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

IF 2.8 3区 经济学 Q2 BUSINESS, FINANCE International Journal of Finance & Economics Pub Date : 2023-11-06 DOI:10.1002/ijfe.2902
Yousra Trichilli, Sahbi Gaadane, Mouna Boujelbène Abbes, Afif Masmoudi
{"title":"Behavioural explanations of Expectile <scp>VaR</scp> forecasting and dynamic hedging strategies for downside risk during the <scp>COVID</scp>‐19 pandemic: Insights from financial markets","authors":"Yousra Trichilli, Sahbi Gaadane, Mouna Boujelbène Abbes, Afif Masmoudi","doi":"10.1002/ijfe.2902","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":47461,"journal":{"name":"International Journal of Finance & Economics","volume":"28 1","pages":"0"},"PeriodicalIF":2.8000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Finance & Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/ijfe.2902","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

Abstract

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
COVID - 19大流行期间预期VaR预测和下行风险动态对冲策略的行为解释:来自金融市场的见解
在本文中,我们研究了在COVID - 19大流行之前和期间,加密货币、商品和股票市场的原教旨主义、乐观主义和悲观主义投资者对确认偏差对风险预期值(EVaR)预测的影响。利用DCC‐range GARCH模型,我们还探讨了有条件的最小下行风险对冲比率。我们的研究结果表明,无论是在COVID - 19之前还是期间,确认偏差都会导致金融市场回报的EVaR过高。此外,基本面主义者对所有市场的预期都保持不变,而在没有确认偏差的情况下,乐观主义者和悲观主义者的预期往往会随着时间的推移趋近于零,但在动荡时期会出现显著分歧。当存在确认偏误时,这些期望之间的平均距离就会变大。对对冲比率结果的分析,无论是否存在确认偏差,也揭示了有条件的最低下行风险对冲比率。这些比率表明了在不同时期每个金融市场对冲下行风险的最佳比例。我们发现,在前COVID - 19 (COVID - 19)期间,条件最小下行风险对冲比率通常较低(较高),这意味着在COVID - 19期间对冲成本较高。这些深刻的发现为交易员和监管机构识别和理解加密货币、大宗商品和股票市场的风险状况提供了宝贵的见解。此外,对有条件的最低下行风险对冲比率的分析为投资者提供了在平静和动荡的市场条件下如何战略性地定位其投资组合以减轻和管理风险的基本信息,无论是否存在确认偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
5.70
自引率
6.90%
发文量
143
期刊最新文献
Issue Information Issue Information Issue Information Issue Information Correction to “Outward foreign direct investment and economic growth in Romania: Evidence from non-linear ARDL approach”
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1