journal article Open Access Jun 29, 2023

Evaluating the Efficiency of Financial Assets as Hedges against Bitcoin Risk during the COVID-19 Pandemic

Mathematics Vol. 11 No. 13 pp. 2917 · MDPI AG
View at Publisher Save 10.3390/math11132917
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.
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References
25
[1]
Baek "Bitcoins as an investment or speculative vehicle? A first look" Appl. Econ. Lett. (2014) 10.1080/13504851.2014.916379
[3]
Aliu, F., Asllani, A., and Hašková, S. (Stud. Econ. Financ., 2023). The impact of bitcoin on gold, the volatility index (VIX), and dollar index (USDX): Analysis based on VAR, SVAR, and wavelet coherence, Stud. Econ. Financ., ahead-of-print. 10.1108/sef-04-2023-0187
[4]
Maghyereh "COVID-19 and the volatility interlinkage between bitcoin and financial assets" Empir. Econ. (2022) 10.1007/s00181-022-02223-7
[5]
Mohammad "COVID-19 government interventions and cryptocurrency market: Is there any optimum portfolio diversification?" J. Int. Financ. Mark. Inst. Money (2022) 10.1016/j.intfin.2022.101691
[6]
Manahov "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets" Int. Rev. Financ. Anal. (2020) 10.1016/j.irfa.2020.101629
[7]
Ederington "The Hedging Performance of the New Futures Markets" J. Financ. (1979) 10.1111/j.1540-6261.1979.tb02077.x
[8]
Wijk, D. (2013). What Can Be Expected from the Bitcoin?. [Master’s Thesis, Erasmus Universiteit].
[9]
Dyhrberg "Bitcoin, Gold and the Dollar—A GARCH Volatility Analysis" Finance Res. Lett. (2016) 10.1016/j.frl.2015.10.008
[10]
Klabbers, S. (2017). Bitcoin as an Investment Asset: The Added Value of Bitcoin in a Global Marketfolio. [Master’s Thesis, Department of Financial Economics, Radboud Universiteit].
[11]
Balcilar "Can Volume Predict Bitcoin Returns and Volatility? Aquantiles-Based Approach" Econom. Modell. (2017) 10.1016/j.econmod.2017.03.019
[12]
Wang "On the Predictive Power of ARJI Volatility Forecasts for Bitcoin" Appl. Econ. (2019) 10.1080/00036846.2019.1602714
[13]
Choi "Bitcoin: An Inflation Hedge but not a Safe Haven" Finance Res. Lett. (2022) 10.1016/j.frl.2021.102379
[14]
Myers "Generalized Optimal Hedge Ratio Estimation" Am. J. Agric. Econ. (1989) 10.2307/1242663
[15]
Myers "Estimating time-varying optimal hedge ratios on futures markets" J. Futur. Mark. (1991) 10.1002/fut.3990110105
[16]
Lien "A note on the superiority of the OLS hedge ratio" J. Futur. Mark. (2005) 10.1002/fut.20172
[17]
Engle "Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. Inflation" Econometrica (1982) 10.2307/1912773
[18]
Bollerslev "Generalized autoregressive conditional heteroskedasticity" J. Econ. (1986) 10.1016/0304-4076(86)90063-1
[19]
Engle "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models" J. Buss. Econ. Stat. (2002) 10.1198/073500102288618487
[20]
Baillie "Bivariate garch estimation of the optimal commodity futures Hedge" J. Appl. Econ. (1991) 10.1002/jae.3950060202
[21]
Kroner "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures" J. Financ. Quant. Anal. (1993) 10.2307/2331164
[22]
Bollerslev "Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized Arch Model" Rev. Econ. Stat. (1990) 10.2307/2109358
[23]
Holmes "Stock Index Futures Hedging: Hedge Ratio Estimation, Duration Effects, Expiration Effects and Hedge Ratio Stability" J. Bus. Financ. Account. (1996) 10.1111/j.1468-5957.1996.tb00402.x
[24]
Fiorentini "Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroscedastic Dynamic Regression Models With Student T Innovations, Journal of Business and Economic Statistics" Appl. Econ. (2003)
[25]
Harvey "Unobserved component time series models with ARCH disturbances" J. Econom. (1992) 10.1016/0304-4076(92)90068-3