Value-at-Risk Assessment and Efficient Portfolio Structure in Cryptocurrencies: An Empirical Analysis, 2019–2023
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Cryptocurrencies, Portfolio Theory, Value-at-Risk, Financial MarketsArticle Sidebar
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The aim of this study is to analyze the risk exposure of four cryptocurrencies in order to determine optimal portfolio combinations that mitigate market risk by applying portfolio theory and the parametric Value-at-Risk (VaR) model. The study covered the period from 2019 to 2023 and employed a quantitative and descriptive approach based on the daily logarithmic returns of Bitcoin, Ethereum, Tether, and Binance Coin, obtained from the CoinMarketCap platform. Using these data, the study estimated the correlations among the assets, identified efficient portfolios, and measured the daily risk exposure of each cryptocurrency. The analysis was complemented by an analysis of variance (ANOVA). The results show that Tether dominates the efficient portfolios, with allocations exceeding 90% in most years, owing to its low volatility and weak correlations with the other cryptocurrencies, whereas Bitcoin and Ethereum exhibit high volatility. The VaR analysis revealed average daily values ranging from 5% to 8% for Bitcoin and Ethereum and below 1% for Tether. However, the ANOVA indicated that there were no statistically significant differences in daily risk among the cryptocurrencies. The main conclusion of this study is that the application of VaR and portfolio theory is useful for assessing and comparing risk across digital assets. In addition, stablecoins play a stabilizing role in cryptocurrency portfolio management. These findings contribute to the understanding of financial risk in decentralized markets by providing empirical evidence for the design of efficient investment strategies in volatile environments.
Agrrawal, P., Gilbert, F. W., & Harkins, J. (2022). Time dependence of CAPM betas on the choice of interval frequency and return timeframes: Is there an optimum? Journal of Risk and Financial Management, 15(11), Article 520. https://doi.org/10.3390/jrfm15110520 DOI: https://doi.org/10.3390/jrfm15110520
Aljinović, Z., Marasović, B., & Šestanović, T. (2021). Cryptocurrency portfolio selection—A multicriteria approach. Mathematics, 9(14), Article 1677. https://doi.org/10.3390/math9141677 DOI: https://doi.org/10.3390/math9141677
Ante, L., Saggu, A., & Fiedler, I. (2025). The stablecoin discount: Evidence of Tether's U.S. Treasury Bill market share in lowering yields (arXiv:2505.12413) [Preprint]. arXiv. https://doi.org/10.2139/ssrn.5260299 DOI: https://doi.org/10.2139/ssrn.5259211
Aydoğan, B., Cayirli, O., & Vardar, G. (2025). Impact of macroeconomics factors on cryptocurrency pricing: Evidence from Bitcoin and Ethereum markets. Computational Economics, 3131–3166. https://doi.org/10.1007/s10614-024-10804-0 DOI: https://doi.org/10.1007/s10614-024-10804-0
Azar, P. D., Baughman, G., Carapella, F., Gerszten, J., Lubis, A., Perez-Sangimino, J. P., Rappoport, D. E., Scotti, C., Swem, N., Vardoulakis, A., & Werman, A. (2022). The financial stability implications of digital assets (Finance and Economics Discussion Series No. 2022-058). Board of Governors of the Federal Reserve System. https://doi.org/10.17016/FEDS.2022.058 DOI: https://doi.org/10.17016/feds.2022.058
Bank for International Settlements. (2023). The crypto ecosystem: Key elements and risks. https://www.bis.org/publ/othp72.pdf
Brynjarsson, A., & Ágústsdóttir, K. (2022). Cryptocurrencies in optimized portfolios: A portfolio theory approach [Master's thesis, Copenhagen Business School].
Che, N. X., Copestake, A., Furceri, D., & Terracciano, T. (2023). The crypto cycle and U.S. monetary policy (IMF Working Paper No. 2023/163). International Monetary Fund. https://doi.org/10.5089/9798400245411.001 DOI: https://doi.org/10.5089/9798400245411.001
CoinMarketCap. (2024, January 28). CoinMarketCap. https://coinmarketcap.com/
De Lara Haro, A. (2008). Medición y control de riesgos financieros (3rd ed.). Limusa.
