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

Matsumoto, T, Bunn, D W and Yamada, Y (2021) Pricing Electricity Day-ahead Cap Futures with Multifactor Skew-t Densities. Quantitative Finance. ISSN 1469-7688 (Accepted)

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.

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Item Type: Article
Subject Areas: Management Science and Operations
Additional Information:

© 2021 Taylor & Francis / Informa Group.

This is an Accepted Manuscript version of the following article, accepted for publication in Quantitative Finance [awaiting citation on first online publication].

It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License https://creativecommons.org/licenses/by-nc-nd/4.0/, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

Date Deposited: 20 Sep 2021 10:36
Subjects: P > Pricing
E > Electricity supply industry
Last Modified: 21 Sep 2021 19:54
URI: https://lbsresearch.london.edu/id/eprint/1963
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