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The Rise & Rise of Forward CurvesThe financial, operational and strategic importance of forward curves underlines that organisations need to ensure that transparent and robust curve management and construction methodologies are in place. These need to be allied with well defined quality assurance practices, stewardship and the business investment necessary to maintain these data assets ... while ensuring regulatory and international accountancy standards compliance.

By Richard Quigley

THE IMPORTANCE OF forward curves cannot be overestated in today’s environment. For organisations engaged in trading activities that facilitate buying or selling of forward goods/services (physical or financial), forward curves are a key decision input. They are vital for mark-to-market, risk exposure assessments, investment decisions, inputs for derivative pricing models, identification of future arbitrage opportunities and trader evaluation strategies.

Equally important to forward curves is the need to ensure a more responsive data infrastructure, with a solid architectural framework that guarantees a flexible and scalable environment in alignment with the ever growing needs of the business. At the same time, there’s the undeniable need to comply with the external political and regulatory challenges that are impacting the use and management of forward curves.

The forward curve has evolved from being relatively unknown a decade or so ago (certainly in the power and gas markets) to become the consummate influential decision making and reporting entity. So what exactly is a forward curve? As Daniel L. Vaughn of ICAP eloquently articulated many years ago, the forward curve is “…..the compilation of prices of actual transactions for forward (future) delivery periods that are executed today”, and whose importance is embedded in their reflection of the current price of a commodity.

Figure 1 (overleaf) graphically depicts a forward curve constructed from the delivery period (tenor points) as at 10 December 2011. These are shown in both relative positions (for instance,. M02, Q03) and absolute (such as Feb12 Q0312 format) for convenience.

Curves such as these are provided or easily constructed from exchanges like ICE or CME, while non-exchange curves are provided or derived from a variety of sources. These include brokers

such as ICAP, Tullet Prebon, Marex Spectron and assessment providers like Platts, Argus and ICIS. However, exchange curves have many advantages over other pricing sources in that they tend to offer strong transparent pricing. They’re also a reliable, regulated source, as well as offering standard product specification. In addition, they generally offer higher liquidity with longer term tradable horizons for many of the products. The combination of these factors gives them a level of transparency and confidence by providing strong observable inputs for fair value accounting (or mark-to-market) and lesser subjectivity.

The counter-balance to exchange traded derivatives (off-exchange or OTC trading commonly used for swaps, forwards and (exotic) options) does not offer the same level of transparency, standardisation or regulation provided by exchange or central counterparties (CCPs). Indeed, these very characteristics (coupled with the high interconnection of large market participants) were a contributing factor to the global financial crisis. As a direct result of this, and the significance of the OTC derivative market in the collapse of Lehman

The forward curve has evolved ... into the consummate influential decision

making and reporting entity

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Brothers and the US government bailout of AIG, targeted regulation has been proposed by the G-20. This involves a strong commitment to establishing regulatory frameworks for OTC derivatives that reduce risk and increase transparency in the OTC market.

In Europe, this takes the form of the European Market Infrastructure Regulation (EMIR). This regulation will mandate central clearing of standard OTC contracts through CCPs, while imposing risk mitigation standards for non-centrally cleared contracts. Examples of current CCPs clearing OTC derivatives include ICE Clear Europe and ICE Trust for CDS.

In addition, more onerous reporting requirements are on the way. The obligation for clearing will be applied to both financial and non-financial counterparties that exceed

certain thresholds. However, commodity participants may be shielded under the ‘non-financial counterparty’ definition by exemptions for genuine hedging “… or providing investment services in commodity or exotic derivatives to clients (of their main business), provided that activity is ‘ancillary’ to their or their group’s main (non-investment/banking services) business.”

Although this legislation was inevitable in the aftermath of the financial crisis, there will be significant financial burdens

on market players. These include new costs and fees, increased regulatory burdens and potential penalties that may strengthen the case for a more staggered pace of introduction to help reduce costs and business interruption. There is little doubt that this legislation is wide-reaching and significant in the day-to-day operations of ‘financial counterparties’, and will impact the mark-to-mark process and end of day Value-at-Risk (VaR) calculations and risk assessments.

The EMIR regulation is awaiting formal approval with a target date of the beginning of 2013, although many industry observers anticipate a delay. It is not by chance that this far reaching EMIR regulation has seen some changes to Fair Value Accounting

Standards that will come into force at the same time.

