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Optimising Portfolio Risk by Involving Crypto Assets in a Volatile Macroeconomic Environment

Author

Listed:
  • Attila Bányai

    (Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Páter Károly Str. 1, H-2100 Gödöllő, Hungary)

  • Tibor Tatay

    (Department of Statistics, Finances and Controlling, Széchenyi István University, Egyetem Square 1, H-9026 Győr, Hungary)

  • Gergő Thalmeiner

    (Department of Investment, Finance and Accounting, Hungarian University of Agriculture and Life Sciences, Páter Károly Str. 1, H-2100 Gödöllő, Hungary)

  • László Pataki

    (Doctoral School of Management and Business Administration, John von Neumann University, Infopark Sétány 1, H-1117 Budapest, Hungary
    Faculty of Social Sciences, Eötvös Lóránd University, Pázmány Péter Sétány 1/A, H-1117 Budapest, Hungary)

Abstract

Portfolio diversification is an accepted principle of risk management. When constructing an efficient portfolio, there are a number of asset classes to choose from. Financial innovation is expanding the range of instruments. In addition to traditional commodities and securities, other instruments have been added. These include cryptocurrencies. In our study, we seek to answer the question of what proportion of cryptocurrencies should be included alongside traditional instruments to optimise portfolio risk. We use VaR risk measures to optimise the process. Diversification opportunities are evaluated under normal return distributions, thick-tailed distributions, and asymmetric distributions. To answer our research questions, we have created a quantitative model in which we analysed the VaR of different portfolios, including crypto-diversified assets, using Monte Carlo simulations. The study database includes exchange rate data for two consecutive years. When selecting the periods under examination, it was important to compare favourable and less favourable periods from a macroeconomic point of view so that the study results can be interpreted as a stress test in addition to observing the diversification effect. The first period under examination is from 1 September 2020 to 31 August 2021, and the second from 1 September 2021 to 31 August 2022. Our research results ultimately confirm that including cryptoassets can reduce the risk of an investment portfolio. The two time periods examined in the simulation produced very different results. An analysis of the second period suggests that Bitcoin’s diversification ability has become significant in the unfolding market situation due to the Russian-Ukrainian war.

Suggested Citation

  • Attila Bányai & Tibor Tatay & Gergő Thalmeiner & László Pataki, 2024. "Optimising Portfolio Risk by Involving Crypto Assets in a Volatile Macroeconomic Environment," Risks, MDPI, vol. 12(4), pages 1-21, April.
    • Handle: RePEc:gam:jrisks:v:12:y:2024:i:4:p:68-:d:1377263
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    References listed on IDEAS

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    2. Stoyan Stoyanov & Svetlozar Rachev & Frank Fabozzi, 2013. "Sensitivity of portfolio VaR and CVaR to portfolio return characteristics," Annals of Operations Research, Springer, vol. 205(1), pages 169-187, May.
    3. Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
    4. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    5. Hsu, Shu-Han & Sheu, Chwen & Yoon, Jiho, 2021. "Risk spillovers between cryptocurrencies and traditional currencies and gold under different global economic conditions," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
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    Cited by:

    1. Silky Vigg Kushwah & Shab Hundal & Payal Goel, 2024. "Unveiling Interconnectedness and Volatility Transmission: A Novel GARCH Analysis of Leading Global Cryptocurrencies," International Journal of Economics and Financial Issues, Econjournals, vol. 14(3), pages 132-139, May.

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