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Visão geral da estratégia selecionada

PENGUUSDT

Mercado cripto · Binance
PENGU 215000 +6214.73% 1TRAD-HQS2
Recomendado pela DevioLab · Core 1 iRecomendação principal da DevioLab: perfil mais protegido, suave e estável, focado no controle de risco e drawdown.
Recomendado pela DevioLab · Core 2 iRecomendação mais agressiva da DevioLab: aceita maior risco e drawdowns mais profundos em troca de retornos potencialmente maiores.
126Operações
75.4%Taxa de acerto
+4.02%Operação média
+19.96%Melhor operação
-26.54%Pior operação
+7,745.0%Anualizado
Perfil analítico da estratégia · f36a6c6cdbc4db56

PENGU · PENGU 15-Minute Algorithmic Trading Strategy Performance with 5.0 Profit Factor

In-depth quantitative analysis of the PENGU 215000 +6214.73% 1TRAD-HQS2 trading model on the 15m crypto timeframe. Featuring a DevioLab Score of 76.16 and rank 1 for this asset, the strategy earned 7745.04% total return across 126 completed trades with a 75.4% win rate.

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Strategy profile

This quantitative trading strategy is tailored for the spot crypto market using a 15-minute execution frame on PENGU (PENGU). Based on rigorous statistical evaluation, the model achieved a DevioLab Score of 76.16, ranking 1st among evaluated strategies for this ticker. Designated as PENGU 215000 +6214.73% 1TRAD-HQS2, the execution methodology isolates directional momentums without relying on qualitative assumptions.

Trading rhythm and position duration

The algorithm generated 126 closed trades throughout its recorded backtest history. Duration-specific metrics such as average and median holding hours are unavailable in this sample set. Nevertheless, the trade count across the 15m timeframe indicates a selective entry system that refrains from overtrading, waiting for distinct structural setups rather than engaging in high-frequency scalping.

Quality of historical results

Historical execution reveals strong statistical edge. Out of 126 completed trades, 95 ended in profit, delivering a 75.4% win rate alongside 31 losing positions. Total cumulative return across all recorded data stands at 7745.04%. The strategy maintained a profit factor of 5.0, reflecting robust gain-to-loss asymmetry. The average trade returned 4.02%, while the median trade achieved 5.15%. System balance is further proved by the fact that the top 3 winning trades contributed only 7.44% of total gross profit, confirming that overall return is driven by consistency rather than lucky outliers.

Risk, drawdown and losing behavior

Risk parameters indicate a maximum historical equity drawdown of 26.54%. The single worst trade recorded a loss of -26.54%, aligning directly with the maximum drawdown peak. The strategy posted an impressive maximum winning streak of 17 consecutive trades, whereas its longest losing streak was capped at just 3 trades, demonstrating strong resilience during adverse market phases.

Behavior through time and yearly stability

While the strategy dataset concludes on 2026-08-10, granular yearly breakdown data is not present in the source metrics. Because annual segmented statistics are unavailable, long-term consistency cannot be evaluated on a year-by-year basis. Consequently, performance must be evaluated across the full aggregated sample of 126 trades.

Strengths and limitations

Key strengths include a high profit factor of 5.0, a 75.4% win rate, a maximum winning streak of 17 trades, and low profit concentration (top 3 trades accounting for 7.44% of gross profit). The primary limitations center on a moderate sample size of 126 trades, missing holding period metrics, and zero closed positions in the period since June 1, 2024.

DevioLab analytical conclusion

The model demonstrates exceptional quantitative metrics for PENGU on the 15-minute timeframe, holding rank 1 for this ticker with a DevioLab Score of 76.16. Its high win rate and short maximum losing streak point to effective entry filtering. However, the lack of recent trades since mid-2024 suggests traders should carefully verify active market conditions before assuming forward continuity.

Data scope and methodology

All figures presented in this research are derived from a simulated historical backtest on closed trades for PENGU on a 15m timeframe ending on 2026-08-10. These historical percentage results do not represent actual live Binance account equity and do not guarantee future returns. This content is provided strictly for quantitative research purposes and does not constitute financial advice.

Análise completa da estratégia