XPLUSDT
Crypto market · BinanceQuantitative Strategy Analysis for XPL · XPL on 15m Timeframe
A detailed quantitative review of the algorithmic trading strategy XPL 215000 +1078.41% 1TRAD-JTG8 for the XPL asset. Ranked first for this ticker with a DevioLab Score of 74.36, the model features a 79.49% win rate and a profit factor of 6.67 across 39 historical trades.
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Strategy profile
The algorithm named XPL 215000 +1078.41% 1TRAD-JTG8 is engineered for spot trading of the XPL asset on a 15-minute chart. Classified as a Core strategy within the analytical framework, it holds the top rank for this ticker with a DevioLab Score of 74.36. Across its evaluation history, the system generated 39 completed closed trades. Operating without leverage, the strategy accumulated a total historical return of 987.38 percent. Driven by a high win rate and a strong profit factor of 6.67, the algorithm exhibits a distinct quantitative edge over standard market benchmarks.
Trading rhythm and position duration
Trading rhythm metrics are derived from the 15-minute execution timeframe. Because specific holding time stats such as average or median holding hours are not present in the provided dataset, duration analysis relies on trade counts. The model executed 39 completed trades in total. This low total trade volume suggests a selective filter rather than frequent execution. Given the absence of holding duration figures or trades-per-month metrics, this strategy cannot be categorized as scalping. Instead, it operates selectively, waiting for specific market conditions before placing orders.
Quality of historical results
The historical performance quality is characterized by strong hit accuracy. Out of 39 completed trades, 31 ended in profit, yielding a win rate of 79.49%, while only 8 trades recorded losses. The average trade performance stands at 7.79%, with a median trade gain of 9.66%. A profit factor of 6.67 underscores that total gross gains far outweighed total gross losses. Profit distribution is well-balanced: the top 3 winning trades accounted for 23.27% of total gross profit, confirming that overall profitability is sustained by a consistency of gains rather than isolated outliers. The best single trade achieved a gain of 36.69%.
Risk, drawdown and losing behavior
Risk characteristics highlight a notable downside asymmetry. The maximum historical drawdown reached 43.66%, matching the worst single losing trade of minus 43.66%. This indicates that an unmanaged single adverse trade can significantly impact capital if strict risk mitigation is not applied. However, loss clustering remains minimal, with the longest losing streak capped at 2 consecutive trades compared to a maximum winning streak of 7 trades. While entry precision is exceptionally high, controlling tail loss magnitude remains paramount.
Behavior through time and yearly stability
The supplied dataset does not include a yearly performance breakdown or a definitive start date, recording an end date of 2026-08-09. Due to the missing yearly breakdown metrics, annual consistency cannot be evaluated on a calendar-year basis. The stated annualized return metric matches the cumulative history profit of 987.38%. Users should take the compact sample size of 39 trades into account when considering historical stability.
Strengths and limitations
Key strengths include a strong 79.49% win rate, a robust profit factor of 6.67, a high median trade gain of 9.66%, and a healthy profit distribution where the top 3 winners represent only 23.27% of gross profits. Primary limitations center on the limited sample size of 39 trades, a maximum single trade loss and drawdown of 43.66%, and zero trade activity recorded since June 2024.
DevioLab analytical conclusion
The XPL 215000 +1078.41% 1TRAD-JTG8 model demonstrates impressive statistical efficiency on the XPL ticker, earning the top rank with a DevioLab Score of 74.36. Its elevated win rate and profit factor highlight strong entry timing. However, the 43.66% maximum drawdown underscores the necessity of strict risk management. Quantitative evaluation should account for the compact trade count and recent dormancy.
Data scope and methodology
This analysis relies strictly on historical simulated spot trading data through 2026-08-09 without leverage. The statistics reflect closed simulated positions and do not constitute guaranteed future performance or direct account returns. This report serves informational purposes only and does not represent financial advice.