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Stock instrument · execution via BinanceAMD · Advanced Micro Devices, Inc. Quantitative Strategy Analysis: Evaluating a High Profit Factor and Low Turnover Framework on 15-Minute Data
This quantitative research report evaluates the top-ranked algorithmic trading model for AMD (Advanced Micro Devices, Inc.) over a 6.94-year historical backtest dataset spanning September 2019 to August 2026. Achieving a DevioLab Score of 85.96 and securing the number one rank for this ticker, the strategy exhibits an exceptional profit factor of 6.25 combined with a 76.19% win rate across 105 completed trades. Despite utilizing a 15-minute chart execution interval, the model displays a medium-term position holding profile with an average holding duration of 368.99 hours (approximately 15.38 days). Risk control metrics show a constrained maximum historical drawdown of 19.79%, while gross profit distribution remains remarkably balanced, with the top three winning trades contributing just 17.89% of cumulative gross gains. Recent testing performance since June 1, 2024, accounts for 44 closed positions generating a combined trade gain sum of 304.82%, reinforcing the historical consistency observed across all individual calendar years from 2020 through 2026.
Analysis as of 25.08.2026. Strategy data is updated separately.Read full analysis
Strategy profile
The quantitative strategy under review, designated technical name AMDB 0 +57175.98% 1TRAD-UFH9, is configured for Advanced Micro Devices, Inc. (AMD) in the stock market context utilizing a 15-minute candle interval. Operating across a historical evaluation sample of 6.94 years from September 16, 2019, through August 25, 2026, the framework generated 105 total completed trades. Among these trades, 80 resulted in net positive gains while 25 closed as losses, yielding an overall historical win rate of 76.19%. The strategy achieved a DevioLab Score of 85.96, establishing it as the top-ranked quantitative model among all evaluated strategies for the AMD ticker in DevioLab strategy database. From an overarching performance perspective, the historical backtest recorded a cumulative closed trade percentage sum of 57,175.98%, translating to an annualized compounding-style metric of 1,657.79%. The profit factor, calculated as the ratio of aggregate gross profits to aggregate gross losses, stands at an exceptionally strong 6.25. This indicates that for every unit of capital surrendered during losing trades, the strategy historically recovered 6.25 units in gross profits. The model operates as a core independent selection strategy, exhibiting statistical characteristics that differentiate it substantially from high-frequency or rapid intraday turnover algorithms.
Trading rhythm and position duration
Although the strategy processes price information on a 15-minute timeframe, its operational rhythm is characterized by long holding times and low overall trade frequency. Over the 6.94-year test history, the strategy completed 105 trades, which equates to an average trade frequency of 15.13 trades per year or 1.69 trades per active month. The temporal spacing between trade exits averages 22.74 days, with a median exit interval of 17.03 days, confirming that position closures are periodic events rather than continuous daily occurrences. Position duration statistics further reinforce this swing to position trading classification. The average holding duration across all completed trades is 368.99 hours, equivalent to approximately 15.38 calendar days. The median holding duration is 216.00 hours, or exactly 9.00 days. The structural divergence between the short 15-minute chart resolution and multi-day holding times suggests that the algorithm leverages granular intraday price data to refine execution timing while capturing macro price trends. Traders analyzing this model should recognize that operating on a 15-minute execution grid does not automatically imply scalping behavior; in this case, position retention spans multiple weeks on average.
Quality of historical results
Evaluating trade return expectations reveals a highly favorable statistical distribution. The mean return across all 105 completed trades is +6.83%, while the median trade return is +5.84%. The close alignment between the mean and median metrics indicates a symmetrical payoff profile that is not artificially inflated by a solitary statistical anomaly. The best individual trade achieved a performance of +76.68%, whereas the worst individual trade recorded a loss of -13.07%, establishing a total trade dispersion range of nearly 90 percentage points. A key quantitative strength of this framework lies in the structure of its profit concentration. The top three winning trades collectively account for 17.89% of total gross profit. In quantitative research, a top-three winner contribution below 20% signifies a broad-based profit distribution, proving that total returns are driven by repeated operational success rather than heavy dependence on a few lucky momentum spikes. This structural distribution, combined with a 76.19% hit rate and a 6.25 profit factor, demonstrates that the strategy routinely captures meaningful upside moves while maintaining strict control over trade degradation.
