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Investing with Cryptocurrencies—a Liquidity Constrained Investment Approach

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  • Simon Trimborn
  • Mingyang Li
  • Wolfgang Karl Härdle

Abstract

Cryptocurrencies have left the dark side of the finance universe and become an object of study for asset and portfolio management. Since they have low liquidity compared to traditional assets, one needs to take into account liquidity issues when adding them to a portfolio. We propose a Liquidity Bounded Risk-return Optimization (LIBRO) approach, which is a combination of risk-return portfolio optimization under liquidity constraints. Cryptocurrencies are included in portfolios formed with stocks of the S&P 100, US Bonds, and commodities. We illustrate the importance of the liquidity constraints in an in-sample and out-of-sample study. LIBRO improves the weight optimization in the sense that it only adds cryptocurrencies in tradable amounts depending on the intended investment amount. The returns greatly increase compared to portfolios consisting only of traditional assets. We show that including cryptocurrencies in a portfolio can indeed improve its risk–return trade-off.

Suggested Citation

  • Simon Trimborn & Mingyang Li & Wolfgang Karl Härdle, 2020. "Investing with Cryptocurrencies—a Liquidity Constrained Investment Approach," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 280-306.
    • Handle: RePEc:oup:jfinec:v:18:y:2020:i:2:p:280-306.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbz016
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    1. Serge Darolles & Christian Gouriéroux & Emmanuelle Jay, 2012. "Robust Portfolio Allocation with Systematic Risk Contribution Restrictions," Working Papers 2012-35, Center for Research in Economics and Statistics.
    2. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    3. Marie Briere & Kim Oosterlinck & Ariane Szafarz, 2015. "Virtual Currency, Tangible Return: Portfolio Diversification with Bitcoins," Post-Print CEB, ULB -- Universite Libre de Bruxelles, vol. 16(6), pages 365-373.
    4. Green, Richard C & Hollifield, Burton, 1992. "When Will Mean-Variance Efficient Portfolios Be Well Diversified?," Journal of Finance, American Finance Association, vol. 47(5), pages 1785-1809, December.
    5. repec:bla:jfinan:v:58:y:2003:i:4:p:1651-1684 is not listed on IDEAS
    6. Härdle, Wolfgang Karl & Trimborn, Simon, 2015. "CRIX or evaluating blockchain based currencies," SFB 649 Discussion Papers 2015-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Elendner, Hermann & Trimborn, Simon & Ong, Bobby & Lee, Teik Ming, 2016. "The cross-section of crypto-currencies as financial assets: An overview," SFB 649 Discussion Papers 2016-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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    More about this item

    Keywords

    asset classes; blockchain; crypto-currency; CRIX; portfolio investment;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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