IDEAS home Printed from https://ideas.repec.org/p/cer/papers/wp672.html
   My bibliography  Save this paper

On the Performance of Cryptocurrency Funds

Author

Listed:
  • Daniele Bianchi
  • Mykola Babiak

Abstract

We investigate the performance of funds that specialise in cryptocurrency markets. In doing so, we contribute to a growing literature that aims to understand the role of digital assets as an investment. Methodologically, we implement a novel bootstrap approach that samples jointly the cross-sectional distribution of alphas and controls for the nonnormality of fund returns and their within-strategy correlations. Empirically, we find that a sizable minority of managers are able to cover their costs and generate large alphas. However, there is weak statistical evidence of managers’ skills once withinstrategy common variation in returns is taken into account.

Suggested Citation

  • Daniele Bianchi & Mykola Babiak, 2020. "On the Performance of Cryptocurrency Funds," CERGE-EI Working Papers wp672, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    • Handle: RePEc:cer:papers:wp672
    as

    Download full text from publisher

    File URL: http://www.cerge-ei.cz/pdf/wp/Wp672.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Michael C. Jensen, 1968. "The Performance Of Mutual Funds In The Period 1945–1964," Journal of Finance, American Finance Association, vol. 23(2), pages 389-416, May.
    2. Huij, Joop & Verbeek, Marno, 2007. "Cross-sectional learning and short-run persistence in mutual fund performance," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 973-997, March.
    3. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    4. Aleksandar Andonov & Rob M.M.J. Bauer & K.J. Martijn Cremers, 2017. "Pension Fund Asset Allocation and Liability Discount Rates," The Review of Financial Studies, Society for Financial Studies, vol. 30(8), pages 2555-2595.
    5. Russ Wermers, 2000. "Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses," Journal of Finance, American Finance Association, vol. 55(4), pages 1655-1703, August.
    6. Marcin Kacperczyk & Amit Seru, 2007. "Fund Manager Use of Public Information: New Evidence on Managerial Skills," Journal of Finance, American Finance Association, vol. 62(2), pages 485-528, April.
    7. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2011. "Recent trends in trading activity and market quality," Journal of Financial Economics, Elsevier, vol. 101(2), pages 243-263, August.
    8. S. P. Kothari & Jerold B. Warner, 2001. "Evaluating Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 56(5), pages 1985-2010, October.
    9. Elton, Edwin J & Gruber, Martin J & Blake, Christopher R, 1996. "Survivorship Bias and Mutual Fund Performance," The Review of Financial Studies, Society for Financial Studies, vol. 9(4), pages 1097-1120.
    10. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    11. Gruber, Martin J, 1996. "Another Puzzle: The Growth in Activity Managed Mutual Funds," Journal of Finance, American Finance Association, vol. 51(3), pages 783-810, July.
    12. Quinn McNemar, 1947. "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, Springer;The Psychometric Society, vol. 12(2), pages 153-157, June.
    13. Harry Mamaysky & Matthew Spiegel & Hong Zhang, 2007. "Improved Forecasting of Mutual Fund Alphas and Betas," Review of Finance, European Finance Association, vol. 11(3), pages 359-400.
    14. Hanno Lustig & Nikolai Roussanov & Adrien Verdelhan, 2011. "Common Risk Factors in Currency Markets," The Review of Financial Studies, Society for Financial Studies, vol. 24(11), pages 3731-3777.
    15. 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.
    16. Glode, Vincent, 2011. "Why mutual funds "underperform"," Journal of Financial Economics, Elsevier, vol. 99(3), pages 546-559, March.
    17. Robert Novy‐Marx & Joshua Rauh, 2011. "Public Pension Promises: How Big Are They and What Are They Worth?," Journal of Finance, American Finance Association, vol. 66(4), pages 1211-1249, August.
    18. Jonathan B. Berk & Richard C. Green, 2004. "Mutual Fund Flows and Performance in Rational Markets," Journal of Political Economy, University of Chicago Press, vol. 112(6), pages 1269-1295, December.
    19. Berk, Jonathan B. & van Binsbergen, Jules H., 2016. "Assessing asset pricing models using revealed preference," Journal of Financial Economics, Elsevier, vol. 119(1), pages 1-23.
    20. Richard A. Ippolito, 1989. "Efficiency with Costly Information: A Study of Mutual Fund Performance, 1965–1984," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 104(1), pages 1-23.
    21. Avramov, Doron & Wermers, Russ, 2006. "Investing in mutual funds when returns are predictable," Journal of Financial Economics, Elsevier, vol. 81(2), pages 339-377, August.
    22. Berk, Jonathan B. & van Binsbergen, Jules H., 2015. "Measuring skill in the mutual fund industry," Journal of Financial Economics, Elsevier, vol. 118(1), pages 1-20.
    23. Marcin Kacperczyk & Stijn Van Nieuwerburgh & Laura Veldkamp, 2014. "Time-Varying Fund Manager Skill," Journal of Finance, American Finance Association, vol. 69(4), pages 1455-1484, August.
    24. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2015. "Scale and skill in active management," Journal of Financial Economics, Elsevier, vol. 116(1), pages 23-45.
    25. Stefan Nagel, 2012. "Evaporating Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 25(7), pages 2005-2039.
    26. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," LSE Research Online Documents on Economics 100409, London School of Economics and Political Science, LSE Library.
    27. 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.
    28. Conrad, Jennifer & Wahal, Sunil & Xiang, Jin, 2015. "High-frequency quoting, trading, and the efficiency of prices," Journal of Financial Economics, Elsevier, vol. 116(2), pages 271-291.
    29. Robert Kosowski & Allan Timmermann & Russ Wermers & Hal White, 2006. "Can Mutual Fund “Stars” Really Pick Stocks? New Evidence from a Bootstrap Analysis," Journal of Finance, American Finance Association, vol. 61(6), pages 2551-2595, December.