Fair Value AccountingFair value accounting provides a code of standards and practices

for the measurement of the value of financial instruments on the current price of the asset or liability, for similar assets or liabilities, or based on another objectively assessed ‘fair’ value. The code has been established to provide a rational and unbiased estimation of the value of the commodity, with value changes recognised in the profit or loss. These codes include Financial Accounting Standard 157 – Fair Value Measurements (FAS 157), which details the framework for measuring fair value for firms reporting their financial statements based on US Generally Accepted Accounting Principles (GAAP) and International Accounting Standard (IAS) 39. It also provides

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Figure 1: The Forward Curve & Associated Tenor Points

MO2 MO3 MO4 MO5(May 12)

MO6(Jun 12)

Q03(Q03 12)

Q04(Q04 12)

Y02(2013)

0

100• A curve is built up from a series of values for specific

delivery periods (tenors) • Tenors can represent either an absolute point in time

or a time relative to when the curve was produced

Curve at 10 Dec 2011

(Feb 12) (Mar 12) (Apr 12)

Tenor Curve

Sou

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Dat

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Fair Value AssessmentsA quick glance at some annual accounting statements shows the use

of forward curves in the application of ‘fair value’:– Glencore’s 2011 Annual Accounts Page 113 notes “… fair value is

estimated by reference to forward market prices”.– BP’s recent Quarterly 2012 Group Results, Page 20 notes “…

derivative commodity contract is entered into on a fair value basis using forward prices consistent with the contract maturity”.

– BG Group 2010 Annual Report, Page 33 notes “… BG Group calculates the fair value of medium and long-term debt and derivatives by using market valuations where available or, where not available, by discounting all future cash flows using the relevant market prices and yield curves at the balance sheet date”.

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The objective of using a valuation technique is to estimate the price at which an orderly transaction to sell the asset or to transfer the liability would take place between market participants and the measurement date under current market conditions. IFRS 13 “… seeks to increase consistency and comparability in fair value measurements and related disclosures through a fair value hierarchy.”

The hierarchy categorises the inputs used in valuation techniques into three levels. It gives the highest priority to (unadjusted) quoted prices in active markets for identical assets or liabilities and the lowest priority to unobservable inputs [IFRS 13:72]. IFRS 13 states that; “Fair value is measured using the price in the principal market for the asset or liability (i.e. the market with the greatest volume and level of activity for the asset or liability) or, in the absence of a principal market, the most advantageous market for the asset or liability.”

The actual valuation techniques used to measure fair value encompass the three approaches:

• Market Approach – uses prices and other relevant information generated by market transactions involving identical or comparable (similar) assets, liabilities, or a group of assets and liabilities (e.g. a business).

• Cost Approach – reflects the amount that would be required currently to replace the service capacity of an asset (current replacement cost).

• Income Approach – converts future amounts (cash flows or income and expenses) to a single current (discounted) amount, reflecting current market expectations about those future amounts.

The market approach is the most common approach used in the commodity market and involves a mixture of Level 1 and Level 2 ‘fair value categorisations’, of which Level 2 requires the involvement of ‘bootstrapping’ techniques. This allows the application of synthetic pricing of OTC traded commodities to be formulated from or using market observable data by correlation or other statistical or inference techniques.

However, a change in valuation technique or its application (for example, a change in its weighting when multiple valuation techniques are used or a change in an adjustment applied to a valuation technique) is appropriate if the change results in a measurement that is equally or more representative of fair value in the circumstances. That might be the case if, for example, any of the following events were to take place:

(a) new markets develop;

(b) new information becomes available;

(c) information previously used is no longer available;

(d) valuation techniques improve; or

(e) market conditions change.

Managing ‘Fair Value’ Measurement AssetsYou may have gleaned by now that recording, managing and

declaring ‘fair value’ is not an easy task and comes with the burden of ensuring compliance with international accountancy obligations and regulatory frameworks (such as EMIR in Europe and the US Dodd-Frank).

the principles for recognising and measuring financial instruments for firms that report their financial statements under the International Financial Reporting Standards (IFRS). From 1st January 2013, IFRS 13 (Fair Value Measurement) will be firmly established as the single source of guidance for fair value measurement.

This will ensure the alignment of definition and meaning of fair value and the same disclosure requirements about fair value measurements for US GAAP and IFRS.

As stated by IFRS; “IFRS 13 provides clear and consistent guidance for measuring fair value and addressing valuation uncertainty in markets that are no longer active. It also increases the transparency of fair value measurements by requiring detailed disclosures about fair values derived using models” [our emphasis].

