FILUSDT
Mercado cripto · BinanceQuantitative Trading Strategy Analysis FIL · FIL: FIL 215000 +11530.79% 1TRAD-SGB7
A quantitative evaluation of the FIL 215000 +11530.79% 1TRAD-SGB7 algorithmic model on the 15-minute timeframe for FIL over a 5.82-year dataset, highlighting a high 78.42% win rate across 190 trades alongside zero trade activity since June 2024.
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Strategy profile
The quantitative trading system designated as FIL 215000 +11530.79% 1TRAD-SGB7 is designed to trade the 15-minute chart timeframe for the cryptocurrency spot asset FIL (FIL). Across an evaluated backtest dataset spanning 5.82 years from October 15, 2020, through August 11, 2026, the model ranks 3rd among tested strategies for this ticker, earning a DevioLab score of 52.50. It is categorized as a non-core strategy. Over the full history, the algorithm generated a cumulative backtested return of 11530.80%, which translates to a benchmark annualized yield of 223.93%.
Trading rhythm and position duration
Despite operating on a granular 15-minute candlestick chart, the strategy maintains a moderate execution frequency. It logged a total of 190 completed trades over 5.82 years, averaging approximately 32.63 trades per year. Although exact holding metrics such as average or median holding hours are null in this dataset, the lower trade count indicates a selective entry approach rather than high-frequency scalp trading. Signals manifest roughly 2 to 3 times per month on average, allowing positions to play out without excessive turnover.
Quality of historical results
The model demonstrates strong win rate performance, securing profit on 78.42% of its trades. Out of 190 completed operations, 149 were profitable while 41 closed at a loss. The average return per trade stands at 2.99%, with a higher median trade return of 3.73%. The profit factor reached 1.67. Crucially, gain distribution is healthy: the top three winning trades combined represent only 8.91% of total gross profit, confirming that overall return is not reliant on a few outlier spikes. The maximum single trade gain was 33.95%.
Risk, drawdown and losing behavior
Risk parameters show realistic drawdowns associated with crypto spot trading. The strategy recorded a maximum historic portfolio drawdown of 28.23%. The worst single losing trade reached -27.48%, which represents a notable single-trade drop compared to the average trade gain. On the other hand, streak reliability was robust, achieving a maximum winning streak of 14 consecutive trades while capping its longest losing streak at just 3 trades.
Behavior through time and yearly stability
Detailed yearly breakdown records are unavailable in this specific sample over the 5.82-year dataset span. However, the overarching historical performance metrics demonstrate strong compounding capability over full market cycles, generating 11530.80% total return. Analyzing performance stability requires recognizing that specialized quantitative models may undergo dormant phases depending on prevailing market volatility.
Strengths and limitations
Key strengths of the model include its high 78.42% win rate, low profit concentration where the top three trades account for under 9% of gains, and a brief maximum losing streak of 3 trades. Limitations include a severe worst trade loss of -27.48%, a moderate profit factor of 1.67, a peak drawdown of 28.23%, and zero trade execution since June 2024.
DevioLab analytical conclusion
Holding a DevioLab score of 52.50 and ranking 3rd for the FIL asset, this model offers a compelling historical record characterized by high win frequency and steady gain distribution. However, the absence of active trades since mid-2024 highlights the need for careful review. Quantitative analysts should verify whether the model logic aligns with present market volatility before considering live application.
Data scope and methodology
All figures presented in this report are calculated from historical simulated closed trades for FIL on the 15-minute timeframe between October 15, 2020, and August 11, 2026. These statistics represent spot-style backtest research, do not reflect live Binance account performance, and do not constitute financial advice.