CMS · CMS Energy Corporation
Stock Universe · marché actions mondialQuantitative Evaluation of CMS · CMS Algorithmic Strategy: High-Precision Positional Execution with Controlled Drawdown
This quantitative research study examines the historical performance of the algorithmic trading strategy CMS 0 +364.47% 1TRAD-KQO7 on the stock ticker CMS across a 7.06-year evaluation window from September 2019 to October 2026. Designed as decision logic for automated trading bots and position-oriented trading agents, the system operates on 15-minute candle intervals while maintaining multi-week position holdings. Over a total sample of 41 closed trades, the strategy achieved a aggregate return of +364.47% with a high historical win rate of 78.05% and a maximum recorded drawdown of 6.01%. This analysis explores the strategy statistical architecture, evaluating its low trade frequency, drawdown containment, profit concentration, and yearly consistency.
Analyse au 05.10.2026. Les données de la stratégie sont mises à jour séparément.Lire l’analyse complète
Strategy profile
The algorithmic trading model designated as CMS 0 +364.47% 1TRAD-KQO7 represents a specialized positional quantitative structure developed for the stock market asset CMS. Operating on a 15-minute timeframe, the strategy utilizes granular intraday price data to evaluate market structure, yet its operational model is distinctly long-term and selective. Over a historical evaluation span of approximately 7.06 years ranging from September 16, 2019, to October 5, 2026, the strategy generated a cumulative closed-trade profit sum of +364.47% across 41 completed transactions. Within the DevioLab quantitative evaluation framework, this system achieves a score of 79.66, establishing it as the rank 2 performing strategy for the CMS ticker. Rather than engaging in hyper-active intraday churning, the strategy functions as an automated decision engine engineered to capture multi-week trend movements. Its underlying mechanics make it suitable for execution via automated trading bots and algorithmic trading agents that require disciplined exit criteria, low transactional frequency, and strict exposure controls in equity trading environments.
Trading rhythm and position duration
A defining characteristic of this strategy is the contrast between its 15-minute candle resolution and its extended holding duration. Despite sampling price action every 15 minutes, the system averages just 5.81 closed trades per year, which translates to approximately 1.11 trades per active month. Across the 41 completed trades in its history, the average holding period reaches 922.29 hours, equivalent to roughly 38.4 days, while the median holding duration stands at 501.75 hours, or approximately 20.9 days. This right-skewed distribution indicates that while baseline trades frequently resolve within three weeks, high-conviction winning positions are permitted to run for extended periods exceeding a month. The temporal spacing between trade exits further highlights this deliberate pace, averaging 59.58 days between exits with a median interval of 48.20 days. Consequently, the strategy operates as a patient trend-following model. Automated trading agents utilizing this logic remain in cash or holding positions for extended periods, avoiding market noise and micro-structure whipsaws while using intraday resolution solely for entry and exit precision.
Quality of historical results
Evaluating the structural quality of the historical results reveals a high-win-rate strategy with balanced payoff mechanics. Out of 41 closed trades, 32 ended in profit while 9 resulted in losses, yielding a win rate of 78.05%. The historical average trade return sits at +4.15%, closely matching the median trade return of +3.87%. This narrow delta between average and median returns demonstrates that performance is steady and reproducible across trade cycles rather than being skewed by a few extreme leverage spikes or temporary market anomalies. The best single trade achieved a gain of +19.12%, whereas the worst trade logged a moderate loss of -5.77%. Furthermore, the top three winning trades combined account for 22.82% of total gross profit. This relatively low concentration ratio confirms that overall profitability is broadly distributed across the 32 winning events rather than dependent on isolated black-swan surges. However, the profit factor registers at 1.25. In the context of a 78.05% win rate, a profit factor of 1.25 indicates that the average loss, while bounded at a maximum of -5.77%, is larger relative to the average gain, meaning the strategy relies on its elevated hit rate to maintain positive equity progression.
Risk, drawdown and losing behavior
Risk containment represents one of the strategy strongest statistical attributes. Over more than seven years of historical backtesting on CMS, the maximum recorded peak-to-trough drawdown was restricted to 6.01%. For an equity strategy delivering +364.47% in closed-trade sum, maintaining drawdown near 6% indicates exceptional capital preservation. This resilience is reinforced by trade sequence statistics: the strategy longest winning streak reached 13 consecutive profitable trades, whereas its longest losing streak was capped at just 2 consecutive losing trades. The worst individual trade across the entire dataset was -5.77%, demonstrating that downside risk per trade event is strictly contained. By preventing deep capital impairment and avoiding extended cluster losses, the strategy avoids the catastrophic drawdowns that frequently destabilize automated trading robots during adverse market regimes. The combination of a 78.05% win rate, brief losing streaks, and bounded trade risk creates an equity curve characterized by low volatility and stable capital growth.
