Strategic Investment Decisions in Traditional Assets with Cryptocurrencies: A 2020–2025 Study

Authors

DOI:

https://doi.org/10.7250/eb-2026-0002

Keywords:

Cryptocurrency investment, portfolio optimization, investment strategies, rebalancing, behavioural finance

Abstract

This study examines how including cryptocurrencies reshapes portfolio outcomes and investment strategy performance in highly volatile markets. Using historical data from 2020–2025 and optimization methods by Markowitz and Black–Litterman (BL), three widely used strategies were tested: Buy-and-Hold, Dollar-Cost Averaging (DCA), and Rebalancing. Portfolios included equities, ETFs, bonds, gold, and cryptocurrencies (Bitcoin, Ethereum) with crypto weights of 0 %, 10 %, and 20 %. Performance was evaluated with return-based (CAGR) and risk-adjusted indicators (Sharpe, Sortino, Calmar, Ulcer Index). Results show higher crypto allocations boost long-term returns but increase volatility and drawdowns, especially under Buy-and-Hold. Rebalancing reduces downside risk and stabilizes outcomes, while DCA supports disciplined accumulation but underperforms in growth and efficiency. Markowitz favours bond-heavy conservative portfolios, whereas BL highlights equity exposure and better reflects investor views. No universal “best” strategy exists; choices should reflect risk tolerance, behaviour, and investment horizon. The study systematically compares strategies and offers insights on how crypto assets alter the risk–return balance, bridging theory and practical decision-making.

References

al Guindy, M. (2021). Cryptocurrency price volatility and investor attention. International Review of Economics and Finance, 76, 556–570. https://doi.org/10.1016/j.iref.2021.06.007

Anuno, F., Madaleno, M., & Vieira, E. (2024). Testing of Portfolio Optimization by Timor-Leste Portfolio Investment Strategy on the Stock Market. Journal of Risk and Financial Management, 17(2). https://doi.org/10.3390/jrfm17020078

Bakry, W., Rashid, A., Al-Mohamad, S., & El-Kanj, N. (2021). Risk and Financial Management Bitcoin and Portfolio Diversification: A Portfolio Optimization Approach. JRFM, 14(7). https://doi.org/10.3390/jrfm14070282

Barber, B. M., & Odean, T. (2001). Boys will be Boys: Gender, Overconfidence, and Common Stock Investment. The Quarterly Journal of Economics, 116(1), 261–292. https://doi.org/10.1162/003355301556400

Bodie, Z., Kane, A., & Marcus, A. J. (2018). Investments (11th ed.). McGraw-Hill Education. ISBN 9781259277177.

Bogdan, S., Brmalj, N., & Mujačević, E. (2023). Impact of Liquidity and Investors Sentiment on Herd Behavior in Cryptocurrency Market. International Journal of Financial Studies, 11(3). https://doi.org/10.3390/ijfs11030097

Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1–8. https://doi.org/10.1016/j.jocs.2010.12.007

Charfeddine, L., Benlagha, N., & Maouchi, Y. (2020). Investigating the dynamic relationship between cryptocurrencies and conventional assets: Implications for financial investors. Economic Modelling, 85, 198–217. https://doi.org/10.1016/j.econmod.2019.05.016

Chaudhry, A., & Johnson, H. L. (2008). The efficacy of the Sortino ratio and other benchmarked performance measures under skewed return distributions. Australian Journal of Management, 32(3), 485–502. https://doi.org/10.1177/031289620803200306

Chhatwani, M., & Parija, A. K. (2023). Who invests in cryptocurrency? The role of overconfidence among American investors. Journal of Behavioral and Experimental Economics, 107. https://doi.org/10.1016/j.socec.2023.102107

Choi, J., Kim, H., & Kim, Y. S. (2025). Diversified Reward-Risk Parity in Portfolio Construction. Studies in Nonlinear Dynamics and Econometrics, 29(2), 213–233. https://doi.org/10.1515/snde-2023-0012

Cho, D. D., & Kuvvet, E. (2015). Dollar-Cost Averaging: The Trade-Off Between Risk and Return. Journal of Financial Planning, 28(10), 52–58. https://www.financialplanningassociation.org/article/journal/OCT15-dollar-cost-averaging-trade-between-risk-and-return

Cryptocurrency Prices, Charts and Market Capitalizations CoinMarketCap. (n.d.). https://coinmarketcap.com/

Corbet, S., Lucey, B., Urquhart, A., & Yarovaya, L. (2019). RETRACTED: Cryptocurrencies as a financial asset: A systematic analysis. International Review of Financial Analysis, 62, 182–199. https://doi.org/10.1016/j.irfa.2018.09.003

Dächert, K., Grindel, R., Leoff, E., Mahnkopp, J., Schirra, F., & Wenzel, J. (2022). Multicriteria asset allocation in practice. OR Spectrum, 44(2), 349–373. https://doi.org/10.1007/s00291-021-00641-0

Das, S., & Ahmed, S. S. (2021). Behavioral Finance in Crypto Currency Market: An Integrated and Empirical Investigation. Turkish Online Journal of Qualitative Inquiry (TOJQI), 12(10), 5684.

