Data Sampling Frequency Effects on Risk-Adjusted Cryptocurrency Portfolio Construction
Received: 20 January 2026 | Revised: 14 February 2026 | Accepted: 25 February 2026 | Online: 4 April 2026
Corresponding author: Kamal El Kehal
Abstract
The cryptocurrency market exhibits a high level of volatility, and the process of portfolio construction can be complex and highly lucrative. Issues related to portfolio construction in the cryptocurrency market are targeted in this paper through the assessment of the effect of sampling frequency on cryptocurrency portfolio optimization. A detailed analysis of the effect of three specific sampling frequencies (15 minutes, 1 hour, and 1 day) was undertaken, and the activities of eight top cryptocurrencies (ADA, BTC, DOGE, ETH, LTC, SOL, TRX, and XRP) were considered. Using price information sourced from the KuCoin exchange from 2023 to 2025, we are able to conduct a risk-adjusted optimization-based analysis to determine the optimal portfolio composition while utilizing the Sharpe Ratio measure to determine portfolio performance. The effect of sampling frequency on portfolio composition, as well as on the estimate of the risk/return profile and correlation measures, proved to be significant.
Keywords:
cryptocurrency portfolio, portfolio optimization, data sampling frequency, high-frequency data, risk management, Sharpe ratio, mean-variance optimizationDownloads
References
M. Brière, K. Oosterlinck, and A. Szafarz, "Virtual currency, tangible return: Portfolio diversification with bitcoin," Journal of Asset Management, vol. 16, no. 6, pp. 365–373, Nov. 2015. DOI: https://doi.org/10.1057/jam.2015.5
A. Kajtazi and A. Moro, "The role of bitcoin in well diversified portfolios: A comparative global study," International Review of Financial Analysis, vol. 61, pp. 143–157, Jan. 2019. DOI: https://doi.org/10.1016/j.irfa.2018.10.003
R. Cont, "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, vol. 1, no. 2, pp. 223–236, Feb. 2001. DOI: https://doi.org/10.1080/713665670
H. Markowitz, "Portfolio Selection," The Journal of Finance, vol. 7, no. 1, pp. 77–91, 1952. DOI: https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
F. A. Sortino and R. van der Meer, "Downside risk: Capturing what’s at stake in investment situations," Journal of Portfolio Management, vol. 17, no. 4, pp. 27–31, 1991. DOI: https://doi.org/10.3905/jpm.1991.409343
A. Ang, J. Chen, and Y. Xing, "Downside Risk," The Review of Financial Studies, vol. 19, no. 4, pp. 1191–1239, Dec. 2006. DOI: https://doi.org/10.1093/rfs/hhj035
H. Grootveld and W. Hallerbach, "Variance vs downside risk: Is there really that much difference?," European Journal of Operational Research, vol. 114, no. 2, pp. 304–319, Apr. 1999. DOI: https://doi.org/10.1016/S0377-2217(98)00258-6
V. DeMiguel, L. Garlappi, and R. Uppal, "Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy?," The Review of Financial Studies, vol. 22, no. 5, pp. 1915–1953, May 2009. DOI: https://doi.org/10.1093/rfs/hhm075
N. A. Canakgoz and J. E. Beasley, "Mixed-integer programming approaches for index tracking and enhanced indexation," European Journal of Operational Research, vol. 196, no. 1, pp. 384–399, Jul. 2009. DOI: https://doi.org/10.1016/j.ejor.2008.03.015
J. Ye, Y. Wang, and M. W. Raza, "Bounded strategies for maximizing the sharpe ratio," International Journal of Theoretical and Applied Finance, vol. 26, no. 01, Feb. 2023, Art. no. 2350002. DOI: https://doi.org/10.1142/S0219024923500024
A. F. Bariviera and I. Merediz-Solà, "Where Do We Stand in Cryptocurrencies Economic Research? A Survey Based on Hybrid Analysis," Journal of Economic Surveys, vol. 35, no. 2, pp. 377–407, 2021. DOI: https://doi.org/10.1111/joes.12412
S. M. Hussain, N. Ahmad, and S. Ahmed, "Applications of high-frequency data in finance: A bibliometric literature review," International Review of Financial Analysis, vol. 89, Oct. 2023, Art. no. 102790. DOI: https://doi.org/10.1016/j.irfa.2023.102790
E. Kaur, "The Limits of Lognormal: Assessing Cryptocurrency Volatility and VaR using Geometric Brownian Motion," presented at the Hinweis Second International Conference on Recent Trends in Engineering and Technology (RTET), Dec. 2025.
E. Kaur, "The Limits of Conditional Volatility: Assessing Cryptocurrency VaR under EWMA and IGARCH Models." arXiv, Jan. 20, 2026.
S. Sahu, J. H. O. Vázquez, A. F. Ramírez, and J.-M. Kim, "Analyzing Portfolio Optimization in Cryptocurrency Markets: A Comparative Study of Short-Term Investment Strategies Using Hourly Data Approach," Journal of Risk and Financial Management, vol. 17, no. 3, Mar. 2024. DOI: https://doi.org/10.3390/jrfm17030125
M. Kim, Y. Jin Jeong, and J. Jeong, "Two Empirical Studies of Portfolio Optimization Using Cryptocurrency Allocation Ratios," IEEE Access, vol. 12, pp. 63827–63838, 2024. DOI: https://doi.org/10.1109/ACCESS.2024.3396495
Z. Zhou, Z. Song, T. Ren, and L. Yu, "Two-Stage Portfolio Optimization Integrating Optimal Sharp Ratio Measure and Ensemble Learning," IEEE Access, vol. 11, pp. 1654–1670, 2023. DOI: https://doi.org/10.1109/ACCESS.2022.3232281
J. Bouslimi, S. Boubaker, and K. Tissaoui, "Forecasting of Cryptocurrency Price and Financial Stability: Fresh Insights based on Big Data Analytics and Deep Learning Artificial Intelligence Techniques," Engineering, Technology & Applied Science Research, vol. 14, no. 3, pp. 14162–14169, Jun. 2024. DOI: https://doi.org/10.48084/etasr.7096
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Copyright (c) 2026 Kamal Elkehal, Drissia Ennagoura, Khalid El Fahssi, Badre Bossoufi, Mohamed El Far, Mohamed Taj Bennani
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