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公开目录 · DEVIOLAB

策略目录

探索算法策略、比较表现,并查看每个模型的完整历史。
不知道从哪里开始?
1. 目录 2. 选择 Core 1 3. 加入篮子 4. API 密钥 5. 激活交易机器人
我们的建议: 首次配置建议使用 Core 1——这是 DevioLab 的主要、更稳健的筛选。Core 2 适合明确愿意承受更高风险和更深回撤的用户。
i
什么是 Core 1 和 Core 2?
DevioLab 会分析加密货币和股票市场策略,并整理成可直接使用的精选组合,让您无需手动筛选数百种方案。
★ Core 1
由 DevioLab 筛选的加密货币与股票策略组合,作为主要、更均衡且更稳健的起步选择,重点控制风险与回撤。
◆ Core 2
DevioLab 的独立进取型精选,适合明确愿意承受更高风险和更深回撤,以换取潜在更高收益的用户。
所选策略概览

STRKUSDT

加密市场 · Binance
STRK 215000 +27067.03% 1TRAD-MVQ5
DevioLab 推荐 · Core 1 iDevioLab 主要推荐:更加防御、平稳且稳定的配置,重点控制风险和回撤。
DevioLab 推荐 · Core 2 iDevioLab 更激进的推荐:接受更高风险和更深回撤,以换取潜在更高回报。
68交易
82.4%胜率
+9.47%平均交易
+52.06%最佳交易
-15.50%最差交易
+20,865.1%年化
策略分析档案 · 11a69a65b3457dcf

Quantitative Strategy Analysis: STRK · STRK on 15m Interval

Quantitative breakdown of the algorithmic model STRK 215000 +27067.03% 1TRAD-MVQ5 for STRK. The strategy ranks first for this ticker with a DevioLab Score of 77.10, featuring an 82.35% win rate and a Profit Factor of 5.0.

阅读完整分析

Strategy profile

The algorithmic trading strategy STRK 215000 +27067.03% 1TRAD-MVQ5 is designed for the crypto asset STRK on the 15-minute timeframe. Within the DevioLab ranking framework for this ticker, it holds the top rank with an overall DevioLab Score of 77.10. The backtested dataset spans approximately 2.48 years, starting from February 20, 2024, through August 14, 2026. Over this historical window, the model executed 68 completed trades, providing a quantitative sample to evaluate its statistical distribution under non-leveraged spot market conditions.

Trading rhythm and position duration

The strategy operates with a selective trading frequency, generating 68 completed trades across the 2.48-year sample period. This translates to an annualized rate of approximately 27.40 trades per year. Although built on a 15-minute candle structure, the logic avoids over-trading and focuses on specific market triggers. Detailed duration metrics, such as average holding hours, median holding hours, and median days between exits, are not available in the provided stats. However, the low trade count indicates a disciplined execution rhythm rather than continuous market engagement.

Quality of historical results

Historical performance is characterized by high win accuracy and strong payoff efficiency. Out of 68 total trades, 56 were profitable and 12 were loss-making, yielding a win rate of 82.35%. The system achieved a Profit Factor of 5.0, meaning total gross profits were five times larger than total gross losses. The overall historical gain reached 27067.03%, translating to an annualized figure of 20865.12%. The average return per trade was 9.48% with a median trade return of 8.67%. The single best trade delivered 52.06%, while the top three winning trades accounted for 19.11% of gross profits, demonstrating a healthy profit distribution without extreme outlier dependency.

Risk, drawdown and losing behavior

Risk parameters show manageable downside relative to total return. The maximum historical equity drawdown was capped at 24.22%. The worst single losing trade recorded a loss of -15.50%. Analysis of streak dynamics shows a maximum winning streak of 12 consecutive trades and a maximum losing streak of just 2 consecutive trades. This tight losing streak behavior highlights the strategy's capacity to minimize prolonged drawdown spells.

Behavior through time and yearly stability

Across the 2.48-year evaluation window, explicit calendar-year breakdowns are not available in the source data. Nevertheless, the consistency of the strategy's mathematical expectation is reflected in the close proximity of the average trade gain (9.48%) to the median trade gain (8.67%). This alignment suggests that returns were generated fairly steadily during active trading phases rather than being distorted by isolated skewness.

Strengths and limitations

Core strengths of the strategy include its high Profit Factor of 5.0, an 82.35% win rate, and a short peak losing streak of only 2 trades. Profit concentration is low, with the top three winning trades representing only 19.11% of gross profits. Key limitations include the modest overall sample size of 68 trades, the concentration of trading activity in early 2024, and zero trade triggers after June 1, 2024. Furthermore, the maximum drawdown of 24.22% and worst trade loss of -15.50% underline the necessity of prudent position sizing.

DevioLab analytical conclusion

The STRK 215000 +27067.03% 1TRAD-MVQ5 strategy stands out as the highest-ranked quantitative model for STRK on the 15-minute timeframe, backed by an impressive 77.10 DevioLab Score. Its historical win rate and profit factor highlight strong efficiency when setup criteria are met. However, the extended inactivity following May 2024 warrants careful monitoring to ensure the algorithm aligns with evolving market regimes in STRK.

Data scope and methodology

This analysis is based on historical simulated backtest results of closed trades for STRK on a 15m interval from 2024-02-20 to 2026-08-14. All percentage figures describe simulated past execution and do not represent actual live Binance account returns or guarantee future profitability. This study is provided strictly for educational and analytical purposes and does not constitute financial advice.