DCRUSDT
Crypto market · BinanceAlgorithmic Strategy Analysis for DCR · DCR on 15m Timeframe
A detailed quantitative review of the algorithmic strategy for DCR on the 15-minute timeframe. Based on a historical sample of 165 trades over six years, this report analyzes profitability, drawdown profile, and trade frequency.
Analysis as of 14.08.2026. Strategy data is updated separately.Read full analysis
Strategy profile
This algorithmic trading model is tailored for the DCR cryptocurrency asset on a 15-minute chart interval. Within the performance ranking for this ticker, the strategy holds the 5th position with a DevioLab Score of 45.94. The historical dataset covers the timeframe from July 30, 2020, to August 11, 2026, representing roughly 6.03 years of historical market observation. Over this period, the strategy executed a total of 165 completed trades, indicating a selective entry mechanism despite the short candle duration.
Trading rhythm and position duration
Across the 6.03-year evaluation period, the strategy generated an average of 27.35 trades per year. This frequency demonstrates a measured pace rather than continuous exposure. Specific metrics for average holding hours or median days between exit points are not present in the dataset; however, the low annual trade count confirms that the strategy operates selectively, waiting for specific market conditions before opening positions.
Quality of historical results
The overall historical profit recorded by the strategy reaches 1546604.80%, translating to an annualized return figure of 565.46%. Out of 165 closed trades, 117 were profitable and 48 resulted in losses, achieving a win rate of 70.91%. The average trade gain was 7.58%, while the median trade stood at 7.85%. The profit factor reached 5.0, underscoring a strong ratio of gross gains to gross losses. Furthermore, the top 3 winning trades contributed 10.99% of total gross profit, showing that overall returns were not overly reliant on a few extreme outlier trades.
Risk, drawdown and losing behavior
Despite a high win rate, the strategy exhibits notable tail risk and drawdowns. The maximum historical drawdown reached 47.83%, while the single worst trade produced a loss of -46.74%. This indicates that an adverse trade can consume a substantial portion of portfolio equity. The longest winning streak spanned 16 consecutive trades, compared to a maximum losing streak of 5 trades. The severity of the worst trade highlights the need for strict risk management when reviewing this quantitative model.
Behavior through time and yearly stability
A detailed year-by-year breakdown is not available in the provided dataset, so evaluation across specific calendar years relies on cumulative metrics. Over the entire 6.03-year backtest, the strategy maintained positive expectation and strong trade metrics. However, without annual performance breakdowns, it is not possible to confirm whether returns were evenly distributed across all market regimes or concentrated in specific high-volatility cycles for DCR.
Strengths and limitations
Key strengths of the strategy include a robust win rate of 70.91%, a profit factor of 5.0, and low profit concentration, with the top 3 trades representing only 10.99% of gross profits. Major limitations include a maximum drawdown of 47.83% and a worst trade loss of -46.74%. Additionally, a total sample size of 165 trades over six years remains moderate, which limits the statistical power of the backtest.
DevioLab analytical conclusion
The 15-minute DCR strategy demonstrates high historical efficiency in terms of win rate and profit factor, securing 5th rank among models for this asset with a DevioLab Score of 45.94. While the return metrics are high, the presence of substantial single-trade losses and an extended recent period of zero trades require careful consideration by quantitative researchers.
Data scope and methodology
All figures and percentage values reflect historical simulated trade executions from July 2020 through August 2026. They do not represent live trading results on Binance nor do they guarantee future performance. This analysis is prepared solely for research and educational purposes.