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Investing with Cryptocurrencies—a Liquidity Constrained Investment Approach

Author

Listed:
  • 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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    Cited by:

    1. Christoph J. Börner & Ingo Hoffmann & Jonas Krettek & Tim Schmitz, 2022. "Bitcoin: like a satellite or always hardcore? A core–satellite identification in the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 310-321, July.
    2. Pascal Bruhn & Dietmar Ernst, 2022. "Assessing the Risk Characteristics of the Cryptocurrency Market: A GARCH-EVT-Copula Approach," JRFM, MDPI, vol. 15(8), pages 1-28, August.
    3. Zdravka Aljinović & Branka Marasović & Tea Šestanović, 2021. "Cryptocurrency Portfolio Selection—A Multicriteria Approach," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    4. Moreno, David & Antoli, Marcos & Quintana, David, 2022. "Benefits of investing in cryptocurrencies when liquidity is a factor," Research in International Business and Finance, Elsevier, vol. 63(C).
    5. Buse, Rebekka & Görgen, Konstantin & Schienle, Melanie, 2025. "Predicting value at risk for cryptocurrencies with generalized random forests," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1199-1222.
    6. Chunling Li & Nosherwan Khaliq & Leslie Chinove & Usama Khaliq & József Popp & Judit Oláh, 2023. "Cryptocurrency Acceptance Model to Analyze Consumers’ Usage Intention: Evidence From Pakistan," SAGE Open, , vol. 13(1), pages 21582440231, March.
    7. Danial Saef & Odett Nagy & Sergej Sizov & Wolfgang Karl Härdle, 2025. "Correction: Understanding temporal dynamics of jumps in cryptocurrency markets: evidence from tick-by-tick data," Digital Finance, Springer, vol. 7(2), pages 297-297, June.
    8. Gradojevic, Nikola & Tsiakas, Ilias, 2021. "Volatility cascades in cryptocurrency trading," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 252-265.
    9. Christian M. Hafner & Sabrine Majeri, 2022. "Analysis of cryptocurrency connectedness based on network to transaction volume ratios," Digital Finance, Springer, vol. 4(2), pages 187-216, September.
    10. Abrar, Afsheen & Naeem, Muhammad Abubakr & Karim, Sitara & Lucey, Brian M. & Vigne, Samuel A., 2024. "Shining in or fading out: Do precious metals sparkle for cryptocurrencies?," Resources Policy, Elsevier, vol. 90(C).
    11. Walid M. A. Ahmed, 2024. "On the robust drivers of cryptocurrency liquidity: the case of Bitcoin," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-32, December.
    12. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    13. Meyer, Eva Andrea & Welpe, Isabell M. & Sandner, Philipp, 2024. "Testing the credibility of crypto influencers: An event study on Bitcoin," Finance Research Letters, Elsevier, vol. 60(C).
    14. Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
    15. Jia, Yuecheng & Wu, Yangru & Yan, Shu & Liu, Yuzheng, 2023. "A seesaw effect in the cryptocurrency market: Understanding the return cross predictability of cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 74(C).
    16. Wei Zhang & Yi Li, 2023. "Liquidity risk and expected cryptocurrency returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 472-492, January.
    17. Christoph J. Borner & Ingo Hoffmann & Jonas Krettek & Lars M. Kurzinger & Tim Schmitz, 2021. "Bitcoin: Like a Satellite or Always Hardcore? A Core-Satellite Identification in the Cryptocurrency Market," Papers 2105.12336, arXiv.org.
    18. Afzol Husain & Kwang-Jing Yii & Chorng Yuan Fung & Richard Busulwa, 2025. "Portfolio risk of cryptocurrency inclusion: a comparison among conventional cryptocurrencies and asset-backed cryptocurrencies," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 15(3), pages 687-739, September.
    19. Santhoshi Gondesi & Kameswari Jada & Ramesh Palisetty & Veena Ishwarappa Bhavikatti & Omnamasivaya Boddeda & Chaitanya Gorli & Tejaswini Bastray & Sony Hiremath, 2024. "Digital currency: an empirical study analyzing its effectiveness in the banking sector," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(11), pages 5182-5195, November.

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    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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