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Submitted
April 24, 2025
Accepted
July 30, 2025
Published
April 14, 2026
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Abstract

This paper proposes a dynamic cryptocurrency asset allocation strategy that combines Sharpe Ratio-based weighting with trend filtering using the Simple Moving Average (SMA) of Bitcoin (BTC). The model reallocates capital among a portfolio of seven major cryptocurrencies (BTC, ETH, BNB, SOL, TON, TRX, XRP) every three days, conditional on BTC trading above its respective SMA threshold (50-day, 100-day, or 200-day). When BTC trends below the SMA, the strategy shifts fully to USDT to minimize downside risk. Using historical data from January 1, 2024, to January 1, 2025, the study evaluates performance across three SMA configurations and benchmarks against a buy-and-hold baseline. Results show that the SMA-50 strategy achieved the highest cumulative return (+231.51%) and Sharpe Ratio (2.51), significantly outperforming both the longer SMA-based models and the baseline average return (+132.14%). Risk analysis indicates that shorter SMA windows allow more responsive exposure during market uptrends but increase short-term volatility. Overall, the findings support the use of hybrid strategies combining trend-following filters and risk-adjusted allocation for managing crypto portfolios in volatile environments.

Keywords

Asset Allocation Cryptocurrency Portfolio Optimization Sharpe Ratio Simple Moving Average

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How to Cite
Fauzan Adziima, A., Wara, S. S. M., Nasrudin, M., & Pratama, . A. R. (2026). Sharpe Ratio-Based Dynamic Crypto Asset Allocation with Trend Filtering Using SMA. Enthusiastic : International Journal of Applied Statistics and Data Science, 6(1), 1–9. https://doi.org/10.20885/enthusiastic.vol6.iss1.art1
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