Donatelli Neto, O., & Colombo, J. A. (2021). The impact of cryptocurrencies on the performance of multi-asset portfolios: Evidence from Brazil. Brazilian Review of Finance, 19(4), 86–129. https://doi.org/10.12660/rbfin.v19n4.2021.84354

Fabozzi, F. J., & Markowitz, H. M. (Eds.). (2011). The theory and practice of investment management: Asset allocation, valuation, portfolio construction, and strategies (2nd ed.). John Wiley & Sons.

Faber, M. T. (2007). A Quantitative Approach to Tactical Asset Allocation. The Journal of Wealth Management, Spring 2007. http://ssrn.com/abstract=962461

Gherghina, Ş.-C., & Constantinescu, C.-A. (2024). Examining herding behavior in the cryptocurrency market. Equilibrium. Quarterly Journal of Economics and Economic Policy, 19(3), 749–792. https://doi.org/10.24136/eq.3057

Guan, G., Liang, Z., & Xia, Y. (2024). Optimal management of DB pension fund under both underfunded and overfunded cases. Scandinavian Actuarial Journal, 2024(6), 583–624. https://doi.org/10.1080/03461238.2023.2289372

Han, W., Newton, D., Platanakis, E., Wu, H., & Xiao, L. (2024). The diversification benefits of cryptocurrency factor portfolios: Are they there? Review of Quantitative Finance and Accounting, 63(2), 469–518. https://doi.org/10.1007/s11156-024-01260-w

Handoko, B. L., Hamsal, M., Sundjaja, A. M., & Gunadi, W. (2024). Heuristic Bias and Herding Behavior for Predicting Investor Decision in Cryptocurrency Trading. International Journal of Safety and Security Engineering, 14(4), 1269–1277. https://doi.org/10.18280/ijsse.140424

Harvey, C. R., Mazzoleni, A., & Melone, C. (2025). The unintended consequences of rebalancing (NBER Working Paper No. 33554). National Bureau of Economic Research. https://doi.org/10.3386/w33554

Investing.com - Stock Market Quotes & Financial News. (n.d.). https://www.investing.com/

James, N., & Menzies, M. (2023). Collective Dynamics, Diversification and Optimal Portfolio Construction for Cryptocurrencies. Entropy, 25(6). https://doi.org/10.3390/e25060931

Jeleskovic, V., Latini, C., Younas, Z. I., & Al-Faryan, M. A. S. (2024). Cryptocurrency portfolio optimization: Utilizing a GARCH-copula model within the Markowitz framework. Journal of Corporate Accounting and Finance, 35(4), 139–155. https://doi.org/10.1002/jcaf.22721

Jones, M., Luu, T. (Jack), & Samuel, B. (2024). The interdependence of financial literacy and crypto literacy. Economics Letters, 239. https://doi.org/10.1016/j.econlet.2024.111737

Kitanovski, D., Mishkovski, I., Stojkoski, V., & Mirchev, M. (2025). Network-based diversification of stock and cryptocurrency portfolios. Applied Network Science, 10(1). https://doi.org/10.1007/s41109-025-00708-9

Leggio, K. B., & Lien, D. (2003). An Empirical Examination of the Effectiveness of Dollar-Cost Averaging Using Downside Risk Performance Measures. Journal of Economics and Finance, 27, 211–223.

