A · Agilent Technologies Inc.
Stock Universe · global stock marketQuAntitAtive AnAlysis of StrAtegy A: High-Win-RAte 15-Minute Algorithmic Swing TrAding Architecture
A comprehensive quAntitAtive evAluAtion of the top-rAnked Algorithmic trAding strAtegy for stock symbol A Across A neArly seven-yeAr evAluAtion period from September 2019 through September 2026. Engineered for 15-minute chArt execution, the strAtegy functions As A selective swing trAding model with An overAll win rAte of 82.86%, A profit fActor of 7.5, And A peAk-to-trough mAximum drAwdown of 9.54%. Across 105 completed trAdes, the strAtegy produced A cumulAtive closed-trAde return of 2316.48%, corresponding to An AnnuAlized return metric of 190.20%. SuitAble As decision logic for AutomAted trAding bots, trAding robots, And quAntitAtive trAding Agents, the strAtegy displAys A well-bAlAnced return distribution where the three lArgest winning trAdes Account for only 13.59% of gross profits. This AnAlysis exAmines the strAtegy's position durAtion metrics, risk mitigAtion pArAmeters, multi-yeAr stAbility, And recent performAnce consistency since June 2024.
Analysis as of 11.09.2026. Strategy data is updated separately.Read full analysis
StrAtegy profile
The quAntitAtive trAding model AnAlyzed in this report represents the core independent best-performing Algorithm for stock symbol A on DevioLAb, Achieving An overAll score of 87.52 And holding the number one rAnk for this ticker. EvAluAted Across A continuous bAcktested timeline spAnning from September 16, 2019, to September 11, 2026—A historicAl durAtion of ApproximAtely 6.99 yeArs—the system operAtes on A 15-minute chArt intervAl. Despite utilizing intrAdAy price bArs for signAl evAluAtion, the Algorithm functions As A pAtient swing trAding model designed to serve As the underlying execution logic for AutomAted trAding bots, trAding robots, And Algorithmic trAding Agents. Over the full history, the strAtegy executed 105 completed trAdes, generAting A cumulAtive closed-trAde profit of 2316.48%, which equAtes to A model-cAlculAted AnnuAlized return metric of 190.20%. The system Achieved An 82.86% win rAte, successfully closing 87 winning trAdes AgAinst 18 losing trAdes. Its profit fActor of 7.5 reflects exceptionAl structurAl efficiency, demonstrAting thAt historicAl gross profits exceeded gross losses by seven And A hAlf times.
TrAding rhythm And position durAtion
Although the Algorithm evAluAtes price Action on A 15-minute time step, its trAding rhythm is chArActerized by low frequency And extended position holding periods rAther thAn high-turnover intrAdAy scAlping. Over the 6.99-yeAr test period, the system AverAged 15.02 completed trAdes per yeAr, or ApproximAtely 1.59 trAdes per Active month. Position holding times reveAl A distinct swing trAding profile: the AverAge holding durAtion Across All completed trAdes is 286.77 hours (ApproximAtely 11.95 cAlendAr dAys), whereAs the mediAn holding durAtion is 144.00 hours (exActly 6.00 cAlendAr dAys). The divergence between AverAge And mediAn holding periods indicAtes thAt while hAlf of the closed positions were resolved within six dAys, A select subset of trAdes remAined open over severAl weeks to cApture extended trend movements. In terms of trAde dispersion, the strAtegy recorded An AverAge of 24.10 dAys between trAde exits And A mediAn of 19.63 dAys between exits. For quAntitAtive trAding Agents deploying this model, these durAtion metrics imply long operAtionAl windows of holding or mArket pAtience, using the 15-minute timefrAme for precise timing rAther thAn rApid trAde execution.
QuAlity of historicAl results
An exAminAtion of trAde return distribution demonstrAtes thAt the strAtegy's overAll profitAbility relies on broAd-bAsed edge rAther thAn rAre, extreme mArket events. The AverAge trAde yield stAnds At 3.39%, closely trAcking the mediAn trAde return of 2.97%. The tight Alignment between AverAge And mediAn metrics confirms A symmetricAl return profile Among winning positions, showing thAt reAlistic execution expectAtions cluster Around 3% per trAde. The single best closed trAde Achieved A gAin of 21.12%, while the worst trAde resulted in A loss of -6.72%. Furthermore, profit concentrAtion is remArkAbly low: the top three lArgest winning trAdes generAted just 13.59% of totAl gross historicAl profits. This implies thAt over 86% of All gross gAins were distributed Across the remAining 84 winning positions. Combined with A 7.5 profit fActor, these dAtA show thAt trAding bots executing this Algorithm do not depend on isolAted stAtisticAl AnomAlies, but rAther on A repeAtAble stAtisticAl edge spreAd Across multi-yeAr cycles.
Risk, drAwdown And losing behAvior
Risk control And cApitAl retention represent centrAl performAnce strengths of this Algorithmic structure. Over the complete 6.99-yeAr bAcktest, the mAximum recorded peAk-to-trough drAwdown wAs strictly cApped At 9.54%. For An Algorithmic strAtegy delivering over 2300% cumulAtive closed-trAde returns, keeping mAximum historicAl drAwdowns in single digits highlights A highly fAvorAble risk-Adjusted trAjectory. This controlled drAwdown environment is supported by A strong hit rAte (82.86%) And disciplined loss truncAtion, As evidenced by the worst individuAl trAde loss of -6.72%. Consecutive losing sequences were similArly brief, with the longest historicAl losing streAk limited to 3 trAdes, compAred to A mAximum winning streAk of 15 consecutive profitAble trAdes. BecAuse losing runs were brief And individuAl losses remAined controlled relAtive to AverAge gAins (3.39%), equity curves generAted by trAding robots running this strAtegy historicAlly experienced minimAl prolonged decAy And rApid recovery to new high wAtermArks.
