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Crypto market · BinanceDOT · DOT Quantitative Strategy Research: DOT 215000 +385682.64% TRAD-ISG4
A quantitative evaluation of the core algorithmic strategy DOT 215000 +385682.64% TRAD-ISG4 for the crypto asset DOT on the 15-minute timeframe. The model features a win rate of 76.29%, a profit factor of 3.75, and cumulative historical returns of 385682.64% alongside a maximum drawdown of 51.90%.
Analysis as of 13.08.2026. Strategy data is updated separately.Read full analysis
Strategy profile
The algorithmic trading model DOT 215000 +385682.64% TRAD-ISG4 is engineered for the cryptocurrency asset DOT (symbol DOT) operating on the 15-minute timeframe (15m). Within the internal DevioLab ranking framework, this implementation holds rank 2 among tested strategies for this ticker, achieving a DevioLab Score of 57.35. The strategy carries core status (is_core) and was designated through the protected manual or core selection criteria. Built for spot-style execution without synthetic leverage, the analysis is grounded strictly in historical trade records ending on August 10, 2026.
Trading rhythm and position duration
Across its total history, the algorithm recorded 194 completed trades. This trade count highlights a selective execution profile rather than continuous market participation. Specific parameters regarding average holding hours, median holding hours, and days between trade exits are unspecified in the provided dataset. Owing to the absence of explicit duration metrics, this model cannot be classified as a scalping system. Operating on 15-minute bar intervals, it triggers trades purely on systematic signal generation.
Quality of historical results
Out of 194 total closed positions, 148 trades ended in profit while 46 resulted in losses, delivering a win rate of 76.29%. Cumulative all-history return reached 385682.64%, which translates to an annualized return figure of 324.71%. The profit factor stands at a robust 3.75, showing that gross profits substantially outweighed gross losses. The average trade gain was 5.11%, with a median trade return of 6.07% and a best single trade return of 65.72%. Notably, the top 3 winning trades generated only 10.40% of the gross profit, demonstrating that overall gains were distributed across numerous trades rather than dependent on a few isolated outliers.
Risk, drawdown and losing behavior
Alongside its profitability metrics, the strategy exhibits significant drawdown characteristics. The maximum peak-to-trough drawdown reached 51.90%, placing the algorithm in the elevated drawdown category. The single worst trade registered a loss of -28.78%. The longest consecutive winning streak spanned 19 trades, whereas the longest losing streak was contained to 4 consecutive trades. While the low consecutive loss count underscores strong performance during favorable trends, the overall drawdown severity requires careful risk management consideration.
Behavior through time and yearly stability
The provided dataset does not contain a populated yearly breakdown array. As a consequence, an empirical year-by-year distribution analysis cannot be established within this research report. Analysts should account for this structural data limitation when evaluating performance consistency across different market cycles.
Strengths and limitations
Key strengths of the model include its high win rate of 76.29%, strong profit factor of 3.75, healthy average return per trade of 5.11%, and low profit concentration with the top 3 winners representing just 10.40% of gross gains. A 19-trade winning streak further reflects solid trend capture. Limitations center on a substantial maximum drawdown of 51.90%, a worst single trade loss of -28.78%, zero trade activity since June 1, 2024, and the lack of annual breakdown and holding time metrics in the dataset.
DevioLab analytical conclusion
With a DevioLab score of 57.35 and rank 2 for the DOT asset, this strategy presents a high-win-rate historical model with impressive overall gain metrics. However, its high historical equity drawdown exceeding 50% demands strict risk controls. This document serves as quantitative historical research and does not constitute financial or investment advice.
Data scope and methodology
All percentage metrics and statistics describe simulated historical closed trades. They do not represent exact Binance account performance and do not guarantee future returns. The dataset historical end date is August 10, 2026.