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STRATEGY CATALOG

Explore algorithmic strategies, compare performance and open the complete history of every model.
Each algorithmic strategy corresponds to a real trading agent (Trading Bot) created by the DevioLab team from historical-data testing. It can be used for automated trading through supported exchange APIs — Binance, OKX, Bybit, Gate.io, KuCoin and others as they are enabled — or as a Signal Bot with Telegram and email notifications.
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SEIUSDT

Crypto market · Binance
SEI 215000 +23725.15% 1TRAD-YXV1
Recommended by DevioLab · Core 1 iPrimary DevioLab recommendation: a more protected, smoother and more stable profile focused on risk and drawdown control.
Recommended by DevioLab · Core 2 iMore aggressive DevioLab recommendation: accepts higher risk and deeper drawdowns in exchange for potentially higher returns.
56Trades
83.9%Win rate
+11.28%Avg trade
+46.55%Best trade
-16.39%Worst trade
+2,644.4%Annualized
Strategy analytical profile · f9867e7305610c01

Quantitative Analysis of SEI · SEI Algorithmic Trading Strategy

A detailed quantitative evaluation of the top-ranked core trading model for SEI on the 15-minute timeframe, featuring an 83.93% win rate and a cumulative return of +23725.15% across historical backtesting.

Analysis as of 12.08.2026. Strategy data is updated separately.
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Strategy profile

The trading strategy SEI 215000 +23725.15% 1TRAD-YXV1 ranks first among evaluated models for SEI in the cryptocurrency market. Operating on a 15-minute candle interval, this core model generated a total historical return of +23725.15% over a dataset spanning nearly three years from August 15, 2023, to August 12, 2026. With an overall DevioLab score of 70.67, the system is designed to capture structural price movements in SEI spot trading while maintaining strict risk controls.

Trading rhythm and position duration

Over the 2.99 years covered by the dataset, the strategy executed a total of 56 completed trades, translating to approximately 18.70 trades per year. Because specific metrics for average holding hours and median days between exits are unavailable in this dataset, holding duration cannot be precisely calculated. However, the moderate annual trade frequency indicates a highly selective execution framework rather than high-frequency scalp trading, operating quietly on 15-minute price action.

Quality of historical results

Out of 56 completed positions, 47 closed in profit, yielding an exceptionally high win rate of 83.93%. The strategy achieved a profit factor of 5.00, demonstrating that gross profits outweighed gross losses by a factor of five. The average trade yield stood at 11.28%, with a median trade return of 9.55% and a maximum single trade gain of 46.55%. Crucially, performance was not dependent on a few outlier trades, as the top three winning trades accounted for only 18.69% of the gross profit.

Risk, drawdown and losing behavior

Risk management performance was stable throughout the historical testing period. The strategy incurred only 9 losing trades out of 56, maintaining a maximum losing streak of just 2 consecutive trades. In comparison, its longest winning streak reached 10 consecutive positive positions. The maximum recorded drawdown was limited to 16.39%, matching the magnitude of its single worst loss of -16.39%. This symmetry indicates that account equity drawdowns were largely tied to individual trade stops rather than compounding sequential losses.

Behavior through time and yearly stability

Granular yearly breakdown statistics are not available for this execution model. Nevertheless, the aggregate metrics show a calculated annualized return of 2644.35% over the 2.99-year historical timeframe. The system maintained robust overall stability across its 56 trades without experiencing cluster drawdown phases or extended losing sequences.

Strengths and limitations

The primary strengths of this model include an outstanding 83.93% win rate, a robust profit factor of 5.00, and a well-contained maximum drawdown of 16.39%. Furthermore, the low concentration of returns in top trades confirms balanced profitability across signals. The main limitation is the small sample size of 56 trades over nearly three years, alongside the total lack of active trade executions since June 1, 2024. Additionally, precise holding duration statistics are not documented.

DevioLab analytical conclusion

Scoring 70.67 and holding the top rank for SEI, this core strategy provides a mathematically compelling historical benchmark. Its high efficiency per trade and disciplined drawdown control make it a noteworthy model. However, potential practitioners should remain aware of the long periods of trade inactivity and the limited total trade count when considering systematic deployment.

Data scope and methodology

The statistics in this report cover simulated spot trading results for SEI between August 15, 2023, and August 12, 2026. The initial date represents the start of the available dataset rather than the official launch date of the asset. Percentages describe historical closed trades and do not reflect real-time execution slip, Binance exchange account returns, or guaranteed future performance.

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