A UtiliPoint Issue Alert
Patrick Reames

The most common tools of energy commodity risk management, namely Mark to Market (MtM) and Value at Risk (VaR), have become standardized metrics for any shop trading in the market. These metrics have their roots in the financial trading world, have transitioned well to energy commodity trading, and have become the most accepted measures of financial exposure.
For those holding and trading only energy commodities (physical, financial or both), not the production assets, these metrics work well. Mark to Market provides an objective measure of the commodity portfolio’s value and VaR provides a measure of the risk associated with that portfolio over an assumed holding period (subject to a set of key assumptions). While other models are available for managing the risk associated with transacting in energy commodities, these are the two that have consistently been deployed in any shop that trades energy. So ubiquitous are these metrics that risk management software is generally defined as a solution that offers position management with MtM and VaR functionality.

As noted above, MtM and VaR work well in commodity trading. However, there is a growing recognition that for companies trading portfolios that include not only the commodity, but also the producing assets, these metrics do not necessarily provide a complete picture of the financial risks involved. For these companies, such as generation owners, MtM and VaR address the only risks of the produced commodity, not those associated with the asset. Users of traditional risk management systems have attempted to model assets as various types of options, however, they have generally fallen short in accurately modeling complex real assets. In order to fully address the risks associated with these assets, risk management tools need to be more tightly integrated with the operational systems and employ hybrid models that address the operational constraints and complexities, providing for more accurate hedging strategies and alternative risk measures such as Gross Margin at Risk.

Evolving to this understanding has been somewhat slow in coming. The production side of the energy value chain has historically been thought of in terms of operations, that is, maximize production and minimize costs. With the growing trend of pure trading enterprises acquiring the underlying producing assets, we’ve seen the growing recognition that traditional risk management tools are, in many instances, insufficient in addressing the complexities and interdependences associated with attempting to marry trading and operations. Grant Thain, Sr. Vice President of ETRM Products at Global Energy Decisions (now owned by Ventyx) puts it this way, “There are many reasons that an asset backed trader may need to look beyond a standard MtM/VaR risk solution, and most of these reasons will fall within one or more of the following camps: 1) there may not be sufficient market liquidity to support the underlying holding period assumption, 2) VaR does not match actual earnings volatility on an accrual basis and/or the absolute value of VaR doesn’t reflect the real risk to the business, 3) VaR doesn’t reflect the risk reduction achieved by the hedging group, 4) the associated generation asset models do not provide sufficient accuracy to reconcile with actual outturns, and 5) they may have difficulty in incorporating fundamental energy market interdependencies and constraints with actual spot market revenue and operations.”

Alternative Models
The basic tenant of business is that companies should always seek to maximize shareholder value. For businesses whose stocks are traded in public exchanges, maximizing shareholder value generally means growing earnings in-line with market expectations. As Mr. Thain puts it, “While fair value earnings (mark to market) will contribute to this for the vast majority of companies, the bulk of these earnings are accrual based and need to be managed around a target plan or budgetary expectation. In effect they are interesting in understanding the risk to gross margin by reporting time period.” For most of these companies, their financing structures (with the obligations to meet certain debt and equity targets) depend on the earnings stream generated by their portfolio. Therefore, the fundamental objectives of those companies’ portfolio management group are to understand the likelihood of meeting the earning targets, and to ensure appropriate and effective value protection measures are in place to manage any potential negative impacts to that portfolio. Gross Margin at Risk (GMaR) has been gaining acceptance as an approach to meeting these objectives.

According to Mr. Thain, GMaR is not a new concept and has been in use by many risk management groups for a number of years as a compliment to VaR. However, he points out that it is often confused with a number of alternative labels such as Cash Flow at Risk, Profit at Risk, Revenue at Risk, and To Expiration at Risk. These measures are often interpreted and implemented slightly differently across different enterprises. “The approach to GMaR calculations and associated hedging varies, but are primarily introduced through what have been classed as hybrid models. Hybrid in this circumstance means a combination of standard risk and stochastic processes with an asset dispatch model. Simply put, it follows the following steps: 1) input forward market prices and volatilities, 2) calibrate forward prices to spot market prices, 3) apply simulated prices within a Monte Carlo engine, 4) dispatch assets against spot prices and calculate real option values using a linear program algorithm, and 5) calculate the appropriate hedge and risk metrics.”

As explained by Mr. Thain, a key of the GMaR approach is that it looks at the volatility of actual margins by future reporting period under alternative hedging strategies, including the base position of doing nothing. In addition to calculating an alternative risk measure, the approach can also easily provide:

1. current expected value of the portfolio compared to the plan
2. the potential downside from that expected value (and Relative Earnings at Risk) from the planned position
3. the current probability of meeting the plan
4. the impact of your hedges in reducing risk

“As hedges are added, this approach directly measures the risk reduction and increased probability in meeting the plan’s objective. This arguably provides a more meaningful risk/reward ratio than one based on VaR.”

“A growing number of companies have also been looking at this approach to provide more meaningful hedging ratios. This involves taking the results from the Monte Carlo simulation and calculating the equivalent delta, gamma and other Greeks from the results. While not common yet, we have seen this put into practice using a number of alternative methods.”

The Vendors
In reviewing the market for these types of asset centric capabilities, a number of risk management specialists are providing tools and analytics for asset centric trading including FEA, Lacima, and IRM (now part of OpenLink). Many risk management consulting groups also market capabilities in extending tools to help address the complexities. From the standpoint of product-centric vendors, Ascend Analytics and Global Energy have been leading the push for market acceptance of approach. According to Mr. Thain, Global Energy (now Ventyx) has fully integrated these asset-centric risk management capabilities into their Enerprise framework, ensuring common asset data across the operational, planning, and trading groups.

Market Acceptance
While the market for these alternative approaches to asset backed trading has been growing, it’s been primarily driven from outside the traditional risk and hedging control processes, being viewed as a bridge from operations to the enterprise level risk group. Over the next few years, as asset portfolios continue to grow in value and breadth, the capital exposures and market volatilities will compel more and more organizations to more tightly integrate these capabilities within an enterprise risk control framework. As these companies seek to increase their capabilities in asset centric risk management, they should look to implement solutions that can be fully integrated with their existing or planned ETRM systems and ensure that enough flexibility exists to facilitate expansion of analytic capabilities and reporting. As always, we would also recommend a formalized programmatic approach, such as a vendor supported system, rather than internally developed spreadsheets, prone to error and rarely SOX compliant.

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