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SPECIAL REPORT: RISK A Look Forward— Understanding Forward Curves in Energy Markets May 2012 Risk Data Services WWW.PLATTS.COM A Look Forward — Understanding Forward Curves in Energy Markets EXECUTIVE SUMMARY The term “forward curve” is a basic concept used freely by participants in energy markets. Despite the basic nature of the term itself, there is a wide divergence between companies in the definition and use of forward curves. This paper explores several types of forward curves used by market participants, differences between market-based curves and settlement-derived curves, and tools available to energy companies for modeling forward prices. FORWARD CURVES The term “forward curve” refers to a series of sequential prices either for future delivery of an asset or expected future settlements of an index. If we consider the NYMEX natural gas markets we note market participants could enter into contracts to purchase natural gas deliveries in future months for fixed prices. The contract for June deliveries recently settled at $2.3125, July deliveries settled at $2.519, August deliveries settled at $2.6445, and so forth. If we listed 12 months of futures prices in a table and then graphed thoseprices, it would look like this: Publishers vs. Exchanges A key concept this paper explores is the difference between market assessed forward curves produced by reputable energy market data publishers and data available from exchanges. Publishers, such as Platts, pull data from multiple sources to produce forward curve data that provides greater market coverage and improves reliability. forward curve. The availability and reliability of that forward curve is heavily dependent on the market’s liquidity at each forward month. Market data may come from multiple sources, including regulated exchanges, broker statements, trader indications, or third-party data publishers and distributors. Forward curve data may differ between data sources. The differences are commonly related to market insights available to a particular data source. For example, an exchange may only quote a market in multiple-month “strips” while a third party data publisher may quote each month within those strips based on overthe-counter data not available to the exchange. In the following example, Socal Gas basis swaps were recently quoted by both an exchange and by a market data publisher. The obvious difference is that the data publisher had availability to monthly quotes whereas the exchange quoted the first five months as a single strip. Differences in the remaining months are attributable to market liquidity and available data (i.e. the exchange bases its settlement prices on a few contracts which trade infrequently while the data publisher bases its quotations on daily over-the-counter transactions occurring between multiple market participants): Delivery Month Delivery Month June-12 2. 31 2 5 July-12 2. 51 9 August-12 2. 64 4 5 September-12 2. 61 9 October-12 2. 64 2 5 November-12 2. 93 6 9 December-12 3. 32 1 January-13 3. 40 6 5 February-13 3. 42 3 6 Delivery Month CME Platts March-13 3. 39 5 5 June-12 -0 . 0 3 -0 . 0 425 April-13 3. 35 0 6 July-12 0.0675 0.06 May-13 3. 38 7 3 August-12 0.12 0 . 1 25 September-12 0.065 0 . 0 575 October-12 0 0 November-12 0.0675 0 . 0 481 December-12 0.0675 0 . 1 059 January-13 0.0675 0 . 0 554 February-13 0.0675 0 . 0 602 March-13 0.0675 0 . 0 554 April-13 0.0575 0 . 0 318 May-13 0.0575 0 . 0 293 June-13 0.0575 0 . 0 293 Socal Gas Source: Platts, 5/2012 3.8 3.4 3 2.6 13 3 -1 ay M 13 Ap r 3 -1 12 -1 3 ar M Fe b Ja n c- 12 De 2 -1 2 -1 vNo Oc t -1 12 2 p Se Au g -1 Ju n Ju l- 2 2.2 This collection of prices is referred to as the “forward curve,” so-named because of the shape it takes on a graph. Any commodity with a forward market may be said to have a Sources: NYMEX & Platts, 5/2012 The choice between data sources is often a difficult one, with implications for position reporting, risk measurement, limits monitoring, fair value calculation, and financial statement reporting. PLATTS SPECIAL REPORT: RISK | 2 A Look Forward — Understanding Forward Curves in Energy Markets Exchange Data Limitations Improved Curve Validation Settlement data from an exchange are limited to transactions executed across the exchange’s platform. Settlement prices are based on single markets and are constrained by the liquidity in those markets – if a market doesn’t trade, the exchange will still “settle” its open interest using a formula-based approach in order to keep margin accounts in balance. Accessing market data from a respected publisher, such as Platts, strengthens the curve validation process. More robust results can be achieved through the validation of internally developed curves against independent market data aggregated from multiple sources. BUSINESS CHALLENGES There are many choices available to industry market participants seeking forward curve data sources. The most common sources are exchanges, brokers, data publishers, data distributors, ETRM system vendors, and internally-developed models. The first step towards selection of an appropriate forward curve source is to understand your company’s intended forward curve usage case. The next step is to understand the limitations and methodologies inherent in each forward curve source. The final step is to match your company’s needs to the most appropriate forward curve source and communicating the choice to key stakeholders. USAGE CASES The predominant usage case for forward curves is financial statement preparation. Companies use forward curves as inputs to derivative models to calculate the fair value of financial instruments carried on the balance sheet. For SEC filers, this activity is governed by GAAP, specifically ASC Topic 820 (formerly, SFAS-157). Amongst other things, Topic 820 states companies should use market-based price inputs and should disclose the reliability of