Matsumoto, T, Bunn, D W and Yamada, Y (2022) Pricing Electricity Day-ahead Cap Futures with Multifactor Skew-t Densities. Quantitative Finance, 22 (5). pp. 835-860. ISSN 1469-7688
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.
More Details
Item Type: | Article |
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Subject Areas: | Management Science and Operations |
Additional Information: |
© 2021 Taylor & Francis / Informa Group. |
Funder Name: | Japan Society for the Promotion of Science |
Date Deposited: | 20 Sep 2021 10:36 |
Date of first compliant deposit: | 22 Dec 2021 |
Subjects: |
Pricing Electricity supply industry |
Last Modified: | 30 Oct 2024 01:48 |
URI: | https://lbsresearch.london.edu/id/eprint/1963 |