IDEAS home Printed from https://ideas.repec.org/a/eee/quaeco/v80y2021icp31-48.html
   My bibliography  Save this article

Features of overreactions in the cryptocurrency market

Author

Listed:
  • Borgards, Oliver
  • Czudaj, Robert L.

Abstract

This paper examines features of overreactions that are able to enhance the prediction quality for twelve cryptocurrencies compared to the US stock market. For this purpose, we perform random forest classifications on the basis of all feature combinations and a customized performance metric to predict overreactions on interday and various intraday price levels. We find that features describing the price development prior to the overreaction have the highest ability to classify an overreaction for different frequencies, indicating volatility clustering and framing effects. During an overreaction, the duration and the price steadiness are important features describing the overreaction itself. Our findings are largely comparable for cryptocurrencies and the US stock market despite the fact that both markets are fundamentally different. However, the returns of an overreaction trading strategy are superior for cryptocurrencies while those of US stocks are consistently negative due to the different size of their price reversals as the key factor for profitably exploiting our empirical findings. In addition, our results show for all assets and frequencies that the prediction results are slightly higher for positive overreactions compared to negative overreactions.

Suggested Citation

  • Borgards, Oliver & Czudaj, Robert L., 2021. "Features of overreactions in the cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 31-48.
    • Handle: RePEc:eee:quaeco:v:80:y:2021:i:c:p:31-48
    DOI: 10.1016/j.qref.2021.01.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062976921000168
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.qref.2021.01.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2019. "Long-term price overreactions: are markets inefficient?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(4), pages 657-680, October.
    2. Guglielmo Maria Caporale & Alex Plastun, 2019. "Price overreactions in the cryptocurrency market," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1137-1155, August.
    3. C. W. J. Granger & Zhuanxin Ding, 1995. "Some Properties of Absolute Return: An Alternative Measure of Risk," Annals of Economics and Statistics, GENES, issue 40, pages 67-91.
    4. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    5. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    6. Borgards, Oliver & Czudaj, Robert L., 2020. "The prevalence of price overreactions in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    7. Gilles Teyssière & Alan P. Kirman (ed.), 2007. "Long Memory in Economics," Springer Books, Springer, number 978-3-540-34625-8, November.
    8. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    9. Amini, Shima & Gebka, Bartosz & Hudson, Robert & Keasey, Kevin, 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," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 1-17.
    10. Chevapatrakul, Thanaset & Mascia, Danilo V., 2019. "Detecting overreaction in the Bitcoin market: A quantile autoregression approach," Finance Research Letters, Elsevier, vol. 30(C), pages 371-377.
    11. Wei Zhang & Pengfei Wang & Xiao Li & Dehua Shen, 2018. "Some stylized facts of the cryptocurrency market," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5950-5965, November.
    12. Rama Cont, 2007. "Volatility Clustering in Financial Markets: Empirical Facts and Agent-Based Models," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 289-309, Springer.
    13. repec:adr:anecst:y:1995:i:40:p:04 is not listed on IDEAS
    14. Xue, Yi & Gençay, Ramazan, 2012. "Trading frequency and volatility clustering," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 760-773.
    15. De Bondt, Werner F M & Thaler, Richard H, 1987. "Further Evidence on Investor Overreaction and Stock Market Seasonalit y," Journal of Finance, American Finance Association, vol. 42(3), pages 557-581, July.
    16. Gil-Alana, Luis Alberiko & Abakah, Emmanuel Joel Aikins & Rojo, María Fátima Romero, 2020. "Cryptocurrencies and stock market indices. Are they related?," Research in International Business and Finance, Elsevier, vol. 51(C).
    17. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    18. Corbet, Shaen & Katsiampa, Paraskevi, 2020. "Asymmetric mean reversion of Bitcoin price returns," International Review of Financial Analysis, Elsevier, vol. 71(C).
    19. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    20. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Xinxing & Gao, Yan & Wang, Ping & Zhu, Bangzhu, 2022. "Examining the overconfidence and overreaction in China’s carbon markets," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 472-489.
    2. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Plastun, Alex & Sibande, Xolani & Gupta, Rangan & Wohar, Mark E., 2021. "Evolution of price effects after one-day abnormal returns in the US stock market," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    2. Borgards, Oliver & Czudaj, Robert L., 2020. "The prevalence of price overreactions in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    3. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.
    4. Sandrine Jacob Leal, 2015. "Fundamentalists, chartists and asset pricing anomalies," Quantitative Finance, Taylor & Francis Journals, vol. 15(11), pages 1837-1850, November.
    5. Sandrine Jacob Leal, 2015. "Fundamentalists, Chartists and Asset pricing anomalies," Post-Print hal-01508002, HAL.
    6. Stefan Nagel, 2013. "Empirical Cross-Sectional Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 167-199, November.
    7. Borgards, Oliver & Czudaj, Robert L. & Hoang, Thi Hong Van, 2021. "Price overreactions in the commodity futures market: An intraday analysis of the Covid-19 pandemic impact," Resources Policy, Elsevier, vol. 71(C).
    8. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    9. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    10. Sonntag, Dominik, 2018. "Die Theorie der fairen geometrischen Rendite [The Theory of Fair Geometric Returns]," MPRA Paper 87082, University Library of Munich, Germany.
    11. Thomas Holtfort, 2019. "From standard to evolutionary finance: a literature survey," Management Review Quarterly, Springer, vol. 69(2), pages 207-232, June.
    12. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    13. Achim Himmelmann & Dirk Schiereck & Marc Simpson & Moritz Zschoche, 2012. "Long-term reactions to large stock price declines and increases in the European stock market: a note on market efficiency," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(2), pages 400-423, April.
    14. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    15. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    16. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    17. Bali, Turan G. & Subrahmanyam, Avanidhar & Wen, Quan, 2021. "Long-term reversals in the corporate bond market," Journal of Financial Economics, Elsevier, vol. 139(2), pages 656-677.
    18. Jiri NOVAK, 2014. "Does Stock Liquidity Explain the Premium for Stock Price Momentum?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(1), pages 79-95, February.
    19. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    20. Ali Fayyaz Munir & Mohd Edil Abd. Sukor & Shahrin Saaid Shaharuddin, 2022. "Adaptive Market Hypothesis and Time-varying Contrarian Effect: Evidence From Emerging Stock Markets of South Asia," SAGE Open, , vol. 12(1), pages 21582440211, January.

    More about this item

    Keywords

    Overreaction; Mean reversion; Cryptocurrency; Random forest; Prediction;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:quaeco:v:80:y:2021:i:c:p:31-48. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620167 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.