Cryptocurrency Market: Overreaction to News and Herd Instincts

Rui Dias – Polytechnic Institute of Setúbal, (ESCE/IPS), 2910-761 Setúbal, Portugal; Center of Advanced Studies in Management and Economics, University of Évora, 7004-516 Évora, Portugal

Mariana Chambino – Polytechnic Institute of Setúbal, (ESCE/IPS), 2910-761 Setúbal, Portugal

Cristina Morais da Palma – Polytechnic Institute of Setúbal, (ESCE/IPS), 2910-761 Setúbal, Portugal

Abstract: The present research focuses on the phenomenon of cryptocur­rency market overreactions, especially examining the behavior of Bitcoin, DASH, EOS, Ethereum, Lisk, Litecoin, Monero, NEO, Quantum, Ripple, Stel­lar, and Zcash from January 2, 2018, to March 1, 2023. The findings show that there are both positive and negative autocorrelations, which might re­sult in lowered volatility and more moderate fluctuations in prices. These re­sults possess the potential to assist investors in making well-informed choic­es since they are less susceptible to being influenced by exaggerated reac­tions to news or information hitting the market. However, before invest­ing in cryptocurrency markets, investors should exercise caution and care­fully examine their risk tolerance, since market circumstances may change quickly, making it impossible to perform consistently profitable trades.

9th International Scientific ERAZ Conference – ERAZ 2023 – Conference Proceedings: KNOWLEDGE BASED SUSTAINABLE DEVELOPMENT, hybrid – online, virtually and in person, Prague, Czech Republic, June 1, 2023

ERAZ Conference Proceedings published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia

ERAZ conference partners: Faculty of Logistics, University of Maribor, Maribor (Slovenia); University of National and World Economy – UNWE, Sofia (Bulgaria); Center for Political Research and Documentation (KEPET), Research Laboratory of the Department of Political Science of University of Crete (Greece); Institute of Public Finance – Zagreb (Croatia); Faculty of Tourism and Hospitality Ohrid, University of St. Kliment Ohridski from Bitola (North Macedonia)

ERAZ Conference 2023 Conference Proceedings: ISBN 978-86-80194-72-1, ISSN 2683-5568, DOI: https://doi.org/10.31410/ERAZ.2023

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission. 

Suggested citation

Dias, R., Chambino, M., & Morais da Palma, C. (2023). Cryptocurrency Market: Overreaction to News and Herd Instincts. In V. Bevanda (Ed.), ERAZ Conference – Knowlegde Based Sustainable Development: Vol 9. Conference Proceedings (pp. 67-75). Association of Economists and Managers of the Balkans. https://doi.org/10.31410/ERAZ.2023.67

References

Amini, S., Gebka, B., Hudson, R., & Keasey, K. (2013). A review of the international literature on the short term predictability of stock prices conditional on large prior price changes: Microstructure, behavioral and risk related explanations. In International Review of Fi­nancial Analysis (Vol. 26). https://doi.org/10.1016/j.irfa.2012.04.002 

Antweiler, W., & Frank, M. Z. (2011). Do US Stock Markets Typically Overreact to Corporate News Stories? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.878091 

Bondt, W. F. M. D., & Thaler, R. (1985). Does the Stock Market Overreact? The Journal of Fi­nance, 40(3), 793. https://doi.org/10.2307/2327804 

Chen, M. W., & Zhu, J. (2005). Do Investors in Chinese Stock Market Overreact? Journal of Ac­counting and Finance Research, 13(3).

De Bondt, W. F. M., & Thaler, R. H. (2012). Do Analysts Overreact? In Heuristics and Biases. https://doi.org/10.1017/cbo9780511808098.040 

Diaconaşu, D. E., Mehdian, S., & Stoica, O. (2022). An analysis of investors’ behavior in Bitcoin market. PLoS ONE, 17(3 March). https://doi.org/10.1371/journal.pone.0264522 

Dias, R., Pardal, P., Teixeira, N., & Horta, N. (2022). Tail Risk and Return Predictabili­ty for Europe’s Capital Markets : An Approach in Periods of the. December. https://doi.org/10.4018/978-1-6684-5666-8.ch015 

Dickey, D., & Fuller, W. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057–1072. https://doi.org/10.2307/1912517 

Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics. https://doi.org/10.1016/S0304-4076(03)00092-7 

Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and se­rial independence of regression residuals. Economics Letters, 6(3). https://doi.org/10.1016/0165-1765(80)90024-5  

Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1). https://doi.org/10.1016/S0304-4076(01)00098-7  

Pardal, P., Dias, R., Teixeira, N., & Horta, N. (2022). The Effects of Russia’s 2022 Invasion of Ukraine on Global Markets : An Analysis of Particular Capital and Foreign Exchange Markets. https://doi.org/10.4018/978-1-6684-5666-8.ch014

Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometri­ka, 75(2), 335–346. https://doi.org/10.1093/biomet/75.2.335 

Schaub, M. (2022). Outlier Events in Major Cryptocurrency Markets: Is There Evidence of Over­reaction? Journal of Wealth Management, 24(4). https://doi.org/10.3905/JWM.2021.1.155 

Shiller, R. J. (2022). U.S. Stock Markets 1871-Present and CAPE Ratio. In Online Data Robert Shiller.

Teixeira, N., Dias, R. T., Pardal, P., & Horta, N. R. (2022). Financial Integration and Comove­ments Between Capital Markets and Oil Markets: An Approach During the Russian Inva­sion of Ukraine in 2022. Advances in Human Resources Management and Organizational Development, 240-261. https://doi.org/10.4018/978-1-6684-5666-8.ch013 

Urquhart, A. (2018). What causes the attention of Bitcoin? Economics Letters, 166. https://doi.org/10.1016/j.econlet.2018.02.017  

Vats, A., & Kamaiah, B. (2011). Is There a Random Walk in Indian Foreign Exchange Market? International Journal of Economics and Finance, 3(6), 157–165. https://doi.org/10.5539/ijef.v3n6p157 

Wen, Z., Bouri, E., Xu, Y., & Zhao, Y. (2022). Intraday return predictability in the cryptocur­rency markets: Momentum, reversal, or both. North American Journal of Economics and Finance, 62. https://doi.org/10.1016/j.najef.2022.101733 

Wright, J. H. (2000). Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics. https://doi.org/10.1080/07350015.2000.10524842