Evaluating the Efficiency of the Global Cryptocurrency Market
DOI:
https://doi.org/10.17010/ijf/2023/v17i11/173325Keywords:
ARCH Modeling
, Cryptocurrency, Calendar Effects, EMH, Market Efficiency.JEL Classification Codes
, G12, G14, G15, G17Paper Submission Date
, December 6, 2022, Paper sent back for Revision, September 18, 2023, Paper Acceptance Date, September 30, Paper Published Online, November 15, 2023Abstract
Purpose : This study focused on evaluating the efficiency of the global cryptocurrency market under the efficient market hypothesis.
Methodology : The study explored the presence of calendar effects in the form of the day-of-the-week and the weekend effect in the top 25 global cryptocurrencies and a constructed index using autocorrelation corrected ARCH family models on the log-returns of prices. Non-normality is tackled through the use of a non-parametric bootstrapped approach in addition to parametric estimation. Additionally, rolling window regression is employed as a dynamic framework.
Findings : The findings of this study showed the presence of calendar effects in terms of higher returns for certain days over others, thereby concluding that the global cryptocurrency market as a whole was not efficient.
Practical Implications : As a result of its informational inadequacies, it was implied that cryptocurrency markets were not even efficient in the weak form. This had practical implications for investors, whose aggressive search and trading tactics appear warranted in the context of market anomalies, as well as other market players, like regulators attempting to comprehend the structure of the cryptocurrency market from an efficiency standpoint and researchers attempting to investigate the efficiency-related behavior and psychology of crypto markets.
Originality : This study is exceptional in that it uses a sample of cryptocurrencies that objectively covers the larger global cryptocurrency markets over the most extended amount of time possible, making it unique both for the participants in the crypto markets and for its contribution to the literature on market efficiency. The study employed an evolutionary methodology, taking into account the time-varying behavior of financial assets. As far as we can tell, this is one of the first studies to use this methodology and model formulation.
Downloads
Downloads
Published
How to Cite
Issue
Section
References
Al-Yahyaee, K. H., Mensi, W., & Yoon, S.-M. (2018). Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets. Finance Research Letters, 27, 228–234. https://doi.org/10.1016/j.frl.2018.03.017
Apopo, N., & Phiri, A. (2021). On the (in)efficiency of cryptocurrencies: Have they taken daily or weekly random walks? Heliyon, 7(4), E06685. https://doi.org/10.1016/j.heliyon.2021.e06685
Bartos, J. (2015). Does the Bitcoin follow the hypothesis of efficient market? International Journal of Economic Sciences, IV(2), 10–23. https://doi.org/10.20472/ES.2015.4.2.002
Bollerslev, T. (2008). Glossary to ARCH (GARCH). SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.1263250
Borges, M. R. (2009). Calendar effects in stock markets: Critique of previous methodologies and recent evidence in European Countries (Working Paper WP 37/2009/DE/UECE). ISEG School of Economics and Management, Technical University of Lisbon, Department of Economics, Lisbon. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.469.2309&rep=rep1&type=pdf
Bundi, N., & Wildi, M. (2019). Bitcoin and market-(in)efficiency: A systematic time series approach. Digital Finance, 1(1), 47–65. https://doi.org/10.1007/s42521-019-00004-z
Caporale, G. M., & Plastun, A. (2019). Price overreactions in the cryptocurrency market. Journal of Economic Studies, 46(5), 1137–1155. https://doi.org/10.1108/jes-09-2018-0310
Connolly, R. A. (1989). An examination of the robustness of the weekend effect. The Journal of Financial and Quantitative Analysis, 24(2), 133–169. https://doi.org/10.2307/2330769
Connolly, R. A. (1991). A posterior odds analysis of the weekend effect. Journal of Econometrics, 49(1–2), 51–104. https://doi.org/10.1016/0304-4076(91)90010-B
Cross, F. (1973). The behavior of stock prices on Fridays and Mondays. Financial Analysts Journal, 29(6), 67–69. https://doi.org/10.2469/faj.v29.n6.67
Fama, E. F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34–105. https://doi.org/10.1086/294743
Greene, W. H. (2012). Econometric analysis. Pearson.