those inputs. Input reliability is classified as either “level 1” (unadjusted quotes from active markets), “level 2” (quotes from inactive markets or markets for similar instruments), or “level 3” (price inputs based on management assumptions). The reliability level requirements often mean companies must use the most active market quotes, even in instances where those markets are quoted as strips as opposed to individual months. Accidentally using lower-level price inputs or misrepresenting the reliability of price inputs may put the company at risk of restatement in future periods. Another common usage case is asset valuation for either planning purposes or dynamic hedging. Since these valuations are not for financial statement preparation purposes, companies may use something other than exchange-based curves. This is especially helpful in cases where the operating characteristics of a particular asset are more granular than available market quotes. For instance, a company may have rights to a natural gas storage facility between November and March. If the company applied quarterly strip prices observed on exchanges, it would incorrectly price the asset’s value in November and December (i.e. the strip prices Oct-Dec, not Nov-Dec) and would fail to capture monthly spreads within a given quarter. Using “shaped” curves would provide the company with a better estimate of the asset’s value, even though the intra-quarter prices do not meet GAAP definitions for input price reliability. With a better estimate of the asset’s value, the company would be in a better position to manage the asset’s net risk. A third usage case is risk management and reporting. These practices vary widely amongst energy market participants, as do forward curve applications to this end. Some companies may wish to have Value-at-Risk measurements and limitsmonitoring processes match observable market data regardless of granularity. Other companies may wish to apply liquidity and seasonality adjustments if they believe those practices provide a more nuanced view of firm risk. The former may suggest an exchange-based curve source and the latter may suggest a curve source taking into consideration non-exchange data. In either case, companies should use a curve validation process by which they compare independent forward curve data to the forward curves which they use for financial reporting, risk measurement,and risk reporting. PLATTS SPECIAL REPORT: RISK | 3 A Look Forward — Understanding Forward Curves in Energy Markets LIMITATIONS AND METHODOLOGIES Forward curve providers vary in their approach to curve development, and these approaches should be aligned to a company’s specific usage case as the company determines which to use. Understanding the curve providers’ methodologies and the limitations of those methodologies is a key step in choosing the optimal forward curve source. The following table provides a summary of typical forward curve providers, their methodologies, and limitations. Provider Type Typical Methodology Methodological Limitation Publishers • Combined multiple sources of market data toproduce forward curves (e.g. exchanges, brokers, commercial and back office groups of market participants) • Internal quantitative methodologiesto model illiquid points • Independent of market participants • Usually broad coverage – not limited to trades on their system • Methodology used to model certain transactions may not be readily available or transparent • Timeliness of data delivery may be a challenge for companies requiring end of day risk reporting Exchanges • Quoted market prices for traded markets • Margin-based settlements for nontraded markets • Does not typically capture OTC transactions • May trade strips instead of individual months • Does not capture illiquid points Brokers • Aggregated price indications from dealer markets • Indications do not always indicate market trades • May indicate strips instead of individual months • Does not capture illiquid points Data distributors • Exchange-based data feeds • Data vendor aggregation • Quantitative models • May not have control over data vendor methodologies • May not disclose which curves and tenors are market-based and which are model-based System vendors • Data usually integrated as part of trading/risk management software • Exchange-based data feeds • Data vendor aggregation • Quantitative models • May not have control over data vendor methodologies • May not disclose which curves and tenors are marketbased and which are model-based • May lack long term analytical capabilities Consensus curve publishers • High trust in data as member participates in aggregation • Usually available on a monthly basis and only reflects activities by reporting entities as opposed to the broader market Internally developed curves • Trader assessments • Quantitative models • Traders may reflect book bias • Models may not be consistent with industry practice • Models may be mis-calibrated • May not match market quote PLATTS SPECIAL REPORT: RISK | 4 A Look Forward — Understanding Forward Curves in Energy Markets Transparency is Key When selecting a forward curve data provider, transparency into the providers’ methodologies and modeling techniques is key. The better providers will publish their methodologies on-line for access by anyone with an internet connection. There is an important distinction between curves based on market assessments (e.g. publisher curves) and those based on settlement prices (e.g. exchange curves). Market-assessed curves often involve multiple quotations in multiple markets, including both exchange trades and over-the-counter trades. Settlement prices are based on single markets and are constrained by the liquidity in those markets – if a market doesn’t trade, the exchange will still “settle” its open interest using a formula-based approach in order to keep margin accounts in balance. Understanding this distinction is important as