Extreme value theory and risk management
in electricity markets
Kam Fong Chan – University of Queensland Business School
Philip Gray – Monash Business School

Extreme events in finance

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This chapter explores the relative merits of a number of alternate approaches to estimating Value at Risk (VaR) for electricity markets. The distinctive features of electricity markets present non-trivial challenges for the trading and hedging activities of market participants. Compared to traditional approaches to forecasting VaR, the empirical findings provide strong support for the use of Extreme Value Theory (EVT). However, more sophisticated conditional EVT approaches do not necessarily outperform vanilla EVT approaches. Furthermore, the left tail of the return distribution proves particularly challenging to model. Given the idiosyncrasies of each electricity market, it is unlikely that a single approach is optimal across the board.

Extreme events in finance Extreme events in finance

Kam Fong Chan, University of Queensland Business School

Kam Fong Chan

University of Queensland Business School

Philip Gray, Monash Business School

Philip Gray

Monash Business School