ZILUSDT
Crypto market · BinanceAlgorithmic Strategy Analysis for ZIL · ZIL on the 15-Minute Timeframe
A quantitative evaluation of the ZIL algorithmic model featuring a profit factor of 5.0, a 72.06% win rate, and a historical maximum drawdown of 58.27%.
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Strategy profile
This algorithmic trading model is designed for the crypto asset ZIL using a 15-minute timeframe (15m). Within the DevioLab quantitative ranking framework, this strategy holds the rank 1 position for the ticker, earning a DevioLab Score of 48.94. The model is designated as a core strategy. Over its recorded simulation dataset, it registered a cumulative all-time return of 168202.17%, translating to an annualized performance estimate of 518.14%. Underlying technical indicators, trade triggers, and leverage settings are unstated in the provided statistical record, making this analysis purely performance-driven.
Trading rhythm and position duration
The strategy completed a total of 204 closed trades across its recorded history. Because explicit duration metrics such as average or median holding hours, trades per year, and trades per active month are missing from the dataset, this strategy cannot be characterized as scalping despite operating on a 15-minute chart. A total sample size of 204 trades indicates a selective execution model that enters positions only under specific market conditions rather than engaging in high-frequency trading.
Quality of historical results
The historical trade distribution demonstrates strong statistical efficiency. Out of 204 completed trades, 147 were profitable and 57 ended in losses, yielding a win rate of 72.06%. The profit factor stands at 5.0, reflecting gross profits five times larger than gross losses. The average trade gain was 4.67%, while the median trade gain reached 5.91%. The best single trade generated a 40.50% return. Importantly, the top three winning trades accounted for only 7.22% of gross profits, proving that performance is broadly distributed across many trades rather than dependent on extreme outliers. The longest winning streak reached 16 consecutive trades.
Risk, drawdown and losing behavior
Alongside its profitability metrics, the strategy exhibits an elevated risk profile. The maximum peak-to-trough drawdown reached 58.27%, necessitating careful position sizing. The worst individual trade delivered a loss of -40.10%. Conversely, consecutive losses remained tightly contained, with the longest losing streak capped at just 3 trades. This indicates that while prolonged losing sequences are rare, individual drawdowns can be sharp when adverse moves occur.
Behavior through time and yearly stability
The dataset concludes on 2026-08-10, while the historical start date is unrecorded. Furthermore, explicit breakdown statistics by calendar year are unavailable. Consequently, temporal stability must be interpreted through the aggregate set of 204 trades rather than individual annual performance slices. Readers should account for this structural data limitation when considering long-term consistency across different market cycles.
Strengths and limitations
Key strengths include a strong 72.06% win rate, an outstanding profit factor of 5.0, high median trade returns (5.91%), and healthy profit distribution where the top three trades represent only 7.22% of gross gains. It is also the top-ranked strategy for this asset. Limitations include a severe maximum drawdown of 58.27%, a large worst-trade loss (-40.10%), zero trade activity since June 2024, and the lack of detailed holding duration metrics.
DevioLab analytical conclusion
The ZIL strategy displays exceptional historical performance quality, highlighted by a profit factor of 5.0 and a 72.06% win rate, supporting its rank 1 status and DevioLab Score of 48.94. However, potential users must weigh these strong return metrics against the elevated drawdown of 58.27% and the pause in trade executions since June 2024.
Data scope and methodology
This analysis is based on a historical backtest of 204 closed simulated trades on the ZIL 15m chart up to 2026-08-10. All quoted percentages describe historical simulated closed trades. They do not represent exact exchange account performance and do not guarantee future results.