2012.T1.c Foundations

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2012 FRM Foundations 1c (3rd/3)

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• Published Mar 10, 2012

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Foundations 1.c Agenda (order of study guide)

• CAS – Overview of Enterprise Risk Management

• Steve Allen, Financial Disasters, Chapter 4 (Case Studies)

• René Stulz, “Risk Management Failures: What are They and When Do They Happen?”

2012 FRM Foundations 1.c.

2


Casualty Actuarial Society, Enterprise

Risk Management Committee – Overview

of Enterprise Risk Management

3


Describe what is meant by ERM.

2012 FRM Foundations 1.c Risk Management Committee , Overview

4

“ERM is the discipline by which an organization in any industry assesses, controls, exploits, finances, and monitors risks from all sources for the purpose of increasing the organization’s short- and long-term value to its stakeholders.”


Identify and describe risks addressed by ERM.


• ERM Framework

5

Establish Context

Identify Risks

Analyze/Quantify Risks

Integrate Risks

Assess/Prioritize Risks

Treat/Exploit Risks

Monitor & Review

Risk Types

Hazard

Natural disaster

Theft

Liability claims

Financial Operational Strategic

Reputational

Competition

Demographic trends

Technological innovation

Regulatory & Political trends

Not operational risks!




6

Hazard Risks include risks from:

• Fire and other property damage,

• Windstorm and other natural perils,

• Theft and other crime, personal injury,

• Business interruption,

• Disease and disability (including work-related injuries and diseases), and

• liability claims.




7

Financial Risks include risks from:

• price (e.g. asset value, interest rate, foreign exchange, commodity),

• Liquidity (e.g. cash flow, call risk, opportunity cost),

• Credit (e.g. default, downgrade)

• Inflation/purchasing power, and

• Hedging/basis risk




8

Operational Risks include risks from:

• Business operations (e.g., human resources, product development, capacity, efficiency, product/service failure, channel management, supply chain management, business cyclicality),

• Empowerment (e.g., leadership, change readiness),

• Information technology (e.g., relevance, availability), and

• Information/business reporting (e.g., budgeting and planning, accounting information, pension fund, investment evaluation, taxation).

„




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Strategic Risks include risks from:

• Reputational damage (e.g., trademark/brand erosion, fraud, unfavorable publicity)

• Competition,

• Customer wants,

• Demographic and social/cultural trends,

• Technological innovation,

• Capital availability, and

• Regulatory and political trends.


Describe the measures … used within an ERM

framework.

Solvency-related metrics

• Concentrate on the “adverse tail” of the probability distributions

• Relevant for determining economic capital (EC) requirements

Performance-related metrics

• Concentrate on the mid-region of the probability distribution

• Relevant to owners and their proxies


10



framework.


11

Probability of ruin:

The percentile of the probability distribution corresponding to the point at which capital is exhausted.

• Typically, a minimum acceptable probability of ruin is specified, and economic capital is derived therefrom.



framework.


12

Shortfall risk:

The probability that a random variable falls below some specified threshold level.

• Probability of ruin is a special case of shortfall risk in which the threshold level is the point at which capital is exhausted.



framework.


13

Value at risk (VaR):

The maximum loss an organization can suffer, under normal market conditions, over a given period of time at a given probability level

• Technically, the inverse of the shortfall risk concept, in which the shortfall risk is specified, and the threshold level is derived therefrom.

• VaR is a common measure of risk in the banking sector, where it is typically calculated daily and used to monitor trading activity.



framework.


14

Expected policyholder deficit (EPD) or Economic cost of ruin (ECOR):

Enhancement to probability of ruin concept (and thus shortfall risk and VaR) where severity of ruin also reflected.

• Technically, the expected value of the shortfall. (In an analogy to bond rating, comparable to considering the recovery in addition to the probability of default.)

• For insurance companies, the more common term is EPD, and represents the expected shortage in the funds due to policyholders in the event of liquidation.



framework.


