IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i9p1351-d1385677.html
   My bibliography  Save this article

Optimizing Cryptocurrency Returns: A Quantitative Study on Factor-Based Investing

Author

Listed:
  • Phumudzo Lloyd Seabe

    (Department of Mathematics and Applied Mathematics, Sefako Makgatho Health Sciences University, Pretoria 0204, South Africa)

  • Claude Rodrigue Bambe Moutsinga

    (Department of Mathematics and Applied Mathematics, Sefako Makgatho Health Sciences University, Pretoria 0204, South Africa)

  • Edson Pindza

    (College of Economic and Management Sciences, Department of Decision Sciences, University of South Africa, Pretoria 0002, South Africa)

Abstract

This study explores cryptocurrency investment strategies by adapting the robust framework of factor investing, traditionally applied in equity markets, to the distinctive landscape of cryptocurrency assets. It conducts an in-depth examination of 31 prominent cryptocurrencies from December 2017 to December 2023, employing the Fama–MacBeth regression method and portfolio regressions to assess the predictive capabilities of market, size, value, and momentum factors, adjusted for the unique characteristics of the cryptocurrency market. These characteristics include high volatility and continuous trading, which differ markedly from those of traditional financial markets. To address the challenges posed by the perpetual operation of cryptocurrency trading, this study introduces an innovative rebalancing strategy that involves weekly adjustments to accommodate the market’s constant fluctuations. Additionally, to mitigate issues like autocorrelation and heteroskedasticity in financial time series data, this research applies the Newey–West standard error approach, enhancing the robustness of regression analyses. The empirical results highlight the significant predictive power of momentum and value factors in forecasting cryptocurrency returns, underscoring the importance of tailoring conventional investment frameworks to the cryptocurrency context. This study not only investigates the applicability of factor investing in the rapidly evolving cryptocurrency market, but also enriches the financial literature by demonstrating the effectiveness of combining Fama–MacBeth cross-sectional analysis with portfolio regressions, supported by Newey–West standard errors, in mastering the complexities of digital asset investments.

Suggested Citation

  • Phumudzo Lloyd Seabe & Claude Rodrigue Bambe Moutsinga & Edson Pindza, 2024. "Optimizing Cryptocurrency Returns: A Quantitative Study on Factor-Based Investing," Mathematics, MDPI, vol. 12(9), pages 1-28, April.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:9:p:1351-:d:1385677
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/9/1351/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/9/1351/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Frazzini, Andrea & Pedersen, Lasse Heje, 2014. "Betting against beta," Journal of Financial Economics, Elsevier, vol. 111(1), pages 1-25.
    2. Fama, Eugene F. & French, Kenneth R., 2012. "Size, value, and momentum in international stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 457-472.
    3. Sha Wang & Jean-Philippe Vergne, 2017. "Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-17, January.
    4. Caporale, Guglielmo Maria & Gil-Alana, Luis & Plastun, Alex, 2018. "Persistence in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 46(C), pages 141-148.
    5. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    6. Tsang, Kwok Ping & Yang, Zichao, 2021. "The market for bitcoin transactions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    7. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    8. Samet Gunay, 2019. "Impact of Public Information Arrivals on Cryptocurrency Market: A Case of Twitter Posts on Ripple," East Asian Economic Review, Korea Institute for International Economic Policy, vol. 23(2), pages 149-168.
    9. 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.
    10. Eugene Tartakovsky & Ksenia Plesovskikh & Anastasiia Sarmakeeva & Alexander Bibik, 2020. "Autocorrelation of returns in major cryptocurrency markets," Papers 2003.13517, arXiv.org, revised Mar 2020.
    11. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    12. Bariviera, Aurelio F. & Basgall, María José & Hasperué, Waldo & Naiouf, Marcelo, 2017. "Some stylized facts of the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 82-90.
    13. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    14. Okunev, John & White, Derek, 2003. "Do Momentum-Based Strategies Still Work in Foreign Currency Markets?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(2), pages 425-447, June.
    15. Feng, Wenjun & Wang, Yiming & Zhang, Zhengjun, 2018. "Informed trading in the Bitcoin market," Finance Research Letters, Elsevier, vol. 26(C), pages 63-70.
    16. Barroso, Pedro & Santa-Clara, Pedro, 2015. "Momentum has its moments," Journal of Financial Economics, Elsevier, vol. 116(1), pages 111-120.
    17. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    18. Lee Alan Smales, 2020. "One Cryptocurrency to Explain Them All? Understanding the Importance of Bitcoin in Cryptocurrency Returns," Economic Papers, The Economic Society of Australia, vol. 39(2), pages 118-132, June.
    19. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    20. Blitz, D.C. & van Vliet, P., 2007. "The Volatility Effect: Lower Risk without Lower Return," ERIM Report Series Research in Management ERS-2007-044-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    Full references (including those not matched with items on IDEAS)

