IDEAS home Printed from https://ideas.repec.org/p/cer/papers/wp710.html
   My bibliography  Save this paper

A Factor Model for Cryptocurrency Returns

Author

Listed:
  • Daniele Bianchi
  • Mykola Babiak

Abstract

We investigate the dynamics of daily realised returns and risk premiums for a large cross-section of cryptocurrency pairs through the lens of an Instrumented Principal Component Analysis (IPCA) (see Kelly et al., 2019). We show that a model with three latent factors and time-varying factor loadings significantly outperforms a benchmark model with observable risk factors: the total (predictive) R2 from the IPCA is 17.2% (2.9%) for individual returns, against a benchmark 9.6% (-0.02%) obtained from a model with six observable risk factors explored in previous literature. By looking at the characteristics that significantly matter for the dynamics of risk premiums, we provide robust evidence that liquidity, size, reversal, and both market and downside risks represent the main driving factors behind expected returns. These results hold for both individual assets and characteristic-based portfolios, pre and post the Covid-19 outbreak, and for weekly individual and portfolio returns.

Suggested Citation

  • Daniele Bianchi & Mykola Babiak, 2021. "A Factor Model for Cryptocurrency Returns," CERGE-EI Working Papers wp710, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    • Handle: RePEc:cer:papers:wp710
    as

