DCRUSDT
Crypto market · BinanceDCR · DCR Quantitative Strategy Analysis: 15-Minute Algorithmic Performance
An in-depth evaluation of the DCR 215000 +4238690.37% 1TRAD-QUD5 quantitative strategy on the 15-minute timeframe, featuring 495 historical trades, a 70.3% win rate, and a 66.58% maximum drawdown.
Analysis as of 14.08.2026. Strategy data is updated separately.Read full analysis
Strategy profile
This quantitative trading model is engineered for the DCR cryptocurrency asset on a 15-minute timeframe (15m). Within the overall strategy ranking for this specific ticker, the model occupies rank 3 with a DevioLab Score of 51.51. Designed for spot market execution, the algorithm seeks to capture systematic price movements. Across its recorded operational history, the strategy generated a total of 495 completed trades, operating with a structured approach to position entries and exits.
Trading rhythm and position duration
The model executed 495 completed trades over its backtested history, comprising 348 winning trades and 147 losing trades. Specific metrics regarding average or median holding hours, trades per active month, and trade frequency per year are not provided in this dataset sample. Consequently, this model should not be classified as scalping without duration metrics. Trading execution is dictated strictly by the algorithmic rules triggered on the 15-minute chart interval.
Quality of historical results
Historical performance figures reflect a strong cumulative gain across the backtest horizon. Total cumulative historical return reached 3668139.3%, with an annualized metric of 816.41%. The win rate reached a robust 70.3%, supported by a profit factor of 2.14, demonstrating that historical gross profits significantly exceeded gross losses. The average trade returned 2.85%, while the median trade yield stood at 3.65%. Notably, the top 3 winning trades accounted for only 4.42% of total gross profit, confirming that performance was driven by consistent statistical distribution rather than isolated extreme price spikes.
Risk, drawdown and losing behavior
Despite strong overall returns, the system experienced severe historical peak-to-trough drawdowns. The maximum historical drawdown reached 66.58%, underscoring the exposure to equity pullbacks during unfavorable market regimes. The single worst trade recorded a loss of -36.23%, compared to a best single trade return of 46.35%. The longest winning streak spanned 17 consecutive trades, whereas the longest losing streak was contained to 5 consecutive trades out of 147 total losing trades.
Behavior through time and yearly stability
Detailed yearly performance breakdown metrics are not present in this dataset execution log. Performance is evaluated on an aggregate basis up to the dataset end date of August 10, 2026. Without year-by-year distribution metrics, comparative stability across individual calendar years cannot be definitively established, requiring caution when projecting performance across changing market volatility cycles.
Strengths and limitations
Key strengths include a high historical win rate of 70.3%, a healthy profit factor of 2.14, a modest maximum losing streak of 5 trades, and excellent gain distribution where the top 3 trades generated only 4.42% of total gross profit. Limitations center around a substantial maximum drawdown of 66.58%, a severe worst-case loss per trade of -36.23%, zero recent trade executions since June 2024, and the lack of detailed holding duration telemetry.
DevioLab analytical conclusion
Holding a DevioLab Score of 51.51 and ranking 3rd for DCR, this quantitative model demonstrates strong historical return metrics alongside solid trade win consistency. However, the high peak-to-trough drawdown of 66.58% and recent inactivity since June 2024 highlight the importance of disciplined position sizing and risk control. It represents an informative benchmark for algorithmic research on DCR.
Data scope and methodology
This research is based on historical backtested data ending on August 10, 2026. All percentage figures describe simulated closed trades from historical data. They do not represent exact live Binance account execution returns and provide no guarantee of future trading performance.