    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. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, June.
    2. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    3. Ciciretti, Rocco & Dalò, Ambrogio & Dam, Lammertjan, 2023. "The contributions of betas versus characteristics to the ESG premium," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 104-124.
    4. Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
    5. Hanauer, Matthias X. & Lauterbach, Jochim G., 2019. "The cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 38(C), pages 265-286.
    6. Cakici, Nusret & Zaremba, Adam, 2023. "Recency bias and the cross-section of international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    7. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    8. Bradrania, Reza & Veron, Jose Francisco & Wu, Winston, 2023. "The beta anomaly and the quality effect in international stock markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    9. Ruanmin Cao & Lajos Horváth & Zhenya Liu & Yuqian Zhao, 2020. "A study of data-driven momentum and disposition effects in the Chinese stock market by functional data analysis," Review of Quantitative Finance and Accounting, Springer, vol. 54(1), pages 335-358, January.
    10. Israel, Ronen & Moskowitz, Tobias J., 2013. "The role of shorting, firm size, and time on market anomalies," Journal of Financial Economics, Elsevier, vol. 108(2), pages 275-301.
    11. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    12. Cakici, Nusret & Zaremba, Adam, 2021. "Liquidity and the cross-section of international stock returns," Journal of Banking & Finance, Elsevier, vol. 127(C).
    13. Ailie Charteris & Mukashema Rwishema & Tafadzwa-Hidah Chidede, 2018. "Asset Pricing and Momentum: A South African Perspective," Journal of African Business, Taylor & Francis Journals, vol. 19(1), pages 62-85, January.
    14. Cyril Bachelard & Apostolos Chalkis & Vissarion Fisikopoulos & Elias Tsigaridas, 2022. "Randomized geometric tools for anomaly detection in stock markets," Papers 2205.03852, arXiv.org, revised May 2022.
    15. Sebastien Valeyre, 2020. "Refined model of the covariance/correlation matrix between securities," Papers 2001.08911, arXiv.org.
    16. Becchetti, Leonardo & Ciciretti, Rocco & Dalò, Ambrogio, 2018. "Fishing the Corporate Social Responsibility risk factors," Journal of Financial Stability, Elsevier, vol. 37(C), pages 25-48.
    17. Jank, Stephan, 2015. "Specialized human capital, unemployment risk, and the value premium," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113214, Verein für Socialpolitik / German Economic Association.
    18. Pawe³ Sakowski & Robert Œlepaczuk & Mateusz Wywia³, 2016. "Cross-Sectional Returns With Volatility Regimes From A Diverse Portfolio Of Emerging And Developed Equity Indices," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 12(2), pages 23-35, October.
    19. Zaremba Adam & Konieczka Przemysław, 2017. "Size, Value, and Momentum in Polish Equity Returns: Local or International Factors?," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 53(3), pages 26-47, September.
    20. Barroso, Pedro & Detzel, Andrew & Maio, Paulo, 2025. "The volatility puzzle of the beta anomaly," Journal of Financial Economics, Elsevier, vol. 165(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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:gam:jmathe:v:12:y:2024:i:9:p:1351-:d:1385677. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.