22 740.69 5.878Nov 1,096.64 758.38 0.541Dec 1,162.64 801.25 1.284

2006 Jan 1,232.32 846.54 2.192Feb 1,230.66 850.96 0.685Mar 1,322.97 910.56 1.936Apr 1,464.41 1,003.76 3.042May 1,330.00 914.91 0.719Jun 1,310.26 901.02 -0.606

Capitalization Foreign Investors Transactions(Trillions of Rp) (Trillions of Rp)

Period Jakarta Composite Index

37a


Table - Appendix 4Indicators of Bond Market

2002 Jan 18,830.91 144.90 64,772.23 6,459.96Feb 18,830.91 152.00 68,772.23 10,562.98Mar 18,199.31 65.78 71,821.15 8,448.65Apr 18,518.31 630.77 72,559.90 3,721.35May 19,068.31 366.12 74,418.90 10,460.72Jun 19,406.64 510.69 111,485.33 9,035.66Jul 20,028.29 649.26 109,220.80 14,186.15Aug 19,681.12 660.00 113,820.51 17,302.75Sep 20,431.12 1,052.24 118,199.32 16,688.59Oct 20,271.26 1,330.63 120,192.62 12,264.51Nov 20,944.72 381.22 224,176.73 10,563.02Dec 21,520.58 148.12 397,967.17 11,092.92

2003 Jan 22,228.12 513.92 397,967.17 17,597.60Feb 22,228.12 640.55 397,987.37 17,368.72Mar 22,339.62 389.49 388,499.54 17,456.94Apr 22,704.49 391.00 390,746.34 21,506.16May 23,758.49 896.00 391,238.29 29,635.75Jun 28,392.28 2,943.35 385,036.84 45,609.81Jul 35,842.03 3,418.85 385,036.84 7,347.41Aug 35,863.03 957.64 385,036.84 5,000.48Sep 35,963.03 660.79 385,036.84 6,558.29Oct 39,584.03 865.65 385,036.84 11,245.57Nov 39,824.03 1,255.87 385,036.84 7,379.00Dec 45,599.03 1,420.26 389,909.79 3,752.25

2004 Jan 45,606.21 1,256.76 384,655.48 59,424.49Feb 45,528.73 1,131.53 384,655.48 48,159.98Mar 47,319.79 1,862.68 388,342.60 51,666.44Apr 48,239.64 2,027.03 392,609.51 42,196.74May 49,250.66 1,301.29 384,885.22 40,480.53Jun 50,486.62 979.78 385,513.39 32,812.21Jul 53,613.50 1,359.94 386,586.54 41,258.20Aug 53,335.02 1,323.52 394,386.98 42,824.18Sep 53,652.76 1,375.05 391,250.06 37,916.24Oct 57,013.82 1,572.05 400,624.91 30,116.28Nov 58,620.45 1,363.40 401,164.79 38,090.52Dec 61,800.20 1,794.28 399,304.20 48,042.86

2005 Jan 58,363.24 3,383.50 404,767.83 58,513.84Feb 59,457.16 1,117.63 408,236.43 44,953.79Mar 58,379.69 1,553.45 408,714.40 56,643.47Apr 59,123.56 3,743.95 409,249.03 76,050.59May 59,171.99 871.25 400,186.96 41,569.09Jun 61,390.15 969.43 404,985.12 39,843.48Jul 65,524.07 1,328.10 404,985.12 8,277.70Aug 63,770.94 1,665.97 404,985.12 7,478.03Sep 63,570.94 3,424.48 406,545.12 15,341.36Oct 63,295.94 3,517.45 405,466.12 7,354.02Nov 63,230.94 1,025.88 401,416.31 896.81Dec 62,830.94 4,497.30 389,507.56 7,548.31

2006 Jan 62,955.94 1,457.69 405,709.31 3,263.04Feb 62,630.94 1,988.92 395,711.88 2,722.09Mar 63,435.64 921.35 399,962.13 3,023.57Apr 61,935.64 907.22 403,212.13 1,929.08May 63,780.64 655.40 404,512.13 1,896.31Jun 63,066.66 934.55 407,292.96 5,322.53

