The Inefficiency of Bitcoin and the COVID-19 Pandemic

Keywords: Adaptive Market Hypothesis, Bitcoin, Cryptocurrency, Covid-19 Pandemic, Market Efficiency.

Abstract

From the perspectives of asset pricing, market outreach, regulatory framework, and investor ethos, crypto markets differ substantially from traditional financial markets. Given these fundamental differences, it is interesting to examine how the notions of market efficiency apply to crypto markets, especially because the arguments of the efficient market hypothesis (Fama, 1970) and the adaptive market hypothesis (Lo, 2004, and Lo, 2008) were originally developed in the context of traditional financial markets. Research on the informational efficiency of crypto markets has attracted increasing attention in recent years. This paper examines the evolving efficiency of Bitcoin, the leading cryptocurrency, especially during the period when economies around the world were devastated by the Covid-19 pandemic. For a newly-emerged cryptocurrency with a market that is essentially global, a global shock like the Covid-19 pandemic presents ideal conditions for assessing how efficiency evolves as the market faces a series of shocks.  Employing a fixed-length rolling window approach, this paper carries out the following tests: the automatic portmanteau test of Escanciano and Lobato (2009), the wild bootstrap automatic variance ratio test proposed by Kim (2009), the generalized spectral test of Escaciano and Valesco (2006), and the test proposed by Dominguez and Lobato (2003). The results provide evidence of episodes of inefficiency in a market that is efficient over extended periods. The inefficiency index constructed in this study shows that the Bitcoin market went through proportionately longer and more frequent episodes of inefficiency during the Covid-19 period. This is in line with the adaptive market hypothesis and has practical significance for investors and regulators.

 

References

Bai, J. & Perron, P. (2003). Computation and analysis of multiple structural change models, Journal of Applied Econometrics, 18, 1-22.

Barieviera, A. F. (2017). The inefficiency of Bitcoin revisited: a dynamic approach, Economics Letters 161, 1-4.

Charles, A., Darne, O. & Kim, J.H. (2011). Small sample properties of alternative tests for martingale difference hypothesis. Economics Letters, 110 (2), 151-154.

Choi, I. (1999). Testing the random walk hypothesis for real exchange rates. Journal of Applied Econometrics, 14(3), 293-308.

Dominguez, M.A. & Lobato, I.N. (2003). Testing the martingale difference hypothesis. Econometric Reviews, 22(4) 371-377.

Durlauf, S.N. (1991). Spectral based testing of the martingale hypothesis. Journal of Econometrics, 50, 355-376.

Escanciano, J.C. & Velasco, C. (2006). Generalized spectral tests for the martingale difference hypothesis, Journal of Econometrics, 134, 151-185.

Escanciano, J.C. & Lobato, I.N. (2009). An automatic portmanteau test for serial correlation, Journal of Econometrics,151, 140-149.

Fama, E. F. (1970). Efficient capital markets: a review of theory and empirical work, The Journal of Finance, 25(2), 383-417.

Kim, J.H. (2009). Automatic variance ratio test under conditional heteroscedasticity, Finance Research Letters, 6(3), 179-185.

Lo, A.W. & MacKinlay, A.C. (1988). Stock market prices do not follow random walk: evidence from a simple specification test, The Review of Financial Studies 1(1) 41-66.

Lo, A. W. (2004). The adaptive market hypothesis: market efficiency from an evolutionary perspective, The Journal of Portfolio Management 30(5), 15-29.

Lo, A.W. (2008). Efficient Markets Hypothesis, In S.N. Durlauf & L.E. Blume (Eds.), The New Palgrave Dictionary of Economics (2nd edition, pp. 1678–1690). Palgrave McMillan.

Ljung G.M. & Box, G.E.P. (1978). On a measure of lack of fit in time series models, Biometrika 65(2), 297-303.

Nadarajah, S. & J. Chu, J. (2017). On the inefficiency of Bitcoin, Economics Letters, 150, 6-9.

Nicolle, E. & Kharif, O. (2022). Crypto’s $2 trillion shakeout portends Lehman moment, Bloomberg Law, https://news.bloomberglaw.com/banking-law/cryptos-2-trillion-shakedown-portends-lehman-moment?context=article-related

Sensoy, A. (2019). The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies, Finance Research Letters, 28, 68-73.

Urquhart, A. (2016). The inefficiency of Bitcoin, Economics Letters, 148, 80-82.

Wei, W.C. (2018). Liquidity and market efficiency in cryptocurrencies, Economics Letters, 168, 21-24.

Zheng N. & Kaizoji, T. (2019). Market efficiency of the bitcoin exchange rate: Weak and semi-strong form tests with the spot, futures and forward exchange rates, International Review of Financial Analysis, 62, 273-281.
Published
2024-06-24
How to Cite
Asthana, V. (2024). The Inefficiency of Bitcoin and the COVID-19 Pandemic. Review of Applied Socio-Economic Research, 27(1), 50-60. https://doi.org/10.54609/reaser.v27i1.409