GLMUSDT
Mercado cripto · BinanceGLM · GLM Quantitative Strategy Benchmark Analysis
Historical performance evaluation of the top-ranked 15-minute quantitative trading strategy for GLM, analyzing 205 completed trades from March 2023 through August 2026.
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Strategy profile
The quantitative model evaluated in this research targets the spot market for the GLM asset using a 15-minute execution interval. Over an extended sample period of 3.41 years spanning from March 17, 2023, to August 11, 2026, the strategy earned a DevioLab score of 71.74, ranking number one among all benchmarked strategies for this specific ticker. Throughout this history, the model completed 205 total trades, recording 172 winning transactions and 33 losing transactions. The cumulative historical performance yielded a total return of 107717.04 percent, which corresponds to an annualized figure of 4544.87 percent.
Trading rhythm and position duration
Despite relying on a granular 15-minute bar structure, the algorithm demonstrates a measured operational cadence, averaging 60.19 completed trades per year. Exact metrics regarding average or median holding hours, as well as the average time between trade exits, are not available in the underlying dataset. With 205 total closed trades across more than three years, the system avoids overtrading. However, the model completed zero trades during the recent window starting June 1, 2024, indicating that its execution filters remained inactive during that time frame.
Quality of historical results
The system features a high trade accuracy, achieving an 83.90 percent win rate across its historical dataset. This win rate is accompanied by a profit factor of 3.33, demonstrating that gross profits exceeded gross losses by over three times. The average return per completed trade stands at 3.94 percent, while the median trade return is 4.25 percent. Profit distribution across the winning trade set is broad and resilient: the top three winning trades generated only 8.15 percent of total gross profits, proving that performance was built on repeated execution rather than individual outliers. The longest consecutive winning streak reached 28 trades.
Risk, drawdown and losing behavior
The historical maximum peak-to-trough drawdown recorded by the strategy was 38.58 percent. Out of 205 completed positions, 33 ended in a loss, representing a losing trade ratio of 16.10 percent, with the longest consecutive losing streak limited to 3 trades. Tail risk examination reveals that the single best winning trade yielded a return of 30.29 percent, whereas the worst single loss reached negative 29.03 percent. This symmetry in extreme outcomes indicates that despite an 83.90 percent success rate, individual losing trades can occasionally draw down capital significantly when stop conditions are triggered.
Behavior through time and yearly stability
Assessing temporal stability requires reviewing trade metrics across separate annual calendar periods. Detailed yearly breakdown tables are omitted in the source data. Nevertheless, overall sample metrics indicate that trading activity was concentrated prior to mid-2024. Because all 205 trades occurred before June 2024, analysts must account for potential multi-month regimes during which the model triggers no active market entries.
Strengths and limitations
Key statistical strengths of this model include an 83.90 percent win rate, a 3.33 profit factor, a maximum winning streak of 28 trades, and a well-balanced return distribution where the top three trades represent only 8.15 percent of total gross profits. On the limitation side, the system experienced a peak historical drawdown of 38.58 percent and a single worst trade loss of 29.03 percent. Furthermore, the complete lack of trade activity since June 1, 2024, alongside missing duration metrics, restricts visibility into recent real-market responsiveness.
DevioLab analytical conclusion
With a DevioLab score of 71.74 and the top rank for GLM, this 15-minute spot model exhibits high historical trade expectancy, characterized by a 3.94 percent average trade and a 4.25 percent median return across 205 trades. However, risk management models must account for its historical 38.58 percent max drawdown and its extended inactive phase since June 2024. Continuous monitoring remains essential to verify whether current market conditions align with the strategy historical parameters.
Data scope and methodology
This analysis covers historical spot backtest data for GLM on a 15-minute timeframe between March 17, 2023, and August 11, 2026, spanning 3.41 years. The reported statistics reflect closed simulated trade returns and do not represent guaranteed future results or exact real-time execution performance on Binance or other exchanges due to execution friction, slippage, and fee variations.