Managing Forward Curves in a Complex Market

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Any company that owns commodities, either through production or merchant activities, needs to know not only the current value of those commodities based on market prices, but also needs to develop a view of the future value of those commodities during the time that they are projected to be held in inventory. Additionally, agreements to purchase commodities in the future must be accounted for, not only at their agreed or projected purchase price, but also during their anticipated holding period.Commodity prices are constantly changing and are driven by market forces that are virtually impossible to predict with any degree of certainty. As such, accurately forecasting costs and price exposures is difficult at best, and particularly so now, given the rapidly changing supply and demand patterns that define the global commodity complex. Huge growth in demand for all commodities in Asia, the rapid rise of agricultural exports from developing countries in the Asia-Pac region, and the shale revolution that is driving unprecedented growth in US oil production, are all examples of the new dynamics that have fundamentally altered price formation in markets around the world. In this globalized and increasingly interconnected market-place, which is being constantly buffeted by economic uncertainty, predicting future prices is more difficult, but perhaps more important, than ever.

Text of Managing Forward Curves in a Complex Market

  • Managing Forward Curves in a Complex Market

    WHITE PAPER

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  • Commodity Technology Advisory LLC, 2014

    Introduction

    Commodity prices are constantly changing and are driven by market forces that are virtually impossible to predict with any degree of certainty. As such, accurately forecasting costs and price exposures is difficult at best, and particularly so now, given the rapidly changing supply and demand patterns that define the global commodity complex. Huge growth in demand for all commodities in Asia, the rapid rise of agricultural exports from developing countries in the Asia-Pac region, and the shale revolution that is driving unprecedented growth in US oil produc-tion, are all examples of the new dynamics that have fundamentally altered price formation in markets around the world. In this globalized and increasingly interconnected market-place, which is being con-stantly buffeted by economic uncertainty, predicting future prices is more difficult, but perhaps more im-portant, than ever. Along with ever shifting supply and demand patterns, new markets, trading hubs, and storage facilities have opened, creating new trading loca-tions where none existed just a few short years ago. Though many have already become recognized pric-ing centers, others are, and continue to be, rather illiquid, with few transactions and little knowledge in the broader market as how to price those locations on a future basis. Even in areas and markets that have had a long and sustained history of prices, new productive re-gions (such the massive growth in natural gas pro-duction from the Marcellus Shale in the Northeast US, for example) can create a lasting and dramatic

    change in futures prices. Future price prediction then becomes difficult as the sudden change in fundamentals produces prices that are uncor-related from historical activity. With these market changes, the ability to interpret market activity and measure the future impact of anticipated developments becomes more imperative. Defaulting to a common exchange price curve or at-tempting to simply project historical prices forward is insufficient in this dynamic environment as it ignores the both the global impact of chang-ing supply and demand patterns and the growing inter-relationships amongst commodities and markets. While some wholesale spot markets that trade on exchanges, such as Henry Hubs natural gas contract, are well established, highly liquid and somewhat seasonally predictable, the majority of commodity trading locations and markets around the globe are not, and exchange data is either not directly reflective or is unreliable. Its these imperfect, inefficient and sometimes insufficiently liquid wholesale spot markets where the need for careful and thoughtful modeling of future prices, or the forward curve, becomes an essential exercise in risk management and financial reporting for commodity trading companies. In this paper, well examine the complexities associated with the development, and the specific uses, of forward price curves. In addi-tion, well review a sophisticated technology available from DataGenic the Genic CurveBuilder - that can automate and reduce the complexity associated with the development of forward price curves.

    Any company that owns commodities, either through production or merchant activities, needs to know not only the current value of those commodities based on market prices, but also needs to develop a view of the future value of those commodities during the time that they are projected to be held in inventory. Additionally, agreements to purchase commodities in the future must be accounted for, not only at their agreed or projected purchase price, but also during their anticipated holding period.

  • Commodity Technology Advisory LLC, 2015, All Rights Reserved.