    Download full text from publisher

    File URL: http://www.cerge-ei.cz/pdf/wp/Wp710.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schilling, Linda & Uhlig, Harald, 2019. "Some simple bitcoin economics," Journal of Monetary Economics, Elsevier, vol. 106(C), pages 16-26.
    2. Kelly, Bryan T. & Pruitt, Seth & Su, Yinan, 2019. "Characteristics are covariances: A unified model of risk and return," Journal of Financial Economics, Elsevier, vol. 134(3), pages 501-524.
    3. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta & Albert J. Menkveld, 2023. "Equilibrium Bitcoin Pricing," Journal of Finance, American Finance Association, vol. 78(2), pages 967-1014, April.
    4. Lin William Cong & Zhiguo He & Jiasun Li & Wei Jiang, 2021. "Decentralized Mining in Centralized Pools [Concentrating on the fall of the labor share]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1191-1235.
    5. Joseph Abadi & Markus Brunnermeier, 2018. "Blockchain Economics," NBER Working Papers 25407, National Bureau of Economic Research, Inc.
    6. Lewellen, Jonathan & Nagel, Stefan & Shanken, Jay, 2010. "A skeptical appraisal of asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 175-194, May.
    7. Chiu, Jonathan & Koeppl, Thorsten V, 2017. "The economics of cryptocurrencies – bitcoin and beyond," Working Paper Series 6688, Victoria University of Wellington, School of Economics and Finance.
    8. Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March.
    9. Jonathan Chiu & Thorsten V. Koeppl, 2017. "The Economics Of Cryptocurrencies - Bitcoin And Beyond," Working Paper 1389, Economics Department, Queen's University.
    10. Michael Sockin & Wei Xiong, 2020. "A Model of Cryptocurrencies," NBER Working Papers 26816, National Bureau of Economic Research, Inc.
    11. Lin William Cong & Zhiguo He, 2019. "Blockchain Disruption and Smart Contracts," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1754-1797.
    12. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    13. Stefan Nagel, 2012. "Evaporating Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 25(7), pages 2005-2039.
    14. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    15. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    16. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
    17. Brauneis, Alexander & Mestel, Roland & Riordan, Ryan & Theissen, Erik, 2021. "How to measure the liquidity of cryptocurrency markets?," Journal of Banking & Finance, Elsevier, vol. 124(C).
    18. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2019. "Common Risk Factors in Cryptocurrency," NBER Working Papers 25882, National Bureau of Economic Research, Inc.
    19. Narasimhan Jegadeesh & Sheridan Titman, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
    20. Moskowitz, Tobias J. & Ooi, Yao Hua & Pedersen, Lasse Heje, 2012. "Time series momentum," Journal of Financial Economics, Elsevier, vol. 104(2), pages 228-250.
    21. Farshid Abdi & Angelo Ranaldo, 2017. "A Simple Estimation of Bid-Ask Spreads from Daily Close, High, and Low Prices," The Review of Financial Studies, Society for Financial Studies, vol. 30(12), pages 4437-4480.
    22. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    23. Borri, Nicola & Shakhnov, Kirill, 2020. "Regulation spillovers across cryptocurrency markets," Finance Research Letters, Elsevier, vol. 36(C).
    24. Lin William Cong & Ye Li & Neng Wang, 2021. "Tokenomics: Dynamic Adoption and Valuation [The demand of liquid assets with uncertain lumpy expenditures]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1105-1155.
    25. Warren E. Weber, 2016. "A Bitcoin Standard: Lessons from the Gold Standard," Staff Working Papers 16-14, Bank of Canada.
    26. Bianchi, Daniele & Babiak, Mykola, 2022. "On the performance of cryptocurrency funds," Journal of Banking & Finance, Elsevier, vol. 138(C).
    27. Shane A. Corwin & Paul Schultz, 2012. "A Simple Way to Estimate Bid‐Ask Spreads from Daily High and Low Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 719-760, April.
    28. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    29. Daniel, Kent & Titman, Sheridan, 2012. "Testing Factor-Model Explanations of Market Anomalies," Critical Finance Review, now publishers, vol. 1(1), pages 103-139, January.
    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. Bianchi, Daniele & Babiak, Mykola, 2022. "On the performance of cryptocurrency funds," Journal of Banking & Finance, Elsevier, vol. 138(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. Dong, Bingbing & Jiang, Lei & Liu, Jinyu & Zhu, Yifeng, 2022. "Liquidity in the cryptocurrency market and commonalities across anomalies," International Review of Financial Analysis, Elsevier, vol. 81(C).
    2. Bianchi, Daniele & Babiak, Mykola & Dickerson, Alexander, 2022. "Trading volume and liquidity provision in cryptocurrency markets," Journal of Banking & Finance, Elsevier, vol. 142(C).
    3. Yukun Liu & Aleh Tsyvinski, 2018. "Risks and Returns of Cryptocurrency," NBER Working Papers 24877, National Bureau of Economic Research, Inc.
    4. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2019. "Common Risk Factors in Cryptocurrency," NBER Working Papers 25882, National Bureau of Economic Research, Inc.
    5. Jermann, Urban J., 2021. "Cryptocurrencies and Cagan’s model of hyperinflation," Journal of Macroeconomics, Elsevier, vol. 69(C).
    6. Bianchi, Daniele & Babiak, Mykola, 2022. "On the performance of cryptocurrency funds," Journal of Banking & Finance, Elsevier, vol. 138(C).
    7. Patton, Andrew J. & Weller, Brian M., 2020. "What you see is not what you get: The costs of trading market anomalies," Journal of Financial Economics, Elsevier, vol. 137(2), pages 515-549.
    8. Ye Li & Simon Mayer & Simon Mayer, 2021. "Money Creation in Decentralized Finance: A Dynamic Model of Stablecoin and Crypto Shadow Banking," CESifo Working Paper Series 9260, CESifo.
    9. Korniotis, George & Bhambhwani, Siddharth & Delikouras, Stefanos, 2019. "Blockchain Characteristics and the Cross-Section of Cryptocurrency Returns," CEPR Discussion Papers 13724, C.E.P.R. Discussion Papers.
    10. 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.
    11. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, December.
    12. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "A diagnostic criterion for approximate factor structure," Journal of Econometrics, Elsevier, vol. 212(2), pages 503-521.
    13. Brunnermeier, Markus & Abadi, Joseph, 2018. "Blockchain Economics," CEPR Discussion Papers 13420, C.E.P.R. Discussion Papers.
    14. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta & Albert J. Menkveld, 2023. "Equilibrium Bitcoin Pricing," Journal of Finance, American Finance Association, vol. 78(2), pages 967-1014, April.
    15. Cong, Lin William & Li, Ye & Wang, Neng, 2022. "Token-based platform finance," Journal of Financial Economics, Elsevier, vol. 144(3), pages 972-991.
    16. Ma, Tian & Leong, Wen Jun & Jiang, Fuwei, 2023. "A latent factor model for the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 87(C).
    17. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2020. "Joint Extreme events in equity returns and liquidity and their cross-sectional pricing implications," Journal of Banking & Finance, Elsevier, vol. 115(C).
    18. Zhang, Wei & Li, Yi & Xiong, Xiong & Wang, Pengfei, 2021. "Downside risk and the cross-section of cryptocurrency returns," Journal of Banking & Finance, Elsevier, vol. 133(C).
    19. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "Estimation of large dimensional conditional factor models in finance," Working Papers unige:125031, University of Geneva, Geneva School of Economics and Management.
    20. Kelly, Bryan T. & Pruitt, Seth & Su, Yinan, 2019. "Characteristics are covariances: A unified model of risk and return," Journal of Financial Economics, Elsevier, vol. 134(3), pages 501-524.

    More about this item

    Keywords

    cryptocurrency markets; instrumented PCA; asset pricing; factor models; risk premiums;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cer:papers:wp710. 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: Lucie Vasiljevova (email available below). General contact details of provider: https://edirc.repec.org/data/eiacacz.html .

    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.