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Our recommendation: for your first setup, use Core 1 — DevioLab’s primary, more protected selection. Core 2 is intended for users who knowingly accept higher risk and deeper drawdowns.
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What are Core 1 and Core 2?
DevioLab analyzes crypto and stock-market strategies and builds ready-made selections so you do not have to manually review hundreds of options.
★ Core 1
A DevioLab-selected collection of crypto and stock strategies recommended as the primary, more balanced and protected starting choice, with emphasis on risk and drawdown control.
◆ Core 2
A separate, more aggressive DevioLab selection for users who knowingly accept higher risk and deeper drawdowns in exchange for potentially higher returns.
Selected strategy overview

RAYUSDT

Crypto market · Binance
RAY 215000 +237631.08% 1TRAD-VYD3
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.
103Trades
78.6%Win rate
+8.80%Avg trade
+83.00%Best trade
-44.95%Worst trade
+2,929.1%Annualized
Strategy analytical profile · 0d8bd6b5c6153bf9

RAY · RAY: 15-Minute Quantitative Strategy Performance Analysis

A historical evaluation of the second-ranked quantitative trading strategy for RAY on a 15-minute chart, featuring an 81-win track record out of 103 trades, a 78.64% win rate, and a profit factor of 2.50.

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Strategy profile

This quantitative trading model for RAY is engineered for a 15-minute candlestick timeframe within the spot crypto market structure. Across its total recorded historical dataset ending August 10, 2026, the strategy completed 103 trades. It ranks second among strategies evaluated for this specific token, securing a DevioLab score of 67.36. Cumulative historical closed-trade profitability reached 131653.79%, with an annualized calculation metric of 2929.07%. Out of 103 trades, 81 yielded positive returns and 22 resulted in losses, establishing a win rate of 78.64%.

Trading rhythm and position duration

The algorithm recorded 103 completed executions over its historical evaluation window. Granular duration metrics, including average holding hours, median holding hours, and average days between trade exits, are unavailable in the source statistics. Because trade triggers are derived from 15-minute price bars, execution frequency fluctuates based on structural market conditions rather than fixed time intervals. Analysts should recognize that exact position duration dynamics remain unmeasured within this dataset.

Quality of historical results

The historical performance reflects high trading efficiency, highlighted by a overall profit factor of 2.50. The average trade expectation is a positive 8.80%, while the median return per trade stands at 5.95%. The distribution of winning trades exhibits healthy stability: the top three winning transactions accounted for 20.91% of total gross historical profit. This indicates that performance was not dependent on an isolated black-swan winner, but sustained across multiple trends, further supported by a peak winning streak of 25 consecutive trades.

Risk, drawdown and losing behavior

Despite maintaining a high win rate, the system subjects capital to notable drawdowns. Peak historical drawdown reached 50.43%, placing this model in the elevated drawdown category. Among the 22 losing trades, the single worst trade registered a decline of negative 44.95%. Conversely, the longest losing streak was limited to 3 consecutive trades. This combination shows that while losing streaks are short, individual bad exits can cause substantial balance drawdowns.

Behavior through time and yearly stability

Yearly breakdown tables and annual consistency metrics are not available in the primary dataset for this algorithm. Consequently, multi-year performance stability across individual calendar years cannot be verified. Evaluators must note that without annual trade distribution data, judging how the model navigated specific macroeconomic cycles or historical crypto market phases remains statistically limited.

Strengths and limitations

Key strengths include a strong historical win rate of 78.64%, a profit factor of 2.50, and low profit concentration with top winners generating only 20.91% of gross gains. A 25-trade winning streak demonstrates robust trend capture capabilities. Significant limitations include a maximum drawdown of 50.43%, a worst single loss of negative 44.95%, zero trade activity since mid-2024, and the absence of duration metrics.

DevioLab analytical conclusion

Holding the second rank for RAY with a score of 67.36, this 15-minute quantitative model demonstrates impressive historical return metrics and trade precision. However, the severe peak drawdown of 50.43% and a worst trade of negative 44.95% mandate strict risk management guidelines. The absence of trade executions since June 2024 requires further verification before evaluating live applicability.

Data scope and methodology

This analysis reflects simulated historical closed trades for RAY through August 10, 2026. Figures are derived from backtested quantitative data and do not represent actual live exchange returns or future profit guarantees. All analytical observations rely exclusively on the provided statistical record without external assumptions.

Full strategy analysis