    A ComTech Advisory WhitepaperManaging Forward Curves in a Complex Market

    FORWARD CURVES DEFINED

    USES OF 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. Established futures markets, such as the NYMEX Henry Hub natural gas contract, provide a series of future month contracts which are traded for fixed prices. These published future month prices take on a curve shape when graphed, and are thus referred to as the forward curve.

    A forward curve can be derived for any commodity with a forward delivery market; however, the accu-racy and completeness of that curve is going to de-pend on a number of factors, and primarily on the liquidity of each forward period. Unfortunately, given

    The predominant use of forward curves is in the preparation of corporate financial statements. Com-panies will use forward curves as key inputs to deriv-ative valuation models in order to calculate the fair value of commodity inventories or financial instru-ments that are carried on the balance sheet. For US-based, public companies that operate under the oversight of the Securities and Exchange Commission (SEC), this valuation activity is gov-erned by GAAP, and specifically ASC Topic 820 (formerly, SFAS-57). Amongst its requirements, Topic 820 states that companies should use mar-ket-based price inputs and should disclose the re-liability 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). These reliability level requirements often mean that compa-nies must use the most active market quotes, even

    The second common use of forward curves is in asset valuation for ei-ther planning purposes or dynamic hedging. As these valuations are not part of, or included, in the preparation of financial statement, com-panies may use something other than exchange-based curves. This is especially helpful in cases where the operating characteristics of a par-ticular asset are more granular than available market quotes; that is, they operate in a market or region not directly traded or otherwise well reflected by an exchange instrument. In this case, using derived curves would provide the asset holder with a better estimate of the assets cur-rent and future value. With an improved estimate of the assets value, the asset holder would be in a better position to manage the assets net risk via pro-duction or fuels hedging, or operational adjustments to maximize val-ue. However, again, its important to remember that such price curves would not meet GAAP definitions for input price reliability.

    that most markets and/exchanges do not exhibit high liquidity in all fu-ture periods, it is generally best practice to derive the curve from many sources of market data including exchanges, broker marks, trader indications and independent data publishers.

    FINANCIAL STATEMENTS AND FORWARD CURVES

    ASSET VALUATION

    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 re-statement in future periods; and in the process, bring increased scrutiny of their accounting and management practices by regulators and shareholders.

  • Commodity Technology Advisory LLC, 2015, All Rights Reserved.

    A ComTech Advisory WhitepaperManaging Forward Curves in a Complex Market

    RISK MANAGEMENT AND REPORTING

    In addition, settlement data from an exchange will be limited to transactions that have been executed across that platform and the accuracy of that data may be constrained by the liquidity in those markets the fewer the deals consummated at any particular mar-ket point, the greater the impact an anomalous trade will have in establishing the published price. Further, should a trade not be consummated for a particular market point in any given period, the exchange will still settle its open interest using a formula-based ap-proach in order to keep margin accounts in balance. Clearly, simply relying on exchange data to es-tablish forward prices may be insufficient, particularly for illiquid points or markets. So, in order to meet a companys requirement for forward curves reflective of their markets and curve usage, more robust curves can be internally developed against independent mar-ket data aggregated from multiple sources.

    A third common use for forward curves is in risk man-agement and reporting; and for these purposes, prac-tices can vary widely amongst market participants. Some companies may wish to have Value-at-Risk measurements and limits-monitoring processes match observable market data regardless of granu-larity. In this case, an exchange-based curve source will likely be the best option for forward curve devel-opment. Other companies may wish to apply liquidity and seasonality adjustments if they believe those practic-

    SOURCES OF FORWARD CURVE DATA

    There are many choices available to market participants seeking forward curve data sources. The most common sources are exchanges, brokers, data publishers, data distributors, ETRM system vendors, and in-ternally-developed models. It is important to understand your companys intended use of any particular forward curve in order to select the appro-priate sources and methodologies for deriving those curves. It is also key to understand the limitations and methodologies inherent in each of the selected data sources. Internally modeled curves may be the only option where reliable market data does not exist (e.g. illiquid points and tenors). In these cir-cumstances, the forward curves quality is highly dependent on the qual-ity of the market data inputs, modeling assumptions and methodology. Whenever internally modeled c