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Crypto portfolio optimization through lens of tail risk and variance measures

Author

Listed:
  • Bojan Tomiæ

    (Effectus University, College for Law and Finance, Zagreb, Croatia)

  • Saša Žikoviæ

    (University of Rijeka, Faculty of Economics and Business, Rijeka, Croatia)

  • Lorena Jovanoviæ

    (University of Rijeka, Faculty of Economics and Business, Rijeka, Croatia)

Abstract

The choice of an adequate risk measure in portfolio optimization depends to a large extent on the characteristics and dynamics of the underlying assets. For investors and asset managers, a range of potential market risks provides much- needed insights into the optimization of their portfolio of assets. Since this paper focuses on multiple risk measures, it presents the investors with a better insight into the potential magnitude of the risk they are faced with. Since the risk-reward optimization target can be adjusted for a broad choice of risk measures in this paper we will test the performance of the classical risk measure i.e. standard deviation versus a tail risk measure such as expected tail loss (ETL). Our goal is to find which of the two offers the better performance for a portfolio of cryptocurrencies and if the differences are statistically significant. The setup for our analysis is testing two optimization targets (MinVar and MinETL) on 10 portfolios of cryptocurrencies randomly chosen from a sample of 70 cryptocurrencies with the highest market capitalization.

Suggested Citation

  • Bojan Tomiæ & Saša Žikoviæ & Lorena Jovanoviæ, 2022. "Crypto portfolio optimization through lens of tail risk and variance measures," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 40(2), pages 297-312.
    • Handle: RePEc:rfe:zbefri:v:40:y:2022:i:2:p:297-312
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    References listed on IDEAS

    as
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    4. Goodell, John W. & Goutte, Stephane, 2021. "Diversifying equity with cryptocurrencies during COVID-19," International Review of Financial Analysis, Elsevier, vol. 76(C).
    5. Platanakis, Emmanouil & Sutcliffe, Charles & Urquhart, Andrew, 2018. "Optimal vs naïve diversification in cryptocurrencies," Economics Letters, Elsevier, vol. 171(C), pages 93-96.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    portfolio optimization; cryptocurrency; risk evaluation; investments;
    All these keywords.

    JEL classification:

    • E49 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Other
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • P45 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - International Linkages

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