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In The News
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June 2005
Integrating Asset Valuation and Trading
By MIKE SICLARI and GIUSEPPE CASTELLACI
Managing risk associated with power generation can directly impact profitability. Energy and fuel prices along with other costs affecting generation assets are managed in some part by trading and hedging activities. The situation is complicated in that energy companies may hold a variety of generation assets that use coal, oil, natural gas or hydro.These assets need to be managed together to optimize their operations. Switching generation from one type of fuel-fired asset to another at the right time can optimize profitability. Other factors, such as regulatory and environmental issues, which extend beyond typical fuel, fixed and variable costs, need to be measured. Weather and emissions fall into this category. The intelligent implementation of risk management tools can help manage these risks.
Generation owners have a variety of methodologies available for valuing generating assets. Some are very complex and consume large amounts of computational time. Most of these companies use a variety of trading and hedging activities to offset market and environmental risks associated with fuel costs, weather or emissions.To evaluate the effectiveness of these activities, it would be desirable to have a system that could employ all of the traditional portfolio risk management techniques to compute value at risk, earnings at risk, deltas, etc. on portfolios that contain both generation assets and trading activities.
Monte Carlo analysis is one such technique. Using this method, series of hourly stochastic spot prices for power and fuel prices are generated for a given production period using mean reversion, jump diffusion or other processes. Dynamic optimization methods take into account a variety of operating constraints to determine when generation is economically viable and at what level of output or dispatch. This approach requires a significant amount of technical expertise and computational power to be useful and is extremely difficult to integrate into an overall system that captures trading activites. It is also difficult and sometimes not feasible to integrate this type of asset methodology into a system that uses typical portfolio risk management techniques.
Another common approach to power asset modeling employs option theory for some or all of the generation output. For instance, a base level of output from a plant might be committed to retail customers, with an option to generate and sell any excess output to the open market. In this case, the baseload output of the generator is valued as a forward contract and the excess is modeled using option theory. If the value of the option on the excess output is in-the-money, the plant's output is run to full capacity and power is then sold on the open market. This approach is computationally efficient and is amenable to most risk management techniques at the cost of idealizing some of the operating constraints. It is also attractive in the sense that asset value-based transactions can be integrated into an overall trading and risk management system that includes other hedging and trading activities.
Risk managers have a suite of option instruments available to assist in the modeling and rapid valuation of one or more power plants or co-firing generators. In order of complexity, they include the following:
Single plant, single fuel:
- Spark spread-two factors (power and fuel);
- Spread-two factors (power and fuel plus a fixed cost); and
- Basket spread (multiple cost factors with fixed cost).
Co-firing or multi-fuel plants:
- Spread (fuel) switching (two cost factors or fuels with fixed cost), and
- Basket spread switching (multiple cost factors with fixed cost).
Basket spread options allow for the introduction of other variable factors, such as the cost of emission permits that trade like other exchange instruments, in addition to the fuel that can affect the value of power generation. A new class of options, known as basket spread switching options, has been introduced to value the power generation of an asset or assets that can run on different fuels.
The payoff of a spread or basket spread switching option reflects the spread between the price of power and at least two baskets of stochastic cost factors, such as the price of fuel, emission costs or any other factors affecting the cost of power generation. The basket spread switching option additionally captures the value-added flexibility of switching generation from two different fuels.
Risk managers realize that generation units that operate with different fuels and can be quickly switched on and off can yield a higher earnings profile in comparison to a single fuel. They do so by optimally capturing the maximum spread between power and fuel prices and other costs in an everchanging market environment.
The use of the above instruments for asset valuation will allow the capture of generation asset value within a consistent risk management framework.
Mike Siclari, Ph.D., and Giuseppe Castellacci, Ph.D., are quantitative researchers at OpenLink. OpenLink is a leading provider of energy and financial trading, risk management, and operations software solutions. The company's Next Generation eXtensible (NGX) platform supports the most rigorous business requirements of firms trading in energy, interest rate derivatives, fixed income securities, foreign exchange, money markets, metals, and soft commodities.
As seen in Hart Energy Markets magazine - June 2005
Copyright © 2005 Hart Energy Publishing. All rights reserved.
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