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Enthusiastic : International Journal of Applied Statistics and Data Science (e-ISSN: 2798-3153, p-ISSN: 2798-253X) is an international journal published and managed by Statistics Department, Faculty of Mathematics and Natural Sciences, Universitas Islam Indonesia. This journal publishes original research articles or review articles on all aspect of statistics and data science field which should be written in English. ENTHUSIASTIC has the vision to become a reputable journal and publish good quality papers. We aim to provide lecturer, researchers both academic and industries, and students worldwide with unlimited access to be published in our journal.

The articles listed on this page have undergone thorough peer review in accordance with the standards and policies of Enthusiastic: International Journal of Applied Statistics and Data Science and have been accepted for publication in forthcoming issues. However, they have not yet been assigned to a specific issue or given an official publication date. They will be formally published once included in a complete issue or volume on the journal’s website.

Volume 6 Issue 1, April 2026

Sharpe Ratio-Based Dynamic Crypto Asset Allocation with Trend Filtering Using Simple Moving Average

Andri Fauzan Adziima ^a,1,*, Shindi Shella May Wara ^a,2, Muhammad Nasrudin^a,3, Alfan Rizaldy Pratama^a,4

^aDepartment of Data Science, Universitas Pembangunan Nasional Veteran Jawa Timur, Surabaya, 60294, Indonesia

Abstract

This paper proposes a dynamic cryptocurrency asset allocation strategy combining Sharpe Ratio-based weighting with Simple Moving Average (SMA) trend filtering of Bitcoin (BTC). The Sharpe Ratio evaluates risk-adjusted returns, while SMA provides robust trend signals, enabling adaptive portfolio management in volatile crypto markets. The model reallocates capital among seven major cryptocurrencies (BTC, ETH, BNB, SOL, TON, TRX, XRP) every three days. If BTC trades below its SMA threshold (50-day, 100-day, or 200-day), the strategy shifts to Tether USD (USDT) to minimize downside risk. Using historical data from January 1, 2024, to January 1, 2025, the SMA-50 strategy achieved the highest cumulative return (+231.51%) and Sharpe Ratio (2.51), significantly outperforming longer SMA models and a buy-and-hold baseline (+132.14%). A Sharpe Ratio of 2.51 indicates 2.51 units of excess return per unit of risk. Risk analysis suggests shorter SMA windows offer responsive exposure but increase short-term volatility. Findings support hybrid strategies for active crypto portfolio management and suggest future research into advanced trend detection.