As noted in KPMG’s excellent June 2011 paper on IFRS 13, they “… seek to reduce the subjectivity of these measurements by requiring the relevant observable inputs to be maximised and the unobservable inputs minimised.”

IFRS 13 Valuation TechniquesIFRS 13 requires companies to

disclose information about the valuation techniques and inputs used to measure fair value, as well as information about the uncertainty inherent in fair value measurements (which was of particular concern during the global financial crisis).

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Table 1: IFRS 13 The Fair Value Hierarchy

Level 1

Quoted prices in active markets for identical assets and liabilities. Level 1 inputs must be used without adjustment whenever available.

Level 2Inputs not included within Level 1 that are observable for the asset or liability, either directly or indirectly.

Level 3

Unobservable inputs, including the entity’s own data, which are adjusted if necessary to reflect market participants’ assumptions.

Source: IFRS

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Although many companies – large and small – perform their curve construction and management within an Excel environment, the use of such a medium has its issues. They are difficult to maintain with overly complex formulae to account for rollover and holiday calendars; different asset class quotation periods are required; there is a lack of audit traceability and stewardship management; and there’s a lot of manual intervention, onerous data manipulation, lack of data version control, and inadequate data licence control and traceability. It is thus difficult for any COO or senior risk manager to defend their decision to spend large sums of money on a new E/CTRM system, while retaining Excel as the key analysis and curve management tool in today’s accounting and regulatory environment.

Getting the Architecture RightFigure 2 details the data management

architectural framework. This provides the flexibility for managing all types of data in the commodity enterprise as a precursor to the construction, management and control of the forward curves.

If you use industry leading development and integration technologies (as well as an agnostic database system, application server and operating system), this kind of framework will no doubt offer long-term benefits and maximum flexibility and scalability. There are, of course, many things to consider for an organisation to achieve this outcome. For instance, does the current internal system warrant further investment to realign the business expectations, or is it better to look outside to a specialist supplier of data management and curve applications and services? There is no easy answer here. There may be very strong arguments on both sides for ‘buy versus build’, which would include discussions on the time to market, migration costs, software costs, maintenance, service reaction time, enhancements input and timeliness, reliability, team knowledge, etc. This information needs to be processed and analysed in a systematic way with a non-biased agenda to ensure the right decision for the company.

Having this ‘controlled framework’ in place – that is to say, the right data management framework strengthened by good data management and stewardship practices – supplies the backbone and integrity to provide the level of confidence in the market

observable forward curve data. However, under a Level 2 fair value hierarchy and using a Market Approach Valuation technique, the fair value measurement input data is somewhat more complex. There are many things to consider for the

construction methodology alone, notwithstanding all the other complexities of managing curves. These are determined by the type of commodity, curve frequency (and resolution), market liquidity, comparable commodities, vendor quotations, seasonality, storage, transportation, etc. There are no

Having the right agile data management platform in place allows the full complement of services to be harnessed

during the curve build and management processes

Figure 2: Agile Data Management High Level Architecture

SOAP Web Service Client

.NET JAVA VBA C++

Presentation Layer

Reference Data Time-Series Data Transaction Data

Persistence Layer

SOAP/HTTP/REST

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JDBC

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Message Queue(JMS Service Provider)

Database Database Database

Scheduling

Business Rules

Source: DataGenic

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purpose-build application that addresses the specific areas and requirements relating to forward curves.

Additionally, the application needs to be highly configurable to account for the many input parameters and rich metadata

information that are used in the build process and curve management. Examples include the curve methodology, the fair value hierarchy and target application. Table 2 offers some guidelines to the attributes and example descriptions that are necessary for a robust and automated curve build process.

With the agile data management structure that is now in place (Figure 2) and the associated processes and controls, the curve building application and framework provides the structured management of all curves, methodologies and real-time process transparency, while allowing flexibility to change and adapt the curve construction. This is key to ensuring regulatory compliance, and ease of reporting with measured and controlled ‘fair value’ valuations and practices. Other key benefits include:

• Transparency – The use of a rules system allows you to break the problem down into distinct conditions. This has the effect of making the logic more understandable to other people.

• Key Person Dependency – The fact that you have increased transparency means that you can mitigate the centralisation of curve building knowledge across a wider pool of persons.