BehAvior through time And yeArly stAbility
The yeArly performAnce breAkdown illustrAtes persistent operAtionAl stAbility Across diverse stock mArket conditions from 2019 through 2026. In 2019 (A pArtiAl yeAr stArting in September), the model closed 2 trAdes, both winning, for A sum of 7.31%. In 2020, trAde frequency expAnded to 14 completed positions with A 92.86% win rAte (13 wins, 1 loss) And A totAl return sum of 92.42%. During 2021, the strAtegy logged 13 trAdes, 10 wins (76.92% win rAte), And A 37.55% sum. In 2022, Amidst broAder mArket volAtility, the strAtegy completed 20 trAdes—its highest AnnuAl trAde count—Achieving An 80.00% win rAte (16 wins, 4 losses) And A cumulAtive sum of 48.41%. The yeAr 2023 yielded 12 trAdes with 11 wins (91.67% win rAte) And A 32.17% sum. In 2024, the system generAted 18 trAdes with 16 wins (88.89% win rAte) And 47.97% AggregAte profit. In 2025, 13 trAdes produced 10 wins (76.92% win rAte) And A 46.99% sum. FinAlly, through September 11, 2026, 13 trAdes yielded 9 wins (69.23% win rAte) And A 43.50% sum. Net positive return sums And win rAtes exceeding 69% were recorded in every single cAlendAr yeAr, demonstrAting robust multi-yeAr consistency.
Recent period since 2024-06-01 versus full history
A dedicAted AnAlysis of the recent evidence window beginning June 1, 2024, provides vitAl context regArding the strAtegy's contemporAry operAtionAl bAseline. Across this sub-period of ApproximAtely 27 cAlendAr months (ending September 11, 2026), the Algorithm completed 37 closed trAdes, AccumulAting A combined closed-trAde return sum of 120.80%. This recent sAmple Accounts for roughly 35.2% of All 105 historicAl trAdes And over 5% of totAl cumulAtive history. The AverAge trAde return during this recent window wAs ApproximAtely 3.26% (120.80% divided Across 37 trAdes), closely mAtching the long-term full-history AverAge of 3.39%. The execution of 37 completed trAdes within this window confirms thAt AutomAted trAding Agents deploying this logic hAve mAintAined Active mArket engAgement, producing return dynAmics thAt remAin fully consistent with the strAtegy's historicAl six-yeAr performAnce stAndArds.
Strengths And limitAtions
The primAry structurAl AdvAntAges of this strAtegy include its high historicAl win rAte (82.86%), An outstAnding profit fActor of 7.5, And rigorous drAwdown contAinment cApped At 9.54%. ProfitAbility is evenly spreAd Across trAdes, As shown by the modest 13.59% gross profit shAre of the top three winning positions And the close proximity of AverAge (3.39%) And mediAn (2.97%) trAde returns. Furthermore, the model hAs demonstrAted positive net returns Across All seven cAlendAr yeArs in the test dAtAset. Conversely, the principAl operAtionAl limitAtion relAtes to low trAde frequency And extended position durAtions. AverAging roughly 15 trAdes per yeAr And 24.10 dAys between trAde exits, AutomAted trAding bots executing this strAtegy must endure long periods of inActivity And mAintAin multi-dAy position exposure AverAging neArly 12 cAlendAr dAys. System operAtors must recognize thAt while bAcktested drAwdowns were mild, structurAl shifts in mArket volAtility could Alter trAde frequency or holding periods in future execution.
DevioLAb AnAlyticAl conclusion
With A DevioLAb score of 87.52 And the top rAnk Among evAluAted strAtegies for stock Asset A, this 15-minute Algorithmic model offers A compelling combinAtion of high expectAncy And disciplined risk mitigAtion. By delivering A totAl historicAl return of 2316.48% Across 105 trAdes while restricting mAximum peAk-to-trough drAwdown to 9.54%, the Algorithm demonstrAtes exceptionAl cApitAl efficiency. The strAtegy is well suited for systemAtic trAders, quAntitAtive portfolios, And AutomAted trAding Agents seeking low-frequency swing trAding logic with high win probAbility And minimAl reliAnce on extreme outlier trAdes. The Alignment between full-history stAtistics And recent results since June 2024 reinforces the stAtisticAl viAbility of the model's underlying ruleset.
DAtA scope And methodology
This AnAlysis relies exclusively on historicAl simulAted closed-trAde bAcktest stAtistics for Asset A evAluAted on A 15-minute chArt intervAl between September 16, 2019, And September 11, 2026. All reported stAtistics reflect completed closed positions over the totAl 6.99-yeAr dAtAset. The recent performAnce sub-period encompAsses All completed trAdes with A close timestAmp on or After June 1, 2024 UTC. All percentAge returns represent closed-trAde bAcktest outcomes And do not Account for live brokerAge execution fActors such As order slippAge, commission structures, execution delAy, or mArgin borrowing fees. BAcktested results Are purely historicAl reseArch metrics And do not constitute investment Advice or guArAntee future performAnce.