    30. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2019. "Common Risk Factors in Cryptocurrency," NBER Working Papers 25882, National Bureau of Economic Research, Inc.
    31. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    32. Brown, Stephen J, et al, 1992. "Survivorship Bias in Performance Studies," The Review of Financial Studies, Society for Financial Studies, vol. 5(4), pages 553-580.
    33. Lukas Menkhoff & Lucio Sarno & Maik Schmeling & Andreas Schrimpf, 2016. "Information Flows in Foreign Exchange Markets: Dissecting Customer Currency Trades," Journal of Finance, American Finance Association, vol. 71(2), pages 601-634, April.
    34. Joop Huij & Marno Verbeek, 2009. "On the Use of Multifactor Models to Evaluate Mutual Fund Performance," Financial Management, Financial Management Association International, vol. 38(1), pages 75-102, March.
    35. 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.
    36. 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.
    37. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross‐Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
    38. Kenneth R. French, 2008. "Presidential Address: The Cost of Active Investing," Journal of Finance, American Finance Association, vol. 63(4), pages 1537-1573, August.
    39. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
    40. Alexander Dyck & Karl V. Lins & Lukasz Pomorski, 2013. "Does Active Management Pay? New International Evidence," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 3(2), pages 200-228.
    41. Yukun Liu & Aleh Tsyvinski, 2018. "Risks and Returns of Cryptocurrency," NBER Working Papers 24877, National Bureau of Economic Research, Inc.
    42. Brad M. Barber & Xing Huang & Terrance Odean, 2016. "Which Factors Matter to Investors? Evidence from Mutual Fund Flows," The Review of Financial Studies, Society for Financial Studies, vol. 29(10), pages 2600-2642.
    43. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," Journal of Financial Economics, Elsevier, vol. 135(2), pages 293-319.
    44. Russ Wermers, 2000. "Mutual Fund Performance: An Empirical Decomposition into Stock‐Picking Talent, Style, Transactions Costs, and Expenses," Journal of Finance, American Finance Association, vol. 55(4), pages 1655-1695, August.
    45. Anthony W. Lynch & David K. Musto, 2003. "How Investors Interpret Past Fund Returns," Journal of Finance, American Finance Association, vol. 58(5), pages 2033-2058, October.
    46. Teodor Dyakov & Hao Jiang & Marno Verbeek, 2020. "Trade Less and Exit Overcrowded Markets: Lessons from International Mutual Funds," Review of Finance, European Finance Association, vol. 24(3), pages 677-731.
    47. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    48. David Yermack, 2013. "Is Bitcoin a Real Currency? An economic appraisal," NBER Working Papers 19747, National Bureau of Economic Research, Inc.
    49. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    50. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    51. Daniele Bianchi & Massimo Guidolin & Manuela Pedio, 2020. "Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets," BAFFI CAREFIN Working Papers 20143, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    52. Marcin Kacperczyk & Clemens Sialm & Lu Zheng, 2005. "On the Industry Concentration of Actively Managed Equity Mutual Funds," Journal of Finance, American Finance Association, vol. 60(4), pages 1983-2011, August.
    53. Malkiel, Burton G, 1995. "Returns from Investing in Equity Mutual Funds 1971 to 1991," Journal of Finance, American Finance Association, vol. 50(2), pages 549-572, June.
    54. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    55. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    56. 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.
    57. Moneta, Fabio, 2015. "Measuring bond mutual fund performance with portfolio characteristics," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 223-242.
    58. 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.
    59. Nicolas P. B. Bollen & Jeffrey A. Busse, 2001. "On the Timing Ability of Mutual Fund Managers," Journal of Finance, American Finance Association, vol. 56(3), pages 1075-1094, June.
    60. Jeffrey A. Busse & Paul J. Irvine, 2006. "Bayesian Alphas and Mutual Fund Persistence," Journal of Finance, American Finance Association, vol. 61(5), pages 2251-2288, October.
    61. Juhani T. Linnainmaa, 2013. "Reverse Survivorship Bias," Journal of Finance, American Finance Association, vol. 68(3), pages 789-813, June.
    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. Victoria Dobrynskaya & Mikhail Dubrovskiy, 2022. "Cryptocurrencies Meet Equities: Risk Factors And Asset Pricing Relationships," HSE Working papers WP BRP 86/FE/2022, National Research University Higher School of Economics.
    2. Siu Hin Tang & Mathieu Rosenbaum & Chao Zhou, 2023. "Forecasting Volatility with Machine Learning and Rough Volatility: Example from the Crypto-Winter," Papers 2311.04727, arXiv.org, revised Feb 2024.
    3. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Bianchi, Daniele & Babiak, Mykola & Dickerson, Alexander, 2022. "Trading volume and liquidity provision in cryptocurrency markets," Journal of Banking & Finance, Elsevier, vol. 142(C).
    5. 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.
    6. Dombrowski, Niclas & Drobetz, Wolfgang & Momtaz, Paul P., 2023. "Performance measurement of crypto funds," Economics Letters, Elsevier, vol. 228(C).
    7. Ben Khelifa, Soumaya & Guesmi, Khaled & Urom, Christian, 2021. "Exploring the relationship between cryptocurrencies and hedge funds during COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 76(C).
    8. Kim, Jang Ho, 2022. "Analyzing diversification benefits of cryptocurrencies through backfill simulation," Finance Research Letters, Elsevier, vol. 50(C).
    9. Daniele Bianchi & Massimo Guidolin & Manuela Pedio, 2020. "Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets," BAFFI CAREFIN Working Papers 20143, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    10. Andreas Renard Widarto & Harjum Muharam & Sugeng Wahyudi & Irene Rini Demi Pangestuti, 2022. "ASEAN-5 and Crypto Hedge Fund: Dynamic Portfolio Approach," SAGE Open, , vol. 12(2), pages 21582440221, April.