15

Tail Value at Risk (Tail VaR) or Tail Conditional Expectation (TCE):

an ECOR-like measure in the sense that both the probability and the cost of “tail events” are considered. It differs from ECOR in that it is the expected value, from first dollar, of all events beyond the tail threshold event, not just the shortfall amount.



framework.


16

Performance-related metrics:

• Variance: average squared difference between a random variable and its mean.

• Standard deviation: square root of the variance.

• Semi-variance and downside standard deviation: only unfavorable deviations from a specified target level are considered in the calculation.

• Below-target-risk (BTR): expected value of unfavorable deviations of a random variable from a specified target level (such as not meeting an earnings target).


Describe the models … typically used within an

ERM framework.


• “As a practical matter, the choice of modeling approach is typically between statistical analytic models and structural simulation models”

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Rating agency models

RBC

Some option pricing models

DFA

Analytical

Simulation

Statistical Structural


Describe the models … typically used within an

ERM framework.


• Continuum of model methods: from “objective” data to experts

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Historical Data Analysis

Empirical distributions

Extreme value theory (EVT)

Regressions

Combination

System dynamics simulation

Fuzzy logic

Expert Input

Preference among bets

Judgments of Relative Likelihood

Influence diagram

Delphi Method


Describe the … tools typically used within an ERM

framework.


19

Generic applications

• Optimization: formal process by which decisions are made under conditions of uncertainty

• Candidate analysis: a restricted form of optimization analysis in which only a finite number of prespecified decision options are considered



framework.


20

Capital management

• Capital adequacy: minimum needed to satisfy economic capital (EC) constraint

• Capital structure: optimal mix

• Capital attribution: assignment by risk (denominator of RAROC)

• Capital allocation: actual deployment to business segments



framework.


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Performance measurement

Investment strategy/asset allocation

Insurance/reinsurance/hedging strategy optimization

Crisis management

Contingency planning

Business expansion/contraction strategy

Distribution channel strategy

Strategic planning


Discuss practical considerations related to ERM

implementation.


22

Designating an ERM “Champion”

Given implementation challenges, a “champion” is needed to spearhead the ERM effort

• Role often fulfilled by Chief Risk Officer (CRO), who typically reports to the CEO or CFO

• Organizational structure created for ERM (e.g., the CRO, the CRO’s staff, the Risk Management Committee) must have the authority to be a change agent.

• Needs senior sponsorship



implementation.


23

Making ERM part of the enterprise culture (“tearing down the silos”)

Under the historical, fragmented approach to risk management, numerous personnel are involved in various aspects of risk management.

Successful ERM coordinates all these different departments, recognizes the need for education, but allows for individual department initiative, flexibility, and autonomy.



implementation.


24

Determining all possible risks of the organization

A multitude of risks face every enterprise. Often the greatest risks are those not contemplated.

Some organizations use their risk management committees to conduct and participate in periodic, structured “disaster scenario” brainstorming exercises specifically to contemplate and, as appropriate, plan for such “unthinkable” events.



implementation.


25

Quantifying operational and strategic risks

Operational and strategic risk are hard to parameterize: point estimates of likelihoods (frequency), consequences (severity), and probability distributions.

Enterprises can start with qualitative analysis to determine those that are material and to prioritize them. In addition, some advocate the use of causal models, as opposed to parametric models, to quantify these risks.



implementation.


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Integrating risks (determining dependencies, etc.)

Build structural models in modular form, which allows enhancement in manageable successive stages over time. This overcomes the following difficulties:

• Past causal relationships are often not indicative of future relationships.

• Differences in time frames (short-term, medium-term, long-term) to consider.

• Selecting correlation factors becomes cumbersome as the number of risks to review increases.



implementation.


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Lack of appropriate risk transfer mechanisms

Insurance, reinsurance and capital markets are not complete; i.e., not able to provide all products and services.

These markets need to continue to evolve over time (such as the development of the alternative risk market for hazard risks) in order to provide products that will meet the risk transfer needs of enterprises.