Dias, A. (2013). Market capitalization and Value-at-Risk. Journal of Banking & Finance, 37(12), 5248–5260. https://doi.org/10.1016/j.jbankfin.2013.04.015 DOI: https://doi.org/10.1016/j.jbankfin.2013.04.015
Fidelity Digital Assets. (2024). Bitcoin as an aspirational store of value revisited. https://www.fidelitydigitalassets.com/sites/g/files/djuvja3256/files/acquiadam/1125481.2.0%20-%20FDA%20Bitcoin%20as%20an%20Aspirational%20Store%20of%20Value%20Revisited%20V2.pdf
Field, J., & Can Inci, A. (2023). Risk translation: How cryptocurrency impacts company risk, beta and returns. Journal of Capital Markets Studies, 5–21. https://doi.org/10.1108/JCMS-02-2023-0003 DOI: https://doi.org/10.1108/JCMS-02-2023-0003
Forero Laverde, G. (2011). Contrastación de paradigmas de las finanzas: Normalidad e hipótesis del mercado eficiente. Aplicaciones en Matlab. Observatorio de Economía y Operaciones Numéricas (ODEON). https://revistas.uexternado.edu.co/index.php/odeon/article/download/2870/2511/9596
Gálvez G., P., Salgado I., M., & Gutiérrez U., M. (2010). Optimización de carteras de inversión: Modelo de Markowitz y estimación de volatilidad con GARCH. Horizontes Empresariales, 39–50. https://doi.org/10.22320/hem.v9i2.2031 DOI: https://doi.org/10.22320/hem.v9i2.2031
Gaytán Cortés, J. (2022). Value at Risk (VaR). Mercados y Negocios, (45), 95–104. https://doi.org/10.32870/myn.vi45.7665 DOI: https://doi.org/10.32870/myn.vi45.7665
Gbadebo, A. D., Adekunle, A. O., Adedokun, W., Lukman, A.-O. A., & Akande, J. (2021). BTC price volatility: Fundamentals versus information. Cogent Business & Management, 8(1), Article 1984624. https://doi.org/10.1080/23311975.2021.1984624 DOI: https://doi.org/10.1080/23311975.2021.1984624
Holovatiuk, O. (2020). Cryptocurrencies as an asset class in portfolio optimisation. Central European Economic Journal, 7(54), 33–55. https://doi.org/10.2478/ceej-2020-0004 DOI: https://doi.org/10.2478/ceej-2020-0004
Iyer, R., & Popescu, A. (2023). New evidence on spillovers between crypto assets and financial markets (IMF Working Paper No. 2023/213). International Monetary Fund. https://doi.org/10.5089/9798400256622.001 DOI: https://doi.org/10.5089/9798400256622.001
Kukacka, J., & Kristoufek, L. (2023). Fundamental and speculative components of the cryptocurrency pricing dynamics. Financial Innovation, 9(1), Article 61. https://doi.org/10.1186/s40854-023-00465-7 DOI: https://doi.org/10.1186/s40854-023-00465-7
Kupiec, P. (2002). Stress testing in a Value at Risk framework. In M. Dempster (Ed.), Risk management: Value at risk and beyond (pp. 76–99). Cambridge University Press. https://doi.org/10.1017/CBO9780511615337.004 DOI: https://doi.org/10.1017/CBO9780511615337.004
Lu, X. (2023). Design and features of block chain and algorithm. In Proceedings of the 2022 3rd International Conference on Big Data Economy and Information Management (BDEIM 2022) (Advances in Economics, Business and Management Research). Atlantis Press. https://doi.org/10.2991/978-94-6463-124-1_66 DOI: https://doi.org/10.2991/978-94-6463-124-1_66
Lin, Y., Su, G., Pan, J., & Zhang, P. (2023). Markowitz-based portfolio research. In Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023) (Atlantis Highlights in Intelligent Systems). Atlantis Press. https://doi.org/10.2991/978-94-6463-222-4_30 DOI: https://doi.org/10.2991/978-94-6463-222-4_30
Linsmeier, T. J., & Pearson, N. D. (2000). Value at risk. Financial Analysts Journal, 56(2), 47–67. https://doi.org/10.2469/faj.v56.n2.2343 DOI: https://doi.org/10.2469/faj.v56.n2.2343
Lyons, R. K., & Viswanath-Natraj, G. (2023). What keeps stablecoins stable? Journal of International Money and Finance, 1–20. https://doi.org/10.1016/j.jimonfin.2022.102777 DOI: https://doi.org/10.1016/j.jimonfin.2022.102777
Manganelli, S., & Engle, R. F. (2001). Value at risk models in finance. European Central Bank. https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp075.pdf
Mangram, M. E. (2013). A simplified perspective of the Markowitz portfolio theory. Global Journal of Business Research, 7(1), 59–70. https://ssrn.com/abstract=2147880
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x DOI: https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
Naifar, N., & Makni, M. (2025). Dynamics of cryptocurrencies, DeFi tokens, and tech stocks: Lessons from the FTX collapse. International Journal of Financial Studies, 13(3), 169. https://doi.org/10.3390/ijfs13030169 DOI: https://doi.org/10.3390/ijfs13030169
Przyłuska-Schmitt, J., Jegorow, D., & Bučková, J. (2023). The dynamics of cryptocurrency price volatility in the face of the crisis on the example of Bitcoin and Ethereum. Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia, 57(2), 101–113. https://doi.org/10.17951/h.2023.57.2.101-113
Rosa, G., & Pareschi, R. (2021). Tether: A study on bubble-networks. Frontiers in Blockchain, 1–11. https://doi.org/10.3389/fbloc.2021.686484 DOI: https://doi.org/10.3389/fbloc.2021.686484
Samimi, A., Bozorgian, A., & Samimi, M. (2022). An analysis of risk management in financial markets and its effects. Journal of Engineering in Industrial Research, 3(1), 1–7. https://doi.org/10.22034/jeires.2022.1.1
Stulz, R. M. (2023). Crisis risk and risk management. European Financial Management, 29(5), 1377–1400. https://doi.org/10.1111/eufm.12441 DOI: https://doi.org/10.1111/eufm.12441
Subathra, R., & Kachi Mohideen, A. (2017). Modern portfolio theory: A review of the work done on performance measures and their role in portfolio construction. International Journal of Scientific Research in Science and Technology, 3(3), 525–532. https://ijsrst.com/IJSRST1733179
Sukomardojo, T., Pamikatsih, M., Arpianto, Y., Nuraini, A., & Fatmawati, E. (2023). Cryptocurrency and macro-economic stability: Impacts and regulations. International Journal of Science and Society, 5(4), 734–745. https://doi.org/10.54783/ijsoc.v5i4.842 DOI: https://doi.org/10.54783/ijsoc.v5i4.842
Vargas, V. (2007). Estadística descriptiva para ingeniería ambiental con SPSS. Universidad Nacional de Colombia. https://repositorio.unal.edu.co/handle/unal/52004
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