EMR · Emerson Electric Co.
Stock Universe · marché actions mondialAlgorithmic Analysis of EMR · Emerson Electric Co. Core Strategy Yielding +1474.89% Total Historical Return
This quantitative research report evaluates the top-ranked algorithmic trading strategy for EMR (Emerson Electric Co.) on DevioLab. Over a 7.03-year simulated test window from September 2019 to September 2026, the strategy recorded 46 completed trades, achieving an 84.78% win rate, a profit factor of 8.75, and a peak historical return of +1474.89%. Position durations reflect extended multi-week holding times despite using a 15-minute intraday execution interval. With every individual calendar year demonstrating positive cumulative returns and a modest peak drawdown of 15.42%, this strategy serves as a balanced benchmark for automated trading bots, trading robots, and quantitative trading agents seeking selective equity exposure.
Analyse au 24.10.2026. Les données de la stratégie sont mises à jour séparément.Lire l’analyse complète
Strategy profile
The EMR core strategy ranks first among all evaluated decision models for Emerson Electric Co. stock on the DevioLab platform, earning a composite quantitative score of 84.76. Built upon a 15-minute price bar interval, the algorithm is designed as decision logic suitable for execution by automated trading bots, trading robots, and algorithmic trading agents. Across a historical testing period spanning 7.03 years between September 16, 2019, and September 25, 2026, the strategy generated 46 completed trades, accumulating a total closed return of +1474.89% and an annualized equivalent yield of +236.44%. The selection logic for this model reflects a balanced core configuration optimized to maintain high expectancy per trade while mitigating overall equity curve volatility.
Trading rhythm and position duration
Despite relying on 15-minute candle data for entry and exit signals, the statistical profile reveals an exceptionally patient trading rhythm rather than high-frequency execution. Over the entire dataset, the strategy executed an average of 6.55 trades per year, or approximately 1.35 trades per active month. The timing between closed positions is substantial, with an average of 53.11 days between exits and a median interval of 28.23 days. Position holding times reflect multi-week exposure, averaging 1031.73 hours (approximately 43 days) per completed trade, alongside a median duration of 391.63 hours (around 16.3 days). This structure confirms that automated trading agents utilizing this logic do not trade continuously; instead, positions remain open across extended trends, drastically reducing trade turnover and signal noise.
Quality of historical results
The payoff statistics demonstrate strong performance across both frequency and magnitude. Out of 46 closed trade events, 39 resulted in gains, yielding an 84.78% win rate. The strategy achieved a profit factor of 8.75, meaning gross historical gains exceeded gross losses by nearly ninefold. Individual trade outcomes show an average return of +6.62% compared to a median trade return of +5.55%, indicating that performance is not skewed by isolated statistical anomalies. The single best trade achieved a gain of +37.36%, while the top three winning positions collectively accounted for 23.91% of total gross profits. This moderate winner concentration illustrates that historical profitability was broadly distributed across many successful trades rather than reliant on a single lucky trade.
Risk, drawdown and losing behavior
Risk containment within the EMR strategy is characterized by rare, controlled drawdowns and brief losing sequences. The maximum simulated drawdown observed across the entire 7.03-year backtest stood at 15.42%, matching the magnitude of the strategy's worst single trade loss (-15.42%). The longest losing streak over the sample period was limited to just 2 consecutive trades, whereas the longest winning streak extended to 12 consecutive profitable exits. The strong symmetry between the maximum drawdown percentage and the worst single trade loss indicates that capital depletion was predominantly driven by individual trade excursions rather than compounding sequences of multiple losing positions.
Behavior through time and yearly stability
Examining annual performance metrics demonstrates consistent historical profitability across every calendar year represented in the dataset. In 2020, the strategy completed 7 trades with an 85.71% win rate, yielding +88.05%. In 2021, 2 trades delivered a 100% win rate and +28.50% cumulative gain. In 2022, 4 trades achieved 100% win rate and +18.21%. In 2023, 4 trades produced 3 wins and 1 loss (75.00% win rate) for +22.47%. In 2024, 3 trades yielded 100% win rate and +27.85%. In 2025, trade frequency increased to 8 trades (62.50% win rate) for +25.93%. In 2026, 18 trades were completed with an 88.89% win rate, summing to +93.52%. Across seven distinct annual cycles, no year finished with a net loss, underscoring structural stability across varying equity market conditions.
Recent period since 2024-06-01 versus full history
Evaluating closed trade data since June 1, 2024, reveals a distinct concentration of trading activity relative to earlier historical years. Of the 46 total completed trades in the entire dataset, 27 closed after June 1, 2024. This recent window generated a cumulative sum of +126.97% in trade returns. The increased exit count in recent years highlights that market volatility or trend conditions in EMR met the strategy's trigger criteria far more frequently in 2025 and 2026 than during the 2021-2024 period. Importantly, the recent window maintained high efficacy, confirming that the logic retained positive expectancy during recent asset price regimes.
Strengths and limitations
The principal analytical strengths of this strategy include its exceptional win rate (84.78%), high profit factor (8.75), unbroken record of positive annual returns, and low gross profit concentration in its top winners (23.91%). Furthermore, its maximum drawdown of 15.42% reflects disciplined capital protection. Conversely, the main limitation stems from sample size constraints: 46 completed trades over 7.03 years represent a low statistical sample count, meaning individual trade outcomes exert a measurable impact on cumulative metrics. Additionally, the strategy requires automated trading bots and position managers to maintain open positions across multi-week holding durations, which may introduce capital lockup considerations for active portfolio allocation.
DevioLab analytical conclusion
With a DevioLab quantitative score of 84.76 and a first-place rank for EMR stock, this core strategy provides a robust template for algorithmic trading agents requiring long-horizon position trades on 15-minute intraday signals. Its combination of infrequent exits, high win rate, resilient drawdown profile, and multi-year positive annual continuity establishes it as a highly balanced model within equity trading research. Investors and automated bot developers should weigh the strategy's low trade frequency and extended position durations against its demonstrated historical efficiency.
Data scope and methodology
All statistics presented in this report derive from historical simulated backtest calculations for EMR stock on a 15-minute chart interval between September 16, 2019, and September 25, 2026. Metrics are based strictly on completed trade events whose sell timestamps fall within the historical window. The analysis assumes hypothetical executions without accounting for live brokerage commissions, margin rates, slippage, order routing delays, or corporate action adjustments. Historical backtest results do not guarantee future returns, and this research is provided solely for quantitative study and algorithmic development purposes.