Listed Bonds Volume Listed Bonds VolumePeriod

Corporate Bonds Government Bonds

Millions of Rp

38a


Table - Appendix 5Indicators of Mutual Funds

2002 Jan 8.53 4.91 0.54Feb 11.54 7.81 0.52Mar 13.89 9.78 0.54Apr 14.80 10.35 0.59May 16.50 11.50 0.60Jun 17.89 12.69 0.58Jul 24.59 18.98 0.56Aug 29.93 23.82 0.54Sep 35.69 28.88 0.28Oct 41.02 33.04 0.26Nov 44.35 35.40 0.27Dec 46.61 37.34 0.30




2006 Jan 27.60 13.46 4.26Feb 26.20 13.69 4.16Mar 28.11 13.4 3.91Apr 28.92 14.31 4.01May 29.74 13.79 4.61Jun 33.06 13.26 4.71

Net Asset Value Fixed Income EquityPeriod

Trillions of Rp

39a


Table - Appendix 6.AIndicators of Corporate Sector

2002 Q 1 112.27 13.71 43.03 12.88Q 2 227.67 17.02 41.00 24.22Q 3 345.42 21.00 32.04 26.91Q 4 455.66 18.39 29.06 12.19

2003 Q 1 84.01 12.76 29.17 19.51Q 2 206.85 14.43 31.01 13.30Q 3 251.07 20.53 32.25 5.06Q 4 236.84 25.65 28.59 9.55

2004 Q 1 74.66 17.52 33.28 11.61Q 2 135.31 24.88 34.12 10.85Q 3 272.53 27.62 35.54 11.79Q 4 375.56 33.65 43.27 12.06

2005 Q 1 101.56 21.24 40.84 23.16Q 2 216.57 23.80 39.09 28.80Q 3 333.50 20.34 24.36 22.18Q 4 262.43 16.30 31.46 44.76

2006 Q 1 130.83 15.43 36.65 23.44Q 2 NA 17.76 36.77 15.78

Business Prospect Expectation of Business Expectation ofin 3 Months Prospect in 6 Months to Come Sales Price

(%, net balance) (%, net balance) (% SBT)

Period Earning Before Tax(Millions of Rp)

40a


Table - Appendix 6.BIndicators of Corporate Sector

Estimation of Commercial Price Estimation of Commercial Price in 6 Months to Come in 3 Months to Come

(% SBT) (% SBT)Period

2003 Jan 135.75 143.69Feb 125.23 125.11Mar 134.86 129.09Apr 134.70 134.39May 124.42 120.09Jun 122.48 119.11Jul 129.38 119.35Aug 130.84 125.79Sep 107.42 115.44Oct 115.28 128.57Nov 111.50 122.30Dec 111.95 116.74



2006 Jan 130.74 138.95Feb 132.81 121.79Mar 140.54 125.84Apr 131.80 115.36May 130.94 123.45Jun 139.22 127.12

41a


Table - Appendix 7Household Indicators





2006 Jan 74.26 102.61 88.44Feb 74.96 95.19 85.08Mar 78.42 103.33 90.87Apr 73.08 102.67 87.88May 74.14 102.17 88.16Jun 76.81 105.42 91.12

Current Economy Consumer Expectation Consumer Confidence IndexPeriod

42a


Table - Appendix 8Indicators of Macroeconomy

SBI, 1 Month Inflation Rate BI Rate USD Exchange Rate(%) (%) (%) (Rp)

Period

2002 Jan 16.93 14.42 - 10,313Feb 16.86 15.13 - 10,151Mar 16.76 14.08 - 9,825Apr 16.61 13.30 - 9,330May 15.51 12.93 - 8,830Jun 15.11 11.48 - 8,713Jul 14.93 10.05 - 9.065Aug 14.35 10.60 - 8,855Sep 13.22 10.48 - 9.000Oct 13.10 10.33 - 9,215Nov 13.06 10.48 - 8,978Dec 12.93 10.03 - 8,950

