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Investing with cryptocurrencies - A liquidity constrained investment approach

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  • Trimborn, Simon
  • Li, Mingyang
  • Härdle, Wolfgang Karl

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 a low liquidity compared to traditional assets, one needs to take into account liquidity issues when one puts them into the same portfolio. We propose use a Liquidity Bounded Risk-return Optimization (LIBRO) approach, which is a combination of the Markowitz framework under the liquidity constraints. The results show that cryptocurrencies add value to a portfolio and the optimization approach is even able to increase the return of a portfolio and lower the volatility risk.

Suggested Citation

  • Trimborn, Simon & Li, Mingyang & Härdle, Wolfgang Karl, 2017. "Investing with cryptocurrencies - A liquidity constrained investment approach," SFB 649 Discussion Papers 2017-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2017-014
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    References listed on IDEAS

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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.
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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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