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On the Performance of Cryptocurrency Funds

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  • 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
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    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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.

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    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

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