Pricing electricity day-ahead cap futures with multifactor skew-t densities

Takuji Matsumoto, Derek Bunn and Yuji Yamada

Quantitative Finance, 2022, vol. 22, issue 5, 835-860

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.

Date: 2022
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DOI: 10.1080/14697688.2021.1984553

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