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Una selección separada y más agresiva de DevioLab para usuarios que aceptan conscientemente mayor riesgo y drawdowns más profundos a cambio de una rentabilidad potencialmente mayor.
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Resumen de la estrategia seleccionada

FLNCBUSDT

Instrumento bursátil · ejecución mediante Binance
FLNCB 0 +63775.51% 1TRAD-UCS1
Recomendado por DevioLab · Core 1 iRecomendación principal de DevioLab: un perfil más protegido, suave y estable centrado en el control del riesgo y del drawdown.
Recomendado por DevioLab · Core 2 iRecomendación más agresiva de DevioLab: acepta mayor riesgo y drawdowns más profundos a cambio de rendimientos potencialmente superiores.
71Operaciones
71.8%Tasa de acierto
+11.44%Operación media
+114.03%Mejor operación
-21.94%Peor operación
+7,361.5%Anualizado
Perfil analítico de la estrategia · 6429d5bdbe5049a4

FLNC · Fluence Energy, Inc.: Quantitative Strategy Analysis on the 15-Minute Timeframe

Quantitative strategy report for Fluence Energy, Inc. on the 15-minute chart. Ranked 4th for this ticker with a DevioLab score of 72.37, the algorithm shows a 72.86% win rate and a cumulative historical return of 63,775.51% across 70 closed trades.

Leer análisis completo

Strategy profile

The algorithmic model FLNCB 0 +63775.51% 1TRAD-JJB6 is designed for trading Fluence Energy, Inc. stock on a 15-minute execution timeframe. Selected as the core1 balanced option, it holds rank 4 among tested strategies for this ticker with a DevioLab score of 72.37. The evaluation historical window spans from December 13, 2021 to August 19, 2026, totaling approximately 4.68 years of backtest data. Note that the dataset start date represents the beginning of the analyzed historical window, not the founding or listing date of the asset.

Trading rhythm and position duration

Over the 4.68-year dataset, the strategy executed 70 completed trades, corresponding to an average frequency of 14.95 trades per year. Operating on 15-minute candle intervals allows for fine-grained entry execution, yet the overall trade volume remains selective. This moderate frequency demonstrates a focus on quality signals rather than high-volume execution or scalping. Granular holding times in hours or days between exits are not recorded in this performance snapshot.

Quality of historical results

Out of 70 closed trades, 51 were profitable and 19 ended in a loss, resulting in a win rate of 72.86%. Total historical profit reached 63775.51%, which converts to an annualized calculation of 8195.81%. The average trade profit stands at 11.74%, while the median trade yield is 7.03%. The best single trade recorded a gain of 114.03%. The top 3 winning trades generated 29.79% of total gross profit, reflecting a healthy distribution of gains across the trading history.

Risk, drawdown and losing behavior

The strategy achieved a profit factor of 1.25, indicating that gross gains outweighed gross losses, albeit with notable drawdowns during adverse periods. The maximum historical drawdown was 39.21%, and the single worst trade loss reached -21.94%. The model sustained a maximum winning streak of 12 consecutive trades, compared to a maximum losing streak of 4 trades, demonstrating solid resilience during favorable market regimes.

Behavior through time and yearly stability

Annual performance breakdowns are omitted in this specific statistic summary. Nevertheless, the total sample of 70 trades across 4.68 years reflects a low-density trading schedule spread throughout the testing period.

Strengths and limitations

Key strengths include a strong 72.86% win rate, substantial overall historical growth of 63775.51%, a 12-trade win streak, and moderate concentration in top trades (29.79%). Primary limitations are the modest profit factor of 1.25, a maximum drawdown of 39.21%, a small sample size of 70 trades, and zero trade activity in the recent window since mid-2024.

DevioLab analytical conclusion

Attaining a DevioLab score of 72.37 and ranking 4th for Fluence Energy, Inc., this model provides an intriguing balanced approach on the 15-minute chart. Analysts evaluating this strategy should consider both its high historical win rate and the limitations posed by a small trade sample size combined with recent trading inactivity.

Data scope and methodology

This analysis relies on simulated backtest performance for FLNC from December 13, 2021 to August 19, 2026 on 15-minute price data. All metrics describe closed historical trades. They do not represent live brokerage account execution and do not constitute financial advice or guarantees of future performance.

Análisis completo de la estrategia