    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. Matallín-Sáez, Juan Carlos & Soler-Domínguez, Amparo & Tortosa-Ausina, Emili, 2016. "On the robustness of persistence in mutual fund performance," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 192-231.
    2. Ferson, Wayne E., 2013. "Investment Performance: A Review and Synthesis," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 969-1010, Elsevier.
    3. Ľuboš Pástor & Robert F. Stambaugh & Lucian A. Taylor, 2017. "Do Funds Make More When They Trade More?," Journal of Finance, American Finance Association, vol. 72(4), pages 1483-1528, August.
    4. Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can Machine Learning Help to Select Portfolios of Mutual Funds?," Working Papers 1245, Barcelona School of Economics.
    5. Brown, Stephen J. & Sotes-Paladino, Juan & Wang, Jiaguo(George) & Yao, Yaqiong, 2017. "Starting on the wrong foot: Seasonality in mutual fund performance," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 133-150.
    6. Ekholm, Anders G., 2012. "Portfolio returns and manager activity: How to decompose tracking error into security selection and market timing," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 349-358.
    7. Livingston, Miles & Yao, Ping & Zhou, Lei, 2019. "The volatility of mutual fund performance," Journal of Economics and Business, Elsevier, vol. 104(C), pages 1-1.
    8. 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.
    9. Cai, Biqing & Cheng, Tingting & Yan, Cheng, 2018. "Time-varying skills (versus luck) in U.S. active mutual funds and hedge funds," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 81-106.
    10. Huang, Rong & Pilbeam, Keith & Pouliot, William, 2021. "Do actively managed US mutual funds produce positive alpha?," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 472-492.
    11. Elton, Edwin J. & Gruber, Martin J., 2013. "Mutual Funds," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1011-1061, Elsevier.
    12. Berk, Jonathan B. & van Binsbergen, Jules H., 2015. "Measuring skill in the mutual fund industry," Journal of Financial Economics, Elsevier, vol. 118(1), pages 1-20.
    13. Lee, Jaeram & Jeon, Hyunglae & Kang, Jangkoo & Lee, Changjun, 2020. "Do actively managed mutual funds exploit stock market mispricing?," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    14. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2015. "Scale and skill in active management," Journal of Financial Economics, Elsevier, vol. 116(1), pages 23-45.
    15. Andrew Clare & Mariana Clare, 2019. "An examination of ex ante fund performance: identifying indicators of future performance," Journal of Asset Management, Palgrave Macmillan, vol. 20(3), pages 175-195, May.
    16. Jiang, Hao & Verardo, Michela, 2013. "Does herding behavior reveal skill? An analysis of mutual fund performance," LSE Research Online Documents on Economics 119034, London School of Economics and Political Science, LSE Library.
    17. Ferson, Wayne & Mo, Haitao, 2016. "Performance measurement with selectivity, market and volatility timing," Journal of Financial Economics, Elsevier, vol. 121(1), pages 93-110.
    18. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2008. "UK mutual fund performance: Skill or luck?," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 613-634, September.
    19. Dahlquist, Magnus & Odegaard, Bernt Arne, 2018. "A Review of Norges Bank's Active Management of the Government Pension Fund Global," UiS Working Papers in Economics and Finance 2018/1, University of Stavanger.
    20. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2016. "A review of behavioural and management effects in mutual fund performance," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 162-176.

    More about this item

    Keywords

    cryptocurrency; investments; active management; alternative investments; boot-strap methods; bitcoin;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    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:wp672. 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.