Behavioural explanations of Expectile VaR forecasting and dynamic hedging strategies for downside risk during the COVID‐19 pandemic: Insights from financial markets

Yousra Trichilli, Sahbi Gaadane, Mouna Boujelbène Abbes and Afif Masmoudi

International Journal of Finance & Economics, 2025, vol. 30, issue 1, 44-70

Abstract: In this paper, we investigate the influence of confirmation bias on Expectile Value at Risk (EVaR) forecasting among fundamentalist, optimistic, and pessimistic investors in cryptocurrency, commodity, and stock markets before and during the COVID‐19 pandemic. Utilizing the DCC‐range GARCH model, we also explore the conditional minimum downside risk hedge ratios. Our findings demonstrate that confirmation bias leads to excessive EVaR for financial market returns, regardless of the period being before or during COVID‐19. Moreover, fundamentalists' expectations in all markets remain constant, while without confirmation bias, optimists' and pessimists' expectations tend to converge to zero over time but diverge significantly during turbulent periods. When confirmation bias is present, the average distance between these expectations widens. Analysing the hedge ratio results, with or without confirmation bias, also unveils the conditional minimum downside risk hedge ratios. These ratios indicate the optimal proportions for hedging downside risk in each financial market during different periods. We find that the conditional minimum downside risk hedge ratios are generally lower (higher) during the pre‐COVID‐19 (COVID‐19) period, implying that hedging costs are higher during the COVID‐19 period. These insightful findings offer valuable insights for traders and regulators in identifying and understanding the risk conditions of cryptocurrency, commodity, and stock markets. Additionally, the analysis of conditional minimum downside risk hedge ratios provides investors with essential information on how to strategically position their portfolios to mitigate and manage risk during both tranquil and turbulent market conditions, with and without confirmation bias.

Date: 2025
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https://doi.org/10.1002/ijfe.2902

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