https://journal.uii.ac.id/ENTHUSIASTIC <p>Enthusiastic : International Journal of Applied Statistics and Data Science (e-ISSN: <a href="https://portal.issn.org/resource/ISSN/2798-3153" target="_blank" rel="noopener">2798-3153</a>, p-ISSN: <a href="https://portal.issn.org/resource/ISSN/2798-253X" target="_blank" rel="noopener">2798-253X</a>) 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.</p> <p> </p> Universitas Islam Indonesia en-US Enthusiastic : International Journal of Applied Statistics and Data Science 2798-253X <p>Authors who publish with this journal agree to the following terms:</p><ol type="a"><li>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="http://creativecommons.org/licenses/by-sa/4.0">Creative Commons Attribution License</a> that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.</li><li>Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.</li><li>Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See <a href="http://opcit.eprints.org/oacitation-biblio.html" target="_new">The Effect of Open Access</a>).</li></ol> https://journal.uii.ac.id/ENTHUSIASTIC/article/view/39963 <p><span style="font-weight: 400;">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.</span></p> Andri Fauzan Adziima Shindi Shella May Wara Muhammad Nasrudin Alfan Rizaldy Pratama Copyright (c) 2026 2026-04-14 2026-04-14 1 9 10.20885/enthusiastic.vol6.iss1.art1