Trading & Hedging Decisions
framework to measure the fair value of derivatives in financial statements. This standard has already increased the consistency as well as comparability in fair value measurements across different firms, and requires firms to ‘bucket’ the fair value of their assets and liabilities into three liquidity levels as a function of the ‘observability’ of their market values. Many firms in the energy sector have traditionally used their
own forward curves to perform daily portfolio valuations and determine unrealised market-to-market (or to be more precise, mark-to-model) gains and losses. The new statement requires companies to take a more active market perspective. The definition of fair value that
specific asset operating constraints. The valuation, risk metrics and hedging ratios calculated from a static model are not just likely to be inaccurate, but could lead to sub-optimal decisions that would impact the profitability.
Conclusion Embracing new developments in energy derivatives valuation
and risk models can empower risk managers to provide greater value to their firms and proactively assist with the identification, measurement and management process of those risks. We expect that energy firms
Embracing new developments in
is gaining most acceptance is the ‘exit’ price and must include non- performance risk adjustments such as counterparty credit risk, which had been largely ignored by accounting and risk management groups traditionally. The introduction of probability of default (PD) as well as liquidity adjustments brings new challenges and opportunities to improve the valuation process and require the interaction of accounting groups with risk groups. Other factors that may impact the credit adjustments are the
existence of netting or offset agreements, as well as collateral and other credit risk mitigation tools such as letters of credit or bank guarantees. Other financial reporting requirements where a risk engine
can assist accounting and treasury groups includes hedge effectiveness evaluation under FAS 133/IAS 39 rules, as well as the assessment of potential collateral requirements in the event of a downgrade and other liquidity risk metrics.
Optimisation of Physical Assets & Trading Strategies Many risk and valuation models assume that the portfolio
is static. However, most trading and hedging decision are not made in a ‘set and forget’ mode. Many firms have hedging strategies in place which set certain ratios of the volume to be hedged for a given horizon as well as the re-balancing frequency. To provide forward looking metrics of risk for those strategies, it is essential to explicitly take into account the trading and hedging decisions under certain market conditions as well as management intervention rules. An area where dynamic risk models are gaining growing
acceptance in the marketplace is in the optimisation of physical assets such as storage facilities, pipelines, and power plants. The traders and operators of those assets attempt to maximise risk- adjusted profits based on observable market spreads and the
worldPower 2010
energy derivatives valuation and risk models can empower risk managers
will be gradually replacing their current risk and valuation models based on unrealistic assumptions regarding portfolio and market behaviour with more dynamic risk
simulation-based tools that can address the real problems that need to be solved. In order for that transformation to take place, systems
and models must change to capture the value of a shared environment, in which risk managers can develop and implement analytic solutions that respond to the evolving needs of traders, risk managers and senior managers. ■
Carlos Blanco is co-founder and Managing Director of NQuantX, LLC, a financial engineering firm that develops customized software to design and implement hedging
programs and trading strategies, as well as valuation and risk measurement of energy derivatives, long term contracts and physical assets. He also conducts several courses on energy derivatives hedging, pricing and risk management, as well as credit and counterparty risk management for the Oxford-
Princeton Program. He is a lecturer on risk management at the University of California, Berkeley. E:
carlos@nquantx.com
Michael Pierce is co-founder and director of financial
engineering at NQuantX LLC. He is a former senior financial engineer at Financial Engineering Associates where he was
responsible for front-line development of numerous software products. Some specific areas of development include energy forward curve calibration and modelling, development of a hybrid electricity model used in Monte Carlo real asset valuation of generating assets and load serving agreements,
correlation matrix calibration and multi-regional temperature modelling for weather derivatives. E:
mike@nquantx.com
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