CAH · Cardinal Health Inc.
Stock Universe · mercado global de açõesCAH Algorithmic Strategy Analysis: 85.54% Win Rate and Multi-Week Swing Dynamics on 15-Minute Charts
An in-depth quantitative examination of a top-ranked algorithmic trading strategy for CAH stock, evaluated over a 7.03-year historical dataset from September 2019 to September 2026. Operating on a 15-minute price evaluation interval, the model achieves a high win rate of 85.54% across 83 completed trades, paired with a Profit Factor of 2.50 and a tightly bounded maximum drawdown of 12.89%. Despite using intra-day timeframe triggers, the strategy functions as a patient swing system with an average holding duration of 395.29 hours (~16.5 days). With a DevioLab score of 77.75 and ranking second overall for the asset, this strategy demonstrates broad profit distribution, low outlier reliance, and sustained efficacy across full-history and post-June 2024 evaluation windows.
Análise em 26.09.2026. Os dados da estratégia são atualizados separadamente.Ler análise completa
Strategy profile
This algorithmic trading strategy evaluates equity price action for CAH within a stock market context, utilizing a 15-minute chart interval to generate systemic entry and exit signals. Designed as an automated decision engine suitable for deployment within automated trading bots, trading robots, and intelligent trading agents, the model filters market noise to isolate high-probability swing opportunities. Over a continuous historical evaluation period extending from September 16, 2019, through September 26, 2026—spanning approximately 7.03 years—the strategy logged 83 fully completed trade cycles. Out of these 83 executions, 71 terminated in profitable closures while 12 resulted in losses, yielding an overall win rate of 85.54%. Cumulative uncompounded gain across the full history reached +3129.35%, supporting a Profit Factor of 2.50. These statistical attributes place the strategy at a DevioLab score of 77.75, securing the number 2 analytical rank among evaluated strategies for the CAH ticker. The strategy's profile is defined by extreme entry selectivity, long holding patience, and highly structured downside containment.
Trading rhythm and position duration
Although the strategy samples market structure on a granular 15-minute candlestick frequency, its execution pacing reflects a patient multi-week swing methodology rather than high-frequency intraday churn. Over the 7.03-year history, the strategy closed an average of 11.81 trades per year, which translates to approximately 1.36 completed trades per active trading month. Position holding times reflect substantial duration: the average holding time across all 83 completed trades is 395.29 hours (approximately 16.47 days), while the median holding duration stands at 269.75 hours (approximately 11.24 days). The divergence between average and median holding durations indicates that while the typical position remains open for nearly two calendar weeks, occasional trades extend across multi-month holding horizons to capture prolonged directional trends. Furthermore, the average interval between consecutive trade exits is 30.92 days, with a median of 26.60 days. This sparse trade frequency demonstrates that automated trading agents executing this decision logic remain flat for extended stretches, prioritizing high signal purity over high transaction velocity.
Quality of historical results
The statistical distribution of trade returns confirms that the strategy's profitability relies on consistent structural accuracy rather than isolated extreme outliers. The average trade yield stands at +4.68%, closely tracking the median trade return of +3.77%. This narrow delta between average and median returns indicates a symmetrical, dependable distribution of winning trades without heavy skewness. The strategy achieved an exceptional maximum winning streak of 20 consecutive profitable trades, whereas the longest losing streak was capped at just 3 trades. While the single best trade reached a gain of +40.24%, gross profit concentration remains exceptionally low: the top 3 largest winning trades account for only 17.80% of total gross historical profits. This implies that over 82% of gross gains were generated across the remaining 68 winning transactions. A Profit Factor of 2.50 combined with an 85.54% hit rate reinforces that the decision engine systematically captures positive expectation without relying on rare black-swan gain events.
Risk, drawdown and losing behavior
Downside risk control within the strategy exhibits remarkable alignment between individual trade stop limits and overall portfolio equity drawdown. The maximum historical drawdown experienced over the 7.03-year backtest was 12.89%, a figure that corresponds almost perfectly with the worst single losing trade recorded at -12.89%. This structural overlap reveals that portfolio equity contractions are primarily driven by isolated single-trade stop events rather than compounding multi-trade loss spirals. Because the longest losing streak did not exceed 3 trades, equity curves recovered rapidly without encountering persistent drawdown regimes. The risk-reward architecture operates on a high-precision hit rate model; losses, while occasionally larger than the average winning trade (+4.68%), are sufficiently infrequent (14.46% loss frequency) and tightly capped (-12.89% maximum loss) that aggregate portfolio equity trends steadily upward. For operators of automated trading robots, this downside structure provides clear, predictable risk limits during adverse price environments.