failure to understand which exchange-based curves are traded versus “settled” may lead to false assertions related to Topic 820 reliability levels. Modeled curves should not be used if reliable market data exists. However, modeled curves may be the only option if market data does not exist (e.g. illiquid points and tenors). In those circumstances, the forward curve’s quality is highly dependent on the quality of market-based inputs, modeling assumptions, and modeling methodology. Failure to calibrate or back-test those models in a timely manner will negatively impact the modeled curves’ accuracy. Securing independently-modeled curves for comparison and validation is therefore an important control against model error. Whatever the curve source, transparency into its markets and methodologies is absolutely vital. Companies need to know: which curves are based on actual market trades;, which curves are based on settles; which settlement prices are exchange-derived for margining purposes when actual trades do not occur; which curves incorporate OTC trades or market assessments; which portions of particular curves are liquid and which are not; and which curves are modeled, how they are modeled, and how often they are recalibrated to observed markets for similar assets. would enable the company to apply sufficient granularity to its asset valuations, VAR calculations, and independent curve validation processes. Selection of a forward curve provider or providers should be accompanied by effective communication to enable stakeholders to understand and agree with the selection. Traders need to know the selection accurately reflects the market. Risk Control needs to know the selection meets risk management needs and is compliant with or can be incorporated into risk policies. Banks, auditors, investors, and regulators need to know the company reliably selects “mark-to-market” over “mark-to-make-believe” on a daily basis. Management needs to understand the selection in terms of the trade-off between cost and utility so that subsequent provider decisions are based on operational needs as opposed to cost-only decisions. RECOMMENDED APPROACH The most effective approach to forward curve selection is to understand your company’s usage cases, match those usage cases to the abilities and products offered by forward curve providers, and communicate the selection and subsequent curverelated processes to stakeholders. A number of common practices should be applied during such an approach: • Purchase reliable and daily mark-to-market data from a reputable source using industry-standard and transparent methodologies; • Risk-rank and categorize curves by factors such aggregate notional value, usage case, and firm-wide risk to help inform forward curve selection decisions; • Incorporate a robust but efficient curve validation methodology into the existing risk management framework; • Update risk policies to include forward curve selection, development, usage, and validation methodologies in order to specify which scenarios are appropriate for different market data sources; and • Communicate to necessary stakeholders that higher-risk curves require robust analysis based on independent validation against the best available market data sources, even if that analysis comes at a cost. SELECTION AND COMMUNICATION Once a company has defined a usage case (or cases), it can select a forward provider whose methodologies address the company’s needs and limitations that do not detract from the usefulness of the curves. It is possible that a company may choose multiple providers for multiple purposes. For instance, a company may select exchange-based curve data for fair value calculations and a publisher for asset valuations and risk management. The exchange-based data would allow the company to comply with Topic 820 reliability level requirements while the publisher data PLATTS SPECIAL REPORT: RISK | 5 BENEFITS OF EFFECTIVE FORWARD CURVE SELECTION to improve the reliability of its risk and analytical tools. This reliability may come through an enhanced curve validation process, reduced reliance on internal models, or consistency with industry-observed practices and pricing. Selecting the right forward curves for derivative valuation is a requirement for financial statement preparation. However, the selection of a forward curve provider or data source may yield additional benefits if done correctly. Aside from accurate valuation of derivatives and assets, the primary benefit of an effective curve selection process is improved clarity, reliability, and efficiency in operational and capital management processes. For instance, a clear understanding of forward curve usage cases and provider methodologies gives companies insights into the valuation components of complex transactions and assets. Companies which are able to institutionalize these insights through process, training, and policy are then able to increase the quality of their internal and external reporting. As another example, an enterprise-wide understanding of forward curve sources and limitations will allow a company The net effect of these benefits is a lower risk of financial reporting issues and misstatements. A clear knowledge of the forward curve source allows companies to provide Reliability Level assertions without fear of a future retraction. An effective validation process reduces the risk of model mis-calibration and derivative valuation error, thereby reducing the possibility of subsequent restatement. Enhanced reporting quality not only reduces the risk of financial statement error and restatement, but it increases management’s confidence in the long-term forecasts and strategic assessments which rely on forward curve assessments. By clarifying the reliability of forward-looking statements, management can better pursue strategies and manage the market risks associated with them. 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