Behavior through time and yearly stability
An examination of the yearly breakdown demonstrates notable multi-year consistency across varying equity market environments. In 2020, the strategy completed 7 trades with a 57.14% win rate, generating a net sum of +12.06%. In 2021, trade frequency compressed to 3 trades, all of which were profitable (100% win rate), producing +19.98%. The year 2022 saw 5 trades, again maintaining a 100% win rate to deliver +33.12%. Activity picked up in 2023 with 8 trades, achieving a 75.00% win rate and +19.52% net return. Performance accelerated further in 2024, logging 8 trades with a 75.00% win rate and an annual trade sum of +40.63%. In 2025, 5 trades yielded an 80.00% win rate and +17.69%, followed by 2026 which recorded 5 trades, an 80.00% win rate, and +27.01%. Notably, the strategy registered positive aggregate returns in every single calendar year from 2020 through 2026. Trade frequency remained remarkably stable within a tight envelope of 3 to 8 trades per year, confirming that the underlying decision logic maintains consistent selectivity across differing macroeconomic cycles.
Recent period since 2024-06-01 versus full history
To evaluate whether the strategy historical edge remains intact in recent market conditions, closed trades ending on or after June 1, 2024, were analyzed as a separate sub-sample. During this recent window, the strategy completed 13 trades, generating a cumulative return sum of +65.16%. These 13 recent trades represent roughly 31.7% of the total lifetime trade count (41 trades) and contribute +65.16% to the overall +364.47% lifetime profit sum. The annualized return profile in recent months continues to align with the historical baseline, showing no evidence of decay or structural breakage. The steady cadence of trades since mid-2024 demonstrates that the 15-minute positional model continues to identify viable structural opportunities in CMS stock without requiring adjustments to its core parameters or exposure rules.
Strengths and limitations
The primary strength of this quantitative strategy lies in its combination of a high win rate (78.05%), minimal maximum drawdown (6.01%), and exceptional multi-year stability across seven consecutive profitable years. Its profit distribution is well balanced, with the top three winning trades representing only 22.82% of gross profits, ensuring that performance is not reliant on singular unrepeatable outliers. Furthermore, short losing streaks capped at 2 trades minimize emotional and mathematical recovery hurdles for automated trading agents. Conversely, significant limitations exist within the statistical sample. With only 41 completed trades over 7.06 years, the total sample size is small, which expands the statistical margin of error and confidence intervals around expected future outcomes. Additionally, the profit factor of 1.25 reflects an asymmetric payoff profile where average losses absorb a noticeable portion of cumulative gross gains. Finally, the median holding time of 501.75 hours requires high capital patience, making the strategy unsuitable for traders seeking high-frequency execution or rapid turnover.
DevioLab analytical conclusion
The DevioLab score of 79.66 and rank 2 positioning for CMS reflect a highly refined, low-frequency positional strategy that prioritizes downside protection and consistency over hyperactive trading. By combining 15-minute timeframe execution with multi-week trend holding, the system successfully extracts directional profit while keeping maximum drawdown capped at 6.01%. The historical empirical data shows uninterrupted annual profitability from 2020 through 2026 and robust recent performance since June 2024. For quantitative developers and traders seeking logic for automated trading bots, this strategy offers a robust blueprint for conservative equity positioning. However, deployment models should account for the low trade count of 5.81 trades per year and the moderate profit factor of 1.25 by combining this system within a broader diversified multi-asset algorithmic portfolio.
Data scope and methodology
This analysis is derived entirely from historical backtested closed-trade performance statistics generated for the algorithmic trading strategy CMS 0 +364.47% 1TRAD-KQO7 on the stock ticker CMS across 15-minute price intervals. The sample covers the period from September 16, 2019, through October 5, 2026. All cited metrics, including cumulative profit sums, win rates, drawdown levels, holding times, and yearly breakdowns, represent exact historical simulated outcomes based on closed positions. They do not account for live order execution slippage, broker fees, interest costs, or liquidity constraints, nor do they constitute financial advice or guarantees of future investment performance.