Behavior through time and yearly stability
An analysis of yearly performance breakdowns from 2019 through 2026 reveals remarkable temporal stability, with every single calendar year producing positive aggregate trade yields. In 2019 (partial year from September 16), the strategy logged 4 trades with a 75.00% win rate and a cumulative return of +20.68%. Momentum expanded in 2020, yielding 14 trades, 13 wins (92.86% win rate), and a +67.07% return. In 2021, 11 trades produced 9 wins (81.82% win rate) and +33.96%. The year 2022 represented a peak activity cycle with 15 trades, 13 wins (86.67% win rate), and a cumulative return of +77.65%. Activity slowed in 2023 to 7 trades, yet maintained high accuracy with 6 wins (85.71% win rate) yielding +22.03%. In 2024, 13 trades delivered 10 wins (76.92% win rate) and +48.47%. The year 2025 demonstrated perfect execution quality, closing 11 out of 11 trades profitably (100.00% win rate) for a total return of +64.27%. Finally, 2026 (through September 26) logged 8 trades, 6 wins (75.00% win rate), and +53.94%. This multi-year record proves that strategy efficacy is broadly distributed across varying market regimes rather than concentrated in a single fortunate market phase.
Recent period since 2024-06-01 versus full history
Focusing explicitly on recent market performance, the evaluation window from June 1, 2024, to September 26, 2026, offers a robust sample of recent strategy behavior. During this 27-month modern period, the strategy completed 26 trades, generating a cumulative uncompounded trade sum of +158.10%. These 26 recent trades represent over 31% of the total 83 trades executed across the entire 7.03-year historical dataset. The average return per trade during this recent sample stands at +6.08%, exceeding the full-history average trade return of +4.68%. This accelerated trade generation and elevated per-trade payoff indicate that market conditions for CAH since mid-2024 have aligned exceptionally well with the strategy's core entry filters. Rather than suffering from alpha decay or parameter degradation over time, the algorithm's signal performance has remained sharp, providing empirical validation that the decision rules retain strong predictive power in contemporary stock market environments.
Strengths and limitations
The primary structural strength of this strategy lies in its outstanding win rate (85.54%) combined with broad profit dispersion, as evidenced by the top 3 winning trades contributing less than 18% of total gross profits. Downside risk is strictly bounded, with maximum historical drawdown holding at 12.89%. Additionally, the long historical track record (7.03 years) and recent post-2024 performance (+158.10% across 26 trades) demonstrate durable structural robustness. However, clear limitations exist. With an average of only 11.81 trades per year and a median exit interval of 26.60 days, the strategy requires extreme operational patience. Capital may remain locked in single positions for weeks (average hold of 395.29 hours) or sit flat during prolonged inactive periods. Furthermore, because individual losing trades can reach -12.89% against an average winning trade of +4.68%, the model's profitability depends strictly on maintaining its high hit rate; any severe regime shift that significantly depresses win rate accuracy would impact overall strategy performance.
DevioLab analytical conclusion
With a DevioLab score of 77.75 and a ranking of #2 for CAH stock, this algorithmic trading strategy represents a highly disciplined, low-frequency swing model built on 15-minute price data. The quantitative evidence shows a robust system that achieves high precision (85.54% win rate) while maintaining controlled drawdowns (12.89%) and excellent profit distribution across 83 trades spanning more than seven years. The strategy avoids reliance on isolated outlier trades, generating stable positive returns across every single calendar year from 2019 to 2026. For quantitative deployment via automated trading agents or trading bots, the algorithm provides an attractive equity curve profile characterized by long holding stability and high signal reliability, provided the execution environment is tailored for low-frequency swing horizons rather than rapid intraday turnover.
Data scope and methodology
The analysis presented in this report is derived exclusively from historical backtested trade logs for asset symbol CAH across the period from September 16, 2019, to September 26, 2026 (7.03 total years). Strategy statistics evaluate completed trades triggered on 15-minute price charts. Cumulative profit totals represent the uncompounded sum of closed trade percentage returns. The recent evaluation window includes all trades with exit timestamps on or after June 1, 2024 UTC. Statistics do not incorporate live order execution variables such as slippage, broker commission structures, order routing delays, or margin borrowing costs. All performance metrics reflect historical backtested modeling and should be interpreted as quantitative research rather than a guarantee of future live execution returns.