• Standardised Logic – Rule formation is standardised, so the rules themselves become standardised, as opposed to writing applications with no standards.

• Direct Relationship with Knowledge – The rules can be written in a ‘natural’

‘one-size-fits-all’ scenarios, as each curve is specific to the OTC instrument and its particular characteristics, although having the right framework allows reusability of curve libraries.

So how do you address the complexities of curves within an application framework and what are the key requirements for curve building and management? Having the correct agile data management platform in place allows the full complement of services to be harnessed during the curve build and management processes (for instance, validation, business process management, date and process dashboard, etc.). However, there is no replacement for a targeted

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Table 2: Forward Curve Attributes

Curve Attribute Example Description

Name Curve Name

Description Full curve description

Curve Methodology Rules

Hierarchy Level 2

Frequency The frequency (resolution) of the curve

Segmentation Used for power curves, e.g. Peak, Base, Off-Peak

Segmentation Delivery N/A (e.g. for Peak this may be 07.00:18:00)

Unit Type Price

Unit of Measure US$/MT (this may be different to input prices)

Decimal Places Can use round-up/round-down

ObservationCan select from any observatione.g. settlement, high, open, low, mid

CommodityThe instrument commodity groupe.g. Crudes, Natural Gas, Power

Conversion: Density User defined or use Vendor factors

Quoting Calendar Defined cal

Rollover Calendar ICE_BRENT_ROLL

Primary Source: ICE

Alternative Source 1 NYMEX

Alternative Source 2 Platts

Workflow MethodEvent (on data update). This could equally be on a scheduled time

Alert NotificationEmail (could be tray alert, or workflow task completion)

Notification Distribution all@risktrading.com

Notification Message Curve completed.

Export Yes

Export Format Excel

Export Workflow WFBootstrap1

Target Application CTRM

Target Application Identifier CTRMABC123

The Key Characteristics of Forward Curve Construction System

– Commodity agnostic– Rules-based (or other AI) curve modelling & library– Ease of rule change & adoption– Curve testing facility– Curve validation– Scheduling– Lifecycle automation– End-to-end process monitoring & alerts– Back testing to ensure model integrity– Curve methodology & curve data versioning– Curve visualisation

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language, such as English. You therefore start writing the logic and then translate to rules, which can easily be referred back to the original knowledge.

• Centralised Knowledge Base – All the rules and libraries are server based, so they are accessible and usable by anyone (they are also automatically kept up to date with the latest versions).

• Collaboration – Curve building logic does not need to be dealt with in isolation – many people can contribute to the library.

ConclusionsThe relevance and importance of forward

curves to today’s trading organisations has never been greater. The newly established regulatory framework for OTC derivatives in Europe (EMIR) will have a profound impact on the marketplace, especially for the ‘financial counterparties’. This regulation mandates that standard OTC contracts are traded through CCPs and that risk mitigation standards are in place for non-centrally cleared contracts. Among other things, these require a re-working of the mark-to-market process, including the market inputs, forward curve compilations, data validation, transactional reference, data retention and revised risk management practices, as well as a review of their stewardship and management. The same is true in a number of other jurisdictions.

In addition, the International Accounting Standards body has provided updated guidelines to its ‘fair value’ techniques and reporting considerations (IFRS 13). Once again, this comes into effect at the beginning of 2013, which is no coincidence.

The challenge to organisations is to ensure compliance at a reasonable cost, while providing the flexibility needed in this increasingly complex regulatory framework when tough market conditions prevail. Excel is certainly not the answer. It requires

a more structured approach to the complexities of data and curve management, which can align with the organisation’s daily processes, while offering new and improved methods of operation.

The ‘buy versus build’ dilemma will always surface at this point, and there are many reasoned arguments

that can be made on both sides. However, when you consider the cost of ownership of an off-the-shelf system that is fit-for- purpose with minimal customisation, the choice may become clearer. The system can be continuously updated and supported by the Vendor Partner for any new regulations, offers fast time to deployment, provides the flexibility for new commodities and process change, while offering standard architecture and scalability. Today is the time to review your current data and forward curve management systems, and to ensure that you’re making the right choice for tomorrow’s challenges. •

Richard Quigley is CEO of DataGenic,

a market leader in data management solutions for the commodity markets.E: richard.quigley@datagenicgroup.com

www.datagenicgroup.com

2011WINNER

Commodity

AwardsBusiness

Data Management2010

The challenge to organisations is to ensure compliance at a reasonable cost

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