CRDO · Credo Technology Group Holding Ltd
Stock Universe · global stock marketCRDO · Credo Technology Group Holding Ltd High-Win-Rate 15-Minute Quantitative Strategy Analysis
An analytical evaluation of the top-ranked DevioLab quantitative strategy for Credo Technology Group Holding Ltd on a 15-minute timeframe. Featuring an 83.13% historical win rate, a 2.22 profit factor, and balanced profit distribution across 83 trades, this strategy demonstrates high statistical precision paired with notable downside exposure during isolated loss events.
Analysis as of 22.08.2026. Strategy data is updated separately.Read full analysis
Strategy profile
The quantitative trading strategy designated for CRDO · Credo Technology Group Holding Ltd on a 15-minute chart represents the top-rated algorithm for this ticker within the DevioLab framework, holding a DevioLab score of 81.22 and ranking first overall for the asset. Operating across a historical dataset spanning 4.57 years from January 27, 2022, to August 22, 2026, the strategy recorded a total of 83 completed trades. Out of these closed positions, 69 resulted in profits while 14 ended in losses, establishing a historical win rate of 83.13%. The cumulative performance across all historical trades reached 194,399.25%, translating to an annualized backtested figure of 20,242.21%. With a profit factor of 2.22, the strategy historically generated more than two dollars in gross winning trades for every dollar lost. This profile reflects a highly selective system that seeks high-probability trade setups on intraday price data while accepting occasional deeper trade pullbacks when positions move against the core statistical baseline.
Trading rhythm and position duration
Despite operating on a 15-minute bar interval, the strategy displays a remarkably low transaction frequency. Over the 4.57-year history window, the algorithm executed 83 completed trades, which corresponds to an average trade frequency of 18.17 trades per year, or approximately 1.5 completed trades per month. This low execution cadence indicates that the signal parameters are highly restrictive, avoiding frequent intraday trading or scalping behavior in favor of highly filtered entry conditions. Specific duration metrics, such as average holding hours, median holding hours, and days between exits, are not present in the statistical feed. Consequently, while the exact duration that individual positions remained open cannot be numerically quantified, the combination of a 15-minute execution chart with only 18 trades per year demonstrates that the algorithm spent substantial stretches of time out of active positions, waiting for specific price setups rather than actively churning equity.
Quality of historical results
Analyzing the payoff structure of the 83 completed trades reveals a healthy statistical balance between average performance and distribution spread. The average trade return stands at 10.68%, while the median trade return is 9.01%. The close proximity between the average and median trade metrics suggests that the strategy's overall profitability is not artificially skewed by a tiny handful of extreme outliers, but rather supported by consistent baseline gains across winning trades. The best single trade achieved a gain of 58.95%, whereas the worst single trade incurred a loss of -21.29%. A critical quality metric is the gross profit concentration: the top 3 winning trades accounted for only 14.83% of total gross profit. This unusually low concentration figure confirms that positive expectancy is broadly distributed across the 69 winning trades rather than dependent on lucky black-swan events. The strategy's payoff profile combines an exceptional 83.13% hit rate with robust trade-level profitability.
Risk, drawdown and losing behavior
Risk management metrics indicate a structural asymmetry between losing trade frequency and individual loss severity. The maximum drawdown recorded across the entire 4.57-year backtest was -21.29%. Notably, this maximum drawdown percentage exactly matches the single worst trade return of -21.29%. This numerical equality indicates that the strategy's historical peak-to-trough equity decline was primarily driven by a single severe trade adverse movement rather than a compounding chain of multiple consecutive losses. This interpretation is reinforced by the strategy's streak metrics: the longest losing streak consisted of just 1 trade, whereas the longest winning streak reached 11 consecutive winning positions. Thus, while losing streaks are statistically minimal, individual adverse exits can be relatively sharp, requiring strict equity resilience to withstand occasional -21.29% drawdowns within an otherwise high-win-rate sequence.
Behavior through time and yearly stability
Detailed annual breakdown statistics are omitted from the supplied dataset, preventing direct year-over-year comparisons of trade count, annual win rate, or yearly cumulative profit distribution. However, evaluating the broader temporal span provides important structural insights. Across the 4.57 years of evaluated history, the strategy averaged 18.17 trades annually. This uniform average across 83 total positions indicates consistent signal density over the multi-year dataset, without obvious evidence of extreme trade clustering or long multi-year operational gaps. Nonetheless, because specific yearly breakdowns are unavailable, the degree to which strategy performance was uniformly distributed across individual calendar years versus concentrated during specific market volatility regimes cannot be definitively confirmed from the raw statistical logs alone.
Recent period since 2024-06-01 versus full history
In evaluating performance from June 1, 2024, onward, the dataset records 0 completed trades during this recent observation window, leaving the sum of recent trade returns null. This complete absence of closed trade activity in the recent window creates a notable statistical gap. It indicates that either market price action during this period did not satisfy the algorithm's selective entry conditions or that active positions remained unclosed at the time of data extraction. From an analytical perspective, this zero-trade recent sample means that current statistical validation rests entirely on the multi-year history prior to June 2024. Investors and quantitative researchers must recognize that the strategy lacks recent empirical trade confirmation, increasing reliance on historical historical robustness rather than recent forward-tested execution.
Strengths and limitations
The primary strength of this quantitative model lies in its exceptional hit rate of 83.13% paired with a profit factor of 2.22 and a remarkably low gross profit concentration of 14.83% in its top 3 winners. Winning streaks reach up to 11 trades, and losing streaks never exceed a single trade in the historical record. On the limitation side, the strategy relies on a relatively modest sample size of 83 total trades over 4.57 years, yielding an average of only 18.17 trades per year. Furthermore, the absence of trades recorded since June 1, 2024, leaves recent dynamic stability unconfirmed. Lastly, while drawdown duration is limited by single-loss streaks, the magnitude of the single worst trade (-21.29%) highlights that individual losses can be substantial relative to the median trade gain of 9.01%.
DevioLab analytical conclusion
Holding the number one rank for CRDO · Credo Technology Group Holding Ltd with a score of 81.22, this 15-minute quantitative strategy represents a robust example of a high-win-rate trend-following or swing-filtering model. Its strength lies in high execution precision, strong average-to-median alignment, and low reliance on profit concentration from extreme outliers. However, potential operators must weigh these advantages against the low trade frequency of 18.17 trades per year, the single-trade drawdown magnitude of -21.29%, and the lack of closed trades in the recent sample window since June 2024. As with all backtested quantitative models, historical results reflect simulated strategy conditions and do not guarantee future performance in live market conditions.
Data scope and methodology
All analytical conclusions presented in this report are derived strictly from the backtested strategy performance data for CRDO · Credo Technology Group Holding Ltd on a 15-minute chart interval covering the period from January 27, 2022, to August 22, 2026. Metrics describe historical simulated closed trade performance and do not incorporate live brokerage execution factors such as exchange fees, order execution slippage, borrow costs, or variable liquidity dynamics. The history start date reflects the beginning of this specific strategy test dataset rather than the corporate history or public listing date of Credo Technology Group Holding Ltd. Past backtested performance is not indicative of future investment returns.