• Risk transfer mechanisms for operational and strategic risks are even less mature.



implementation.


28

Monitoring the Process

Ideally, ERM is not a one-time “project”, but a discipline that evolves over time as risks and opportunities within an enterprise change.

The successful ERM process will include regular progress reports and comparisons to previous risk assessments so changes and refinements can be made as appropriate. Regularly monitoring results can, and should, be tied to the time scales identified for the risks actively managed.



implementation.


29

Start Slowly - Build Upon Successes

Because of the traditional, fragmented approach to risk management described earlier and the complexity of many businesses, enterprises often find it useful to start their

ERM initiative slowly, tackling smaller projects first, so tangible results can be achieved early.


Allen, Chapter 4:

Financial Disasters


Describe the key factors that led to and the lessons

learned from the following risk management case studies:

• Chase Manhattan & Drysdale Securities

• Kidder Peabody

• Barings

• Allied Irish Bank

• Long Term Capital Management (LTCM)

• Metallgesellschaft

• Banker’s Trust

2012 FRM Foundations 1.c Allen, Financial Risk Management: Chapter 4

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Financial Disasters (Case Studies)


32

Misleading Reporting

• Chase/Drysdale

• Kidder Peabody

• Barings

• Allied Irish Bank

Unexpected market moves

• LTCM

• Metallgesellschaft

Conduct of Customer Business

• Banker’s Trust


Chase Manhattan

& Drysdale Securities

• In 1976, Drysdale obtained $300 million in unsecured borrowing

– But only had $20 million in capital

• Lost money on positions.

– Could not repay loans. Drysdale went bankrupt.

• Reputational damage to Chase (and stock price impact)


33

Chase/Drysdale


Chase Manhattan &

Drysdale Securities

Key Factors

• Chase failed to detect the unauthorized positions: Chase did not believe the firm’s capital was a risk.

• Inexperienced managers

• Did not correctly interpret borrowing agreements that made Chase responsible for payments due.

Lessons Learned

• More precise methods required to compute collateral value

• Need process control: new products should receive prior approval “risk function”


34

Chase/Drysdale


Kidder Peabody

• Between 1992 and 1994, Joseph Jett exploited an accounting-type glitch in order to book about $350 million in false profits (government bonds)


35

Kidder Peabody


Kidder Peabody

Key Factors

• System did not present value (PV) forward transactions: allowed booking of artificial profits

• Management did not react to visible suspicions

Lessons Learned

• Investigate a stream of large unexpected profits

• Periodically review models and systems: do assumptions need to be updated?


36

Kidder Peabody


Barings

• During 1993 to 1995, a junior trader (Leeson) took large speculative positions (Japanese stocks, interest rate futures, options) from the Singapore office

– Disguised as safe transactions on behalf of fake customers!

• Losses of ~ 1.25 billion forced Barings into bankruptcy


37

Barings


Barings

• Market risk

– Leeson was short straddles on Nikkei 225. Hoped index would trade in narrow range; planned to pocket premiums. However, after Kobe earthquake (1/1995):

1. Sent index into a tailspin.

2. Earthquake increased volatility (adds value to both calls and puts) which “exploded” the short put options

• Credit risk

– Management of counterparty risk & reporting of specific instrument exposures to counterparties would have been an additional signal


38

Barings


Barings

Key Factors

• Leeson was allowed to settle his own trades

• Management incompetence & poor supervision

• Poor reporting

Lessons Learned

• Absolute necessity of an independent trading back office

• Separation of trading and settlement functions

• Need to make thorough inquiries about unexpected sources of profits and/or cash movements


39

Barings


Allied Irish Bank

• John Rusnak, a currency option trader, entered into massive unauthorized trades from 1997 to 2002, producing losses of $691 million.

