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Pricing Electricity Day-ahead Cap Futures with Multifactor Skew-t Densities

Journal

Quantitative Finance

Subject

Management Science and Operations

Publishing details

Quantitative Finance 2022 Vol 22:5 p 835-860

Authors / Editors

Matsumoto T;Bunn D W;Yamada Y

Biographies

Derek Bunn

Publication Year

2022

Abstract

Short-term risk management is becoming increasingly significant in power trading as the intermittent renewable generators introduce more weather risk into the price formation dynamics. There is a vacuum in hedging instruments at the day-ahead stage to protect retailers in particular from such volatility and price spikes. Motivated by this requirement, this paper analyses a flexible hedging product, day-ahead cap futures. For pricing this product, we parametrically predict the probability distribution of day-ahead prices using the multifactor Generalized Additive Model for Location, Scale and Shape (GAMLSS) based upon the skew-t distribution with weather forecasts and calendar information as explanatory variables. In particular, we reveal that this higher-order moment model is superior to several lower-order models such as the normal distribution in all the following three aspects: fairness as pricing method, underwriting risk of the risk taker, and the variance reduction effect of the risk hedger.

Available on ECCH

No


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