Markowitz, H. M. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x

McBride, R., & Dastan, A. (2022). Ulcer index 2.6: A better risk measure? The Journal of Wealth Management, 25(3), 59–71. https://doi.org/10.3905/jwm.2022.1.190

Navarro-Martinez, D., Loomes, G., Isoni, A., Butler, D., & Alaoui, L. (2018). Boundedly rational expected utility theory. Journal of Risk and Uncertainty, 57(3), 199–223. https://doi.org/10.1007/s11166-018-9293-3

Nofer, M., & Hinz, O. (2015). Using Twitter to Predict the Stock Market: Where is the Mood Effect? Business and Information Systems Engineering, 57(4), 229–242. https://doi.org/10.1007/s12599-015-0390-4

Nuhiu, A., Aliu, F., Horák, J., & Peci, B. (2023). Making Informed Decisions in the Volatile Crypto Market: An Analysis of Portfolio Risk and Return. SAGE Open, 13(3). https://doi.org/10.1177/21582440231193600

Oliveira, D. C., Sandfelder, D., Fujita, A., Dong, X., & Cucuringu, M. (2025). Tactical Asset Allocation with Macroeconomic Regime Detection. arXiv:2503.11499v2. https://doi.org/10.48550/arXiv.2503.11499

Pankwaen, K., Thongkairat, S., & Saijai, W. (2025). Global Cross-Market Trading Optimization Using Iterative Combined Algorithm: A Multi-Asset Approach with Stocks and Cryptocurrencies. Mathematics, 13(8). https://doi.org/10.3390/math13081317

Papathanasiou, S., Dokas, I., & Koutsokostas, D. (2022). Value investing versus other investment strategies: A volatility spillover approach and portfolio hedging strategies for investors. North American Journal of Economics and Finance, 62. https://doi.org/10.1016/j.najef.2022.101764

Brito, R. P., Sebastião, H., & Godinho, P. (2016). Efficient skewness/semivariance portfolios. Journal of Asset Management, 17(4), 331–346. https://doi.org/10.1057/jam.2016.9

Pelster, M., Breitmayer, B., & Hasso, T. (2019). Are cryptocurrency traders pioneers or just risk-seekers? Evidence from brokerage accounts. Economics Letters, 182, 98–100. https://doi.org/10.1016/j.econlet.2019.06.013

Platanakis, E., & Urquhart, A. (2019). Portfolio management with cryptocurrencies: The role of estimation risk. Economics Letters, 177, 76–80. https://doi.org/10.1016/j.econlet.2019.01.019

Qi, J., Zhang, Y., & Ouyang, C. (2025). Cryptocurrency Investments: The Role of Advisory Sources, Investor Confidence, and Risk Perception in Shaping Behaviors and Intentions. Journal of Risk and Financial Management, 18(2). https://doi.org/10.3390/jrfm18020057

Rom, B. M., & Ferguson, K. W. (1993). Post-Modern Portfolio Theory. The Journal of Investing, Winter/Fall 1993, 7–18.

Sanhaji, B., & Chevallier, J. (2023). Tracking ‘pure’ systematic risk with realized betas for Bitcoin and Ethereum. Econometrics, 11(3), 19. https://doi.org/10.3390/econometrics11030019

Sen, J., & Dutta, A. (2022). Design and analysis of optimized portfolios for selected sectors of the Indian stock market. arXiv preprint arXiv:2210.03943. https://doi.org/10.48550/arXiv.2210.03943

Shefrin, H., & Statman, M. (2000). Behavioral portfolio theory. Journal of Financial and Quantitative Analysis, 35(2), 127–151. https://www.jstor.org/stable/2676187

Shiller, R. J. (2000). Irrational exuberance. Princeton University Press. ISBN 9780691050621.

Shrotryia, V. K., & Kalra, H. (2022). Herding in the crypto market: a diagnosis of heavy distribution tails. Review of Behavioral Finance, 14(5), 566–587. https://doi.org/10.1108/RBF-02-2021-0021

Statman, M. (2017). Finance for normal people: How investors and markets behave. Oxford University Press. ISBN 9780190626471.

Thaler, R. H. (2015). Misbehaving: The making of behavioral economics. W. W. Norton & Company. ISBN 978-0-393-08094-0. https://doi.org/10.1007/s11127-015-0276-5

Zhang, Y., Ahluwalia, H., Ying, A., Rabinovich, M., & Geysen, A. (2022, October). Rational rebalancing: An analytical approach to multiasset portfolio rebalancing decisions and insights. Vanguard Research. The Vanguard Group.

Zhao, Y., Liu, N., & Li, W. (2022). Industry herding in crypto assets. International Review of Financial Analysis, 84. https://doi.org/10.1016/j.irfa.2022.102335

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Published

14.07.2026

How to Cite

Rimkus, D. (2026). Strategic Investment Decisions in Traditional Assets with Cryptocurrencies: A 2020–2025 Study. Economics and Business, 40, 24-37. https://doi.org/10.7250/eb-2026-0002