Forecasting Volatility and Tail Risk in Electricity Markets

Antonio Naimoli and Giuseppe Storti
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Antonio Naimoli: Dipartimento di Scienze Economiche e Statistiche (DISES), Università di Salerno, Via Giovannni Paolo II, 132, 84084 Fisciano, Italy

JRFM, 2021, vol. 14, issue 7, 1-17

Abstract: This paper investigates the benefits of jointly using several realized measures in predicting daily price volatility, Value-at-Risk, and Expected Shortfall in the Australian electricity markets of New South Wales, Queensland, and Victoria. We propose using Realized GARCH-type models with multiple measurement equations based on robust estimators to account for market microstructure noise and jumps in electricity price series. The model specifications that combine information from multiple realized measures improve the in-sample fit of the data. The out-of-sample analysis shows that use of the jump-robust medRV estimator significantly increases the accuracy of volatility forecasts, while in forecasting Value-at-Risk and Expected Shortfall at different risk levels, the standard GARCH(1,1) also performs remarkably well.

Keywords: volatility forecasting; value-at-risk; expected shortfall; realized GARCH; electricity prices (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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