Hannan, E. J., & Quinn, B. G. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society: Series B (Methodological), 41(2), 190–195. https://doi.org/10.1111/j.2517-6161.1979.tb01072.x
Khuntia, S., & Pattanayak, J. K. (2017). Dynamics of Indian foreign exchange market efficiency: An adaptive market hypothesis approach. Indian Journal of Finance, 11(9), 39–52. https://doi.org/10.17010/ijf/2017/v11i9/118088
Kumar, H., & Dawar, M. (2017). Seasonality in the Indian stock markets: A study of calendar effects. MUDRA: Journal of Finance and Accounting, 4(1), 1–19. https://doi.org/10.17492/mudra.v4i01.9780
Kurihara, Y., & Fukushima, A. (2017). The market efficiency of Bitcoin: A weekly anomaly perspective. Journal of Applied Finance & Banking, 7(3), 57–64. http://www.scienpress.com/Upload/JAFB%2fVol%207_3_4.pdf
López-MartÃn, C., Muela, S. B., & Arguedas, R. (2021). Efficiency in cryptocurrency markets: New evidence. Eurasian Economic Review, 11(3), 403–431. https://doi.org/10.1007/s40822-021-00182-5
Malkiel, B. G., & Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. https://doi.org/10.1111/j.1540-6261.1970.tb00518.x
Nadarajah, S., & Chu, J. (2017). On the inefficiency of Bitcoin. Economic Letters, 150, 6–9. https://doi.org/10.1016/j.econlet.2016.10.033
Parthasarathy, S. (2019). Revisiting the weak form efficiency with structural breaks: Evidence from the Indian stock market. Indian Journal of Finance, 13(10), 7–21. https://doi.org/10.17010/ijf/2019/v13i10/147744
Quiggin, J. (2013, April 16). The Bitcoin bubble and a bad hypothesis. The National Interest. https://nationalinterest.org/commentary/the-bitcoin-bubble-bad-hypothesis-8353
Ryaly, V. R., Subba Raju, G. V., & Urlankula, B. (2017). Testing the weak-form market efficiency in the Indian stock market: Evidence from the Bombay Stock Exchange Index (BSE) Sensex. Indian Journal of Finance, 11(3), 26–40. https://doi.org/10.17010/ijf/2017/v11i3/111647
Sarma, S. N. (2004). Stock market seasonality in an emerging market. Vikalpa: The Journal for Decision Makers, 29(3), 35–42. https://doi.org/10.1177/0256090920040303
Sensoy, A. (2019). The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies. Finance Research Letters, 28, 68–73. https://doi.org/10.1016/j.frl.2018.04.002
Sullivan, R., Timmermann, A., & White, H. (2001). Dangers of data mining: The case of calendar effects in stock returns. Journal of Econometrics, 105(1), 249–286. https://doi.org/10.1016/S0304-4076(01)00077-X
Tran, V. L., & Leirvik, T. (2019). A simple but powerful measure of market efficiency. Finance Research Letters, 29, 141–151. https://doi.org/10.1016/j.frl.2019.03.004
Tran, V. L., & Leirvik, T. (2020). Efficiency in the markets of crypto-currencies. Finance Research Letters, 35, 101382. https://doi.org/10.1016/j.frl.2019.101382
Urquhart, A. (2016). The inefficiency of Bitcoin. Economics Letters, 148, 80–82. https://doi.org/10.1016/j.econlet.2016.09.019
Vidal-Tomás, D., & Ibañez, A. (2018). Semi-strong efficiency of Bitcoin. Finance Research Letters, 27, 259–265. https://doi.org/10.1016/j.frl.2018.03.013
Wei, W. C. (2018). Liquidity and market efficiency in cryptocurrencies. Economic Letters, 168, 21–24. https://doi.org/10.1016/j.econlet.2018.04.003