– Was supposed to run small arbitrage

– But was disguising large naked positions


40

Allied Irish


Allied Irish Bank

Key Factors

• Similar to Leeson (internal deception)

• Achieved by inventing imaginary trades

Lessons Learned

• Proprietary trading is a high-risk activity

• Risk management architecture is crucial

• Relationship between parent and overseas units needs to be clarified

• Strong and enforceable back-office controls are essential


41

Allied Irish


Long Term Capital Management (LTCM)

• From 1994 to 1998, renowned quants produced spectacular returns with relative value (“arbitrage”-type) trades

• In Summer 1998, series of unexpected and extreme events (e.g., Russian rouble devaluation led to flight to quality)

– New York Fed coordinated a private bailout ($3.65 billion equity investment)


42

LTCM


Long Term Capital Management (LTCM)

Key Factors

• Failure to supplement VaR with a full set of stress test scenarios

• Failure to account for illiquidity of positions during stress

• (Leverage too high?)

• (Too much faith in models?)

Lessons Learned

• Stress scenarios including extreme stresses and interaction between market & credit risk

• Incorporate liquidity

• Initial margin needed if counterparty is trader

• Greater counterparty disclosures


43

LTCM


LTCM: Key factors (con’t)

Model risk #1: Models assumed normal distribution

Model risk #2: Extrapolation of historical returns. Did not anticipate once-in-a-lifetime event

Diversification: Risk models did not handle correlations that spiked during a crisis event

Funding liquidity risk: When firm lost ~ half its value in sudden plunge, lack of equity capital created a cash flow crisis

Market risk: Extreme leverage combined with concentrated market risk—LTCM had a balance sheet leverage of 28-to-1


LTCM

44

LTCM


LTCM: Key factors (con’t)


Transparency and disclosure

Marking to market. “Conflict between hedging strategies and cash requirements”

Transaction types: pairs trading, risk arbitrage, and bets on overall market volatility

Liquidity squeeze: Asian crisis → Brazil devalued its currency → Flight to quality → Spreads increase → Value of LTCM collateral drops → LTCM liquidates to meet margin calls

Insufficient risk management: “underestimated the likelihood that liquidity, credit and volatility spreads would move in a similar fashion simultaneously across markets”

LTCM

45

LTCM


Metallgesellschaft

• MGRM wrote (sold) long-term forward contracts to sell gas/oil

– Hedged with long positions in short-term futures (stack-and-roll hedge)

• As spot oil prices dropped, oil futures curve shifted to contango

– In 1993, creditors rescued with a $1.9 billion package


46

MG


Metallgesellschaft


47

Metallgesellschaft

Basis risk

Liquidity risk

Operational risk

Shift!

MG


Metallgesellschaft

Key Factors

• Stack-and-roll hedge exposes to basis risk

• Shift to contango created losses on roll return

• Accounting standards required recognition of futures losses but not forward gains!

Lessons Learned

• Short-term hedge against long-term contracts requires liquidity

• Uncertainty of roll returns

• Liquidity consideration may favor other than minimum variance hedge


48

MG


Metallgesellschaft: Key Factors (con’t)

1. First factor was that the market shifted to contango (i.e., the futures price is greater than the spot price).

– Greatly increased the cost of the stack-and-roll hedge.

– Led to cash flow (liquidity) problems

2. Second factor was German accounting methods required Metallgesellschaft to show futures losses (i.e., from hedge) but could not recognize unrealized gains from the forward.

– These reported losses triggered margin calls and a panic, which led to credit rating downgrades.


Metallgesellschaft

49

MG


Banker’s Trust (BT)

• To reducing their funding expenses, Proctor & Gamble (P&G) and Gibson Greetings bought complex derivative products offered by BT

• Due to losses (e.g., P&G lost >$100 million in 1994), customers sued BT

– Claimed they were exploited because they were not sophisticated enough to understand their risks


50

BT


Banker’s Trust

Key Factors

• Complex derivatives

• Evidence of some intent to deceive (Discovery evidence)

Lessons Learned

• Better controls for matching complexity of trade with client sophistication

• Need to provision price quotes independent of the front office

• Implications of internal communications that can later be made public


51

BT


René Stulz,” Risk Management

Failures: What are They and

When Do They Happen?