2003 Jan 12.69 8.74 - 8,870Feb 12.24 7.34 - 8,884Mar 11.40 7.12 - 8,902Apr 11.06 7.54 - 8,675May 10.44 6.91 - 8,310Jun 9.53 6.62 - 8,275Jul 9.10 5.79 - 8,510Aug 8.91 6.38 - 8,485Sep 8.66 6.20 - 8,395Oct 8.48 6.22 - 8,497Nov 8.49 5.33 - 8,505Dec 8.31 5.06 - 8,420

2004 Jan 7.86 4.82 - 8,457Feb 7.70 4.60 - 8,453Mar 7.42 5.11 - 8,564Apr 7.33 5.92 - 8,705May 7.32 6.47 - 9,268Jun 7.34 6.83 - 9,400Jul 7.36 7.20 - 9,130Aug 7.37 6.67 - 9,370Sep 7.39 6.27 - 9,155Oct 7.41 6.22 - 9,088Nov 7.41 6.18 - 9,000Dec 7.43 6.42 - 9,270

2005 Jan 7.42 7.32 - 9,161Feb 7.43 7.15 - 9,285Mar 7.44 8.81 - 9,465Apr 7.70 8.12 - 9,570May 7.95 7.4 - 9,518Jun 8.25 7.42 - 9,760Jul 8.49 7.84 8.5 9,805Aug 9.51 8.33 9.5 10,300Sep 10.00 9.06 10 10,300Oct 11.00 17.89 11 10,123Nov 12.25 18.38 12.25 10,025Dec 12.75 17.11 12.75 9,830

2006 Jan 12.92 17.03 12.75 9,370Feb 12.92 17.92 12.75 9,183Mar 12.73 15.74 12.75 9,070Apr 12.74 15.4 12.75 8,785May 12.50 15.6 12.5 9,255Jun 12.25 15.53 12.5 9,263

43a


Matrix ofFinancial Sector Policy Package

I. FINANCIAL SYSTEM STABILITY

II. BANKING INSTITUTIONS

III. NON BANK FINANCIAL INSTITUTIONS

IV. CAPITAL MARKET

V. OTHERS

44a

Glossary, Abbreviation, AppendixI.

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and

per

form

ance

4. E

nsur

e co

mm

itmen

ts o

f th

eA

ug-0

6M

inist

ry o

f Sta

te O

wne

d En

terp

rise

man

agem

ent

of s

tate

-ow

ned

bank

s to

boo

st g

over

nace

m r

isk

man

agem

ent a

nd re

duci

ngim

paire

d lo

ans

No

.Po

licy

Pro

gra

mA

ctio

nD

ead

line

Au

tho

rity

In C

har

ge

46a


Impr

ove

regu

latio

n of

"kn

ow y

our

cust

omer

" on

non

-ban

king

finan

cial

inst

itutio

n (a

nti m

oney

laun

derin

g pr

ogra

m)

Con

sum

er p

rote

ctio

n an

dem

pow

erm

ent

1.M

anag

emen

t of u

nhea

lthy

insu

ranc

e co

mpa

nies

2.Im

prov

e th

e qu

ality

and

efec

tivity

of i

nsur

ance

regu

latio

n an

d su

perv

isory

3.Pr

otec

tion

of in

sura

nce

hold

er

4.En

hanc

e th

e qu

ality

of d

irect

ors

and

com

issio

ners

as

wel

l as

mar

ket p

laye

r

5.Ta

x in

cent

ive

for

deve

lope

r of

insu

ranc

e in

dust

ry

1.D

evel

opm

ent o

f pen

sion

fund

indu

stry

2.En

hanc

emen

t of

regu

latio

n an

dsu

perv

isio

n qu

ality

1.St

reng

then

ing

mul

ti fin

ance

indu

stry

2.St

reng

then

ing

vent

ure

capi

tal

indu

stry

Am

endm

ent

the

Min

istry

of

Fina

nce

Dec

ree

No.

45/

KMK.

