RVNUSDT
Kryptomarkt · BinanceQuantitative Strategy Analysis for RVN · RVN on 15m Timeframe
A detailed people-first research analysis of an algorithmic strategy for RVN on the crypto spot market. Ranked number one for this ticker by DevioLab, the strategy achieves a DevioLab Score of 73.49, featuring a profit factor of 5.0, a 78.49% win rate, and a max drawdown of 21.32%.
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Strategy profile
This quantitative algorithmic analysis focuses on the crypto spot market asset RVN · RVN using a 15-minute timeframe (15m). Within the DevioLab scoring framework, this strategy secures rank 1 for the ticker with an overall DevioLab Score of 73.49. Operating on spot execution rules, the model presents a strong profit factor of 5.0, demonstrating a substantial mathematical margin of gross profits relative to gross losses across its historical dataset.
Trading rhythm and position duration
Over its recorded historical dataset, the strategy executed and closed 93 trades. Because specific duration metrics—such as average and median holding hours or days between exits—are not present in this dataset scope, the trade cadence must be viewed through the lens of its 15-minute chart resolution and total trade count. A total sample size of 93 completed trades represents a compact dataset, meaning individual trades carry meaningful weight in overall performance calculations. Based on trade volume, the model does not classify as high-frequency trading.
Quality of historical results
Historical metrics display robust performance within the 93 completed trades. The percentage of winning trades stands at 78.49% (73 wins versus 20 losses). The average trade return reaches 8.65%, while the median trade return is recorded at 6.99%. The best individual trade delivered a gain of 100.93%. Cumulative historic gain reached 87632.94%, translating to an annualized performance metric of 1267.38%. Crucially, the top three winning trades generated 22.86% of total gross profit, confirming that overall profitability is evenly distributed rather than dependent on a single outlier event.
Risk, drawdown and losing behavior
The maximum historical drawdown across the evaluation window reached 21.32%, representing a disciplined risk exposure relative to the total accumulated gains on the crypto spot market. The worst individual trade generated a loss of -18.10%. Streak behavior heavily favors positive runs: the longest winning streak reached 16 consecutive trades, whereas the longest losing streak was capped at 4 trades. The profit factor of 5.0 highlights strong structural edge during periods of market adversity.
Behavior through time and yearly stability
Detailed yearly breakdown data and dataset start dates are unavailable in the provided metrics, limiting period-by-period comparative stability analysis. The recorded history window concludes on 2026-08-10. Without yearly breakdowns, performance consistency must be evaluated through the aggregated sample of 93 trades. Further live forward-testing will be essential to monitor how the strategy adapts across changing market regimes.
Strengths and limitations
Key strengths of this model include its high win rate of 78.49%, an impressive profit factor of 5.0, and a contained maximum drawdown of 21.32%. The moderate gross profit contribution from the top three trades (22.86%) indicates healthy distribution among winning setups. Primary limitations include the modest sample size of 93 trades, zero trade executions since mid-2024, and missing granular data regarding position holding duration and yearly metrics.
DevioLab analytical conclusion
The strategy holds rank 1 for RVN with a DevioLab Score of 73.49 based on its strong historical win rate and risk-adjusted metrics. However, the limited sample size of 93 completed trades combined with trading inactivity after June 2024 warrants a prudent approach. Quantitative researchers should evaluate these results as historical simulated research rather than indicative of future performance.
Data scope and methodology
All percentage figures and performance statistics presented reflect simulated historical closed trades on crypto spot assets. They do not represent exact returns of a live trading account on Binance and do not guarantee future performance. This analysis relies strictly on the provided statistical dataset without external predictions or unverified assumptions.