Evaluating the Efficiency of Financial Assets as Hedges against Bitcoin Risk during the COVID-19 Pandemic
Li Wei,
Ming-Chih Lee (),
Wan-Hsiu Cheng,
Chia-Hsien Tang and
Jing-Wun You
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Li Wei: Guangxi Accounting Research Institution, The Center of Econometric Application in Accounting and Finance, College of Accounting and Auditing, Guangxi University of Finance and Economics, Nanning 530003, China
Ming-Chih Lee: Department of Banking and Finance, College of Business and Management, Tamkang University, New Taipei City 251301, Taiwan
Wan-Hsiu Cheng: Department of Banking and Finance, College of Business and Management, Tamkang University, New Taipei City 251301, Taiwan
Jing-Wun You: Department of Banking and Finance, College of Business and Management, Tamkang University, New Taipei City 251301, Taiwan
Mathematics, 2023, vol. 11, issue 13, 1-19
Abstract:
In the turbulent landscape of financial markets, Bitcoin has emerged as a significant focus for investors due to its highly volatile returns. However, the risks and uncertainties associated with it necessitate effective hedging strategies. This paper explores the potential of various financial assets, including interest rates, stock markets, commodities, and exchange rates, as dynamic hedges against Bitcoin’s risk. Utilizing a DCC-GARCH model, we construct a dynamic hedging model to analyze the viability of these financial assets as hedges. The data is categorized into pre-pandemic and pandemic periods to assess any change in hedging performance due to the outbreak of COVID-19. Our empirical findings suggest that the dynamic DCC-GARCH model outperforms the static OLS model in this context. During the pandemic period, a diverse set of financial assets demonstrated enhanced efficiency in hedging Bitcoin risk compared to the pre-pandemic phase. Among the hedging commodities, stock market indices, the US dollar index, and commodity futures displayed superior performance.
Keywords: cryptocurrency risk; financial volatility; dynamic hedging; COVID-19 impact; DCC-GARCH model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:13:p:2917-:d:1182581
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