06/2

003

ofim

plem

enta

tion

of "

know

you

rcu

stom

er"

on n

on b

ank

finan

cial

inst

itutio

n

Enha

nce

tran

spar

ency

on

non

bank

finan

cial

inst

itutio

n pr

oduc

tsin

form

atio

nD

evel

op s

trat

egy

man

agem

ent

for

unhe

alth

y in

sura

nce

com

pani

es,

incl

. cle

ar a

nd c

onsis

tent

exi

t pol

icy

Impl

emen

tatio

n of

exi

t po

licy

Enha

nce

the

amen

dmen

t of

UU

No.

2/19

92 o

n in

sura

nce

activ

ities

Seco

nd a

men

dmen

t on

gove

rnm

ent

rule

s N

o.73

/199

2En

cour

age

impl

emen

tatio

n of

med

iatio

n ag

ency

in in

sura

nce

indu

stry

Impl

emen

tatio

n of

Fit

and

Prop

erTe

st fo

r Dire

ctor

s an

d C

omiss

ione

rsof

insu

ranc

e co

mpa

nies

Ack

now

ledg

emen

t of c

laim

pai

d by

life

insu

ranc

e as

a s

ubtr

acta

ble

fee

from

Prep

are

road

map

of

pens

ion

fund

indu

stry

1. P

repa

re G

CG

for p

ensio

n fu

ndin

dust

ry2.

Issu

e re

gula

tion

conc

erni

ngre

port

ing

and

supe

rvisi

ng p

ensio

nfu

nd fo

r civ

il se

rvan

ts

Stre

ngte

ning

cap

ital s

truc

ture

,qu

ality

of s

uper

visio

n an

dex

amin

atio

n of

mul

ti fin

ance

com

pani

es

Stre

ngte

ning

cap

ital s

truc

ture

,qu

ality

of s

uper

visio

n an

dex

amin

atio

n of

ven

ture

cap

ital

com

pani

es

III. N

ON

BA

NK

ING

FIN

AN

CIA

L IN

STIT

UTI

ON

1En

forc

emen

t of

prin

cipl

e of

"K

now

Your

Cus

tom

er"

to n

on-b

anki

ngfin

anci

al in

stitu

tion

2st

reng

then

ing

non

bank

fin

anci

alin

stitu

tion

3St

reng

then

ing

insu

ranc

e in

dust

ry

4St

reng

then

ing

pens

ion

fund

indu

stry

5St

reng

then

ing

mul

ti fin

ance

indu

stry

No

.Po

licy

Pro

gra

mA

ctio

nD

ead

line

Au

tho

rity

In C

har

ge

Aug

-06

Sept

200

6-on

war

ds

Aug

-06

Nov

200

6 -

onw

ards

Mar

-07

Dec

-06

Sep-

06

Dec

200

6-on

war

ds

Sep

2006

-onw

ards

Dec

-06

Dec

-06

Sep-

06

Oct

-06

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ceM

inist

ry o

f Fin

ance

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

47a


IV. C

API

TAL

MA

RK

ET

1D

evel

opm

ent

of C

apita

l Mar

kets

2.D

evel

opm

ent o

f gov

ernm

ent b

ond

mar

kets

3.St

reng

then

ing

mut

ual f

und

indu

stry

No

.Po

licy

Pro

gra

mA

ctio

nD

ead

line

Au

tho

rity

In C

har

ge

1.Bo

ost

com

petit

iven

ess

and

effic

ienc

y of

the

bour

ses

2.En

hanc

ing

qual

ity o

f sup

ervi

sion

and

regu

latio

n

3.Im

prov

e th

e ap

plic

atio

n of

ICT

inth

e ca

pita

l mar

ket

4.D

evel

op s

econ

dary

mar

kets

of

debt

sec

uriti

es

5.D

evel

op c

olle

ctiv

e in

vest

men

tba

sed

prod

ucts

6.D

evel

op le

gal f

ram

ewor

kd f

orfa

cilit

atin

g Isl

amic

cap

ital

mar

kets

7.Ta

x in

cent

ives

for

dev

elop

men

tof

cap

ital m

arke

ts

Expa

ndin

g th

e ba

se o

f inv

esto

rs

Enha

cem

ent o

f acc

ount

abilt

y an

dsu

perv

isio

n

1.M

ergi

ng JS

E an

d SS

E2.

