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DevioLab analiza estrategias de criptomonedas y del mercado bursátil y crea selecciones listas para usar, para que no tengas que revisar cientos de opciones manualmente.
★ Core 1
Una selección de estrategias de cripto y acciones elegida por DevioLab como opción principal, más equilibrada y protegida para empezar, con énfasis en el control del riesgo y del drawdown.
◆ Core 2
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.
Resumen de la estrategia seleccionada

ONTUSDT

Mercado cripto · Binance
ONT 215000 +2117083.35% 1TRAD-BED8
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.
254Operaciones
74.0%Tasa de acierto
+4.50%Operación media
+38.69%Mejor operación
-31.83%Peor operación
+757.4%Anualizado
Perfil analítico de la estrategia · 0e485c17266f187b

Algorithmic Strategy Analysis for ONT · ONT on 15-Minute Interval

An analytical study of the ONT 215000 +2117083.35% 1TRAD-BED8 algorithmic trading model for the ONT asset. Ranking first among strategies for this ticker with a DevioLab score of 52.84, the strategy generated a 73.62% win rate and a profit factor of 2.50 across 6.14 years of historical data.

Leer análisis completo

Strategy profile

The algorithmic trading strategy designated as ONT 215000 +2117083.35% 1TRAD-BED8 is constructed for the crypto asset ONT on the 15-minute timeframe. Within the DevioLab ranking for this specific ticker, the strategy holds the 1 position, earning an overall DevioLab score of 52.84. This score reflects the balance between historical profitability metrics and drawdown parameters across the evaluated dataset. The configuration is a non-core variant recorded in the research repository. The underlying dataset covers 6.14 years of historical price action, spanning from June 22, 2020, to August 11, 2026.

Trading rhythm and position duration

Over the full 6.14-year sample, the strategy completed 254 closed trades. This equates to an average trading frequency of approximately 41.40 trades per year. Given this moderate pace, the strategy cannot be categorized as scalping despite operating on a 15-minute chart. Specific metrics regarding average or median holding hours and average days between exits are not available in the provided statistics. However, the total trade count confirms a selective entry discipline rather than aggressive high-frequency turnover.

Quality of historical results

Cumulative historical return reached 665228.70%, translating to an annualized gain of 628.70%. Out of 254 total executions, 187 trades closed in profit while 67 resulted in losses, delivering a win rate of 73.62%. The strategy maintained a profit factor of 2.50, demonstrating that gross profits comfortably exceeded gross losses. The average trade yield was 4.44%, while the median trade yield stood at 5.97%. The single best trade delivered a 38.69% gain. Profit distribution is well-balanced across trades, as the top three winning trades accounted for only 5.88% of total gross profit.

Risk, drawdown and losing behavior

The strategy recorded a maximum peak-to-trough drawdown of 64.75%, placing it in an elevated risk tier. The single worst trade registered a drawdown of -31.83%. Offsetting this exposure, the model displays strong recovery mechanics during losing phases, with its longest losing streak limited to just 4 consecutive trades. By comparison, the longest winning streak extended to 19 consecutive profitable trades. While the low losing streak helps preserve equity momentum, the overall drawdown figure highlights the necessity of strict risk management.

Behavior through time and yearly stability

Granular annual breakdowns are not included in the dataset, limiting year-by-year comparative breakdown. Across the overall 6.14-year horizon, signal generation remained stable at roughly 41.40 trades annually. The strategy maintains a positive mathematical expectancy underpinned by its 73.62% win rate and 2.50 profit factor. The absence of yearly statistical slices requires caution when evaluating performance consistency across varying crypto market cycles.

Strengths and limitations

Primary strengths include a high historical win rate of 73.62%, a robust profit factor of 2.50, and a well-distributed profit curve where the top three winning trades contribute only 5.88% of gross gains. Additionally, losing streaks are short, capping at 4 consecutive losses. Limitations include a severe maximum drawdown of 64.75%, a substantial worst-trade drawdown of -31.83%, zero trade activity after June 1, 2024, and incomplete statistics regarding holding durations.

DevioLab analytical conclusion

The ONT 215000 +2117083.35% 1TRAD-BED8 strategy ranks 1 for the ONT asset on DevioLab, driven by strong underlying metrics, high win rate, and an average trade return of 4.44%. Its historical statistical profile shows reliable trade distribution over 6.14 years. However, the 64.75% maximum drawdown and the absence of trades after June 2024 underscore the importance of risk controls and continuous monitoring before live execution.

Data scope and methodology

All figures presented in this analysis are derived from backtested simulated closed trades between June 22, 2020, and August 11, 2026, on 15-minute price data for ONT. Performance metrics describe historical backtest outcomes, do not represent actual Binance account trading returns, and offer no guarantee of future results.

Análisis completo de la estrategia