Define the role of risk management …

• To assess risks faced by firm,

• Communicate risks to risk-taking decision-makers

• Manage and monitor risks to ensure firm only bears risks desired by management and board of directors

2010 FRM Foundations 1.c Stulz, “Risk Management Failures”

53

But Board and Management decides to take the risks!


… and explain why a large financial loss is not

necessarily a failure of risk management.

• Hypothetical LTCM Example


Return Probability 99% 25%

1% -70%

Expected 24.05%

“Picking up nickels in front of a steamroller?”

99 years out of 100 they would have earned 25% before fees and would have been stars.

54




• Risk Managers try to know (and communicate) the distribution of possible outcomes

– But they do not decide whether to take the risk

• Assuming risk is a strategic decision based on institution’s risk appetite

– Defining the risk appetite is a decision for the board and top management.

– At the heart of the firm’s strategy – this is how it creates shareholder value


55



56

Strategy Shareholder

value creation

Risk appetite

• Risk Management informs




• “the partners of LTCM knew the risks and the rewards from doing so. In the well-worn language of financial economics, increasing leverage was a positive NPV decision when it was made [ex ante], but obviously ex post it was a costly decision as it meant that when assets fell in value, the fund’s equity fell in value faster than it would have with less leverage.”


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58

Measure risks • Mismeasurement of known risks.

• Failure to take risks into account.

Communicate • Failure in communicating the risks to

top management

Manage

• Failure in monitoring risks.

• Failure in managing risks.

• Failure to use appropriate risk metrics.

Describe how risk management can fail


Describe how risk can be mismeasured.

• Distribution – Select the wrong distribution

– Specify the distribution incorrectly

• Dependencies (correlations) may be mis-measured

• Using and applying the data – Historical sample does not apply

– No sample (“with the subprime crisis, there was no historical data of a downturn in the real estate market during which a large amount of securitized subprime mortgages was outstanding.”)


59


Explain how a firm can fail to take known and unknown

risks into account in making strategic decisions.

1. A firm may ignore a risk even though that risk is known.

2. Somebody in the firm knows about a risk, but that risk is not captured by the risk models.

3. Realization of a truly unknown risk


Risk divisions (typology) can contribute to ignored risks: • Credit vs. market vs. operational risk are

“partly artificial and partly motivated by regulations.” • Trading books (market to market) versus credit book (accrual).

60


Explain the importance of communication in

effective risk management.

• Risk management has to provide timely information to the board and top management

– Top managers are supposed to maximize shareholder value by assuming risk

– Lack of communication has played a role in the most recent crisis.


61


Describe how firms can fail to correctly monitor and manage risk on an ongoing basis

• For a financial firm, risks can change sharply even if the firm does not take new positions.

– Complex positions with derivatives

– Challenging to capture these changes and adjust

• Important for risk manager to identify possible solutions that can be implemented quickly

– Contingency hedging plans are critical.


62


Explain the role of risk metrics and discuss the

shortcomings of existing risk metrics.

• May not scale over long time horizons

– As usual, historical data samples. Can they be trusted?


63

Can we really scale over time into the future?


Explain the role of risk metrics and discuss the

shortcomings of existing risk metrics.

• Not designed to capture risks associated with crises (catastrophes)

– Summer of 2007 and withdrawal of liquidity. Model may not handle sudden illiquidity


64

Can we really parameterize extreme tail risks? (Taleb)


Explain the role of risk metrics and discuss the shortcomings of existing risk metrics.

• Cannot handle complicated interactions across risks and across institutions

– “Statistical risk models typically take returns to be exogenous to the firm and ignore risk concentrations across institutions”


65

Do we understand complex

interactions/dependencies,

esp. at the systems level?


End of 2012 Foundations 1.c

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