Impl

emen

t re

mot

e tr

adin

g

Enha

nce

the

regu

latio

n of

cap

ital

mar

ket a

ccor

ding

to th

e RO

SC

Impl

emen

t e-

repo

rtin

g, e

-lice

nsin

g,e-

regi

stra

tion,

and

e-m

onito

ring

1.D

evel

op p

rice

disc

over

ym

echa

nism

2.En

hanc

e ET

P3.

Dev

elop

bon

d re

po m

arke

t4.

Esta

blis

h pr

imar

y de

lers

for

gove

rnm

ent

bond

s5.

Stre

ngth

en in

fras

truc

ture

for

gove

rnm

ent

bond

mar

ket

Dev

elop

Exc

hang

e Tr

aded

Fun

ds

1.Re

gula

ting

the

impl

emen

tatio

n of

syar

iah-

base

d pr

insip

le in

the

capi

tal m

arke

t2.

Sett

ing

up t

he a

ccou

ntin

gpr

inci

ples

in th

e lig

hts

of th

eim

plem

enta

tion

of s

yaria

h ba

sed

prin

cipl

e in

the

capi

tal m

arke

t

Elim

inat

ion

of o

blig

ator

y fic

al le

tter

for

com

pani

es p

lann

ing

to is

subo

nds

and

stoc

ks

1.Is

suan

ce o

f re

tail

gove

rnm

ent

bond

s2.

Issu

ance

of s

yaria

h ba

sed

inst

rum

ents

1.Im

prov

emen

t of r

egul

atio

nsco

ncen

ring

selli

ng a

gent

of

mut

ual f

unds

2.Se

ttin

g th

e re

gula

tions

conc

erni

ng s

ellin

g ag

ent

ofm

utua

l fun

ds

Oct

-06

Oct

-06

Oct

200

6 - o

nwar

ds

Jun-

07

Sep-

06N

ov-0

6D

ec-0

6

Aug

-06

Dec

-06

Dec

-06

Dec

-06

Aug

-06

Aug

-06

Oct

-06

Aug

-06

Aug

-06

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ce

Min

istry

of F

inan

ceBa

nk In

done

siaM

inist

ry o

f Fin

ance

Min

istry

of

Fina

nce

and

Bank

Indo

nesi

a

Min

istr

y of

Fin

ance

Min

istr

y of

Fin

ance

Min

istr

y of

Fin

ance

Min

istr

y of

Fin

ance

Min

istr

y of

Fin

ance

Min

istr

y of

Fin

ance

Min

istr

y of

Fin

ance

Min

istr

y of

Fin

ance

48a

Glossary, Abbreviation, AppendixV.

OTH

ERS

1D

evel

opm

ent

of E

xpor

t Fi

nanc

ing

2.Pr

ivat

isat

ion

of s

tate

ow

ned

com

pani

es

No

.Po

licy

Pro

gra

mA

ctio

nD

ead

line

Au

tho

rity

In C

har

ge

1. E

stab

lishm

ent

of E

xpor

tFi

nanc

ing

Age

ncy

Dev

elop

men

t of i

nstit

utio

nal

stru

ctur

e fo

r pr

ivat

isatio

n

Sett

ing

the

draf

t la

w c

once

rnin

g th

eEx

port

Fin

anci

ng A

genc

y

1.Es

tabl

ishm

ent o

f Priv

atis

atio

nC

omm

ittee

2.D

evel

opm

ent o

f priv

atis

atio

nst

rate

gy fo

r sho

rt a

nd m

ediu

mte

rm

Dec

-06

Aug

-06

Nov

-06

Min

istry

of F

inan

ce

Coo

rdin

atin

g M

inist

er o

f Ec

onom

y

Min

istry

of S

tate

Ow

ned

Ente

rpris

e

Bank Indonesia, Financial Stability Review No 6 - March 2006

Documents

Transcript of Bank Indonesia, Financial Stability Review No 6 - March 2006