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So, You Want to be a Retail Energy Marketer?
a wholesale marketer. These risks help define the retail energy market and can be placed into two broad categories: volumetric risk and tariff risk.
The main components of volumetric risk are consumption, forecasting and portfolio build risk.
Consumption risk falls into two categories: load profile and usage. () Since retail deals are by definition full-requirement deals, it is incumbent on the marketer to estimate both the customer's load shape and overall usage when pricing a new deal. Load shape will affect the demand charges the marketer incurs and the ratio of on-peak to off-peak power that he has to buy.
Usage will affect the marketer's energy charge. A large shift in either factor has the potential to change a deal's cost structure. Usage risk can be further divided into hourly and daily swings. Fluctuations in day-to-day and hour-to-hour loads, based on weather conditions and various plant operations, can result in mismatched hedges or higher cost supply products from generators.
A close cousin to consumption risk is forecasting error. While consumption risk is an ex ante risk, forecasting error is ex post deal consummation. Forecasting error is the difference between a customer's actual day and month-ahead usage and his forecasted usage. Differences here can leave a marketer either long or short subject to the extreme volatility of the spot market.
Bid-Offer Spreads: A Hedging Device
The Bid-Offer spread was suggested above as one of several possible mitigants for many of the listed risks. How exactly does a retail energy marketer use the spread as a hedging device?
Generically, the Bid-Offer spread represents the profit a market-maker or intermediary demands for creating liquidity. This spread is composed of the intermediary's variable cost per deal plus any liquidity risk they may bear. In liquid markets the bulk of the spread will be variable cost-based and in illiquid markets it will be dominated by the liquidity risk factor.
Newly deregulated energy markets are often characterized by a lack of liquidity. A player who wishes to create markets in such a nascent environment has at least three options for spread determination (in ascending order of complexity):
- Calculate the value-at-risk for the time period estimated it would take to liquidate the position and add the associated capital reserve charges and expected discounted sales value to the spread.
- Calculate the historical volatility of the underlying instrument and do a Monte Carlo simulation to set the mid-offer spread so that some percentage (e.g. 95 percent to 99 percent) of all deals done will have a profit greater than zero. This method may not always be viable since there may be no available data on the historical performance of the risk examined (e.g. unbundled transmission or distribution rates).
- Decompose the illiquid risk into its component parts and individually hedge those components that are liquid. In this case the hedging cost would be included in the spread. For the illiquid components proceed as #2 above. This method can be problematic since the cross-correlations between the component pieces must be known in order to properly take into account the portfolio effect.