Risk, drawdown and losing behavior
Risk characteristics of the strategy are defined by disciplined downside containment relative to cumulative return metrics. The maximum peak-to-trough drawdown recorded over the nearly seven-year backtest period was 19.79%. For an equity strategy operating in a growth technology ticker known for substantial structural volatility, keeping maximum drawdown below 20% represents a notable statistical risk boundary. Losing streak dynamics further highlight the historical resilience of the approach. The strategy experienced a maximum consecutive losing streak of 4 trades, compared to a maximum winning streak of 14 trades. Given that the worst single trade loss was limited to -13.07%, losing cycles were historically resolved without severe capital erosion. The combination of a high win rate (76.19%), limited losing streak duration, and a profit factor of 6.25 ensured that drawdown recovery periods remained historically manageable throughout various market regimes.
Behavior through time and yearly stability
An examination of calendar year performance metrics confirms that the strategy maintained profitability across every single backtested year from 2020 through 2026. In 2020, the model completed 11 trades with a 90.91% win rate, yielding a combined trade return sum of +202.41%. During the 2021 market cycle, trade count rose to 15 while win rate stood at 73.33%, generating a trade sum of +88.12%. Notably, during the broad semiconductor equity compression in 2022, the strategy maintained positive performance, recording 11 trades, a 63.64% win rate, and a net trade sum of +20.16%. Performance rebounded strongly in subsequent years. In 2023, 17 trades produced a 70.59% win rate and a +73.38% sum. In 2024, the strategy executed 17 trades with an 82.35% win rate, generating +86.84%. Performance in 2025 delivered 20 trades, a 65.00% win rate, and a +116.31% return sum, followed by 2026 performance through August registering 14 trades, a 92.86% win rate, and a +129.43% return sum. Annual trade volume remained highly consistent, fluctuating within a narrow band of 11 to 20 trades per year, reflecting a stable signal filter across macro cycles.
Recent period since 2024-06-01 versus full history
The sub-sample period beginning June 1, 2024, provides critical evidence regarding the recent viability of the strategy. Within this post-June 2024 window, the strategy completed 44 trades, generating a cumulative closed trade percentage sum of +304.82%. Comparing this to the overall dataset shows that 41.90% of total lifetime trades (44 out of 105) occurred in the final 2.25 years of the sample period, indicating an acceleration in trade signal generation relative to the 2020-2022 period. This increased recent activity coincided with strong cumulative profitability, demonstrating that the strategy remained highly responsive to price behavior in recent market environments. Unlike strategies that show decaying profitability in modern market conditions, this model captured an aggregate +304.82% across 44 recent trades, confirming that its statistical edge has remained intact through recent market cycles without requiring structural modifications.
Strengths and limitations
The primary analytical strengths of this quantitative model include its exceptional profit factor of 6.25, a robust historical win rate of 76.19%, and a tightly controlled maximum drawdown of 19.79%. Furthermore, gross profit generation is healthy and broad-based, as evidenced by the low 17.89% contribution from the top three winning trades. The strategy has demonstrated exceptional multi-year consistency, posting positive trade return sums across every single calendar year from 2020 through 2026, supported by strong recent performance since June 2024. Conversely, several statistical limitations must be considered. With only 105 completed trades across 6.94 years, the total sample size is relatively small, which increases the statistical variance around expected future performance metrics. Additionally, the average holding time of 368.99 hours (15.38 days) requires capital to remain committed to individual positions for extended durations, exposing open positions to overnight gap risk and earnings announcement volatility. Finally, these results represent simulated historical backtests and do not account for real-world execution friction, slippage, or borrowing costs.
DevioLab analytical conclusion
Securing the top rank for Advanced Micro Devices, Inc. (AMD) with a DevioLab Score of 85.96, strategy AMDB 0 +57175.98% 1TRAD-UFH9 demonstrates a highly effective balance between downside protection and trend capture. By utilizing 15-minute price data to enter medium-term holding positions averaging 15.38 days, the framework successfully filters out intraday noise while taking advantage of major multi-week directional trends in AMD stock. The overall historical metrics—highlighted by a 76.19% win rate, a 6.25 profit factor, a modest 19.79% maximum drawdown, and uniform profitability across all seven calendar years tested—reflect a robust quantitative architecture. Market participants reviewing this strategy should evaluate its low-frequency, medium-duration profile against their personal capital constraints and risk tolerance, remembering that historical simulated excellence serves as an analytical benchmark rather than a guarantee of future live performance.
Data scope and methodology
The statistical findings in this report were calculated from historical closed trade data recorded between September 16, 2019, and August 25, 2026. All trade metrics, including win rates, holding times, drawdowns, and yearly performance summaries, are based on closed position data calculated from 15-minute price candles for AMD stock. Recent period statistics reflect positions closed on or after June 1, 2024, UTC. Calculated percentage returns represent hypothetical backtested trade outputs and do not correspond to live account executions, net brokerage statements, or guaranteed future results. The backtest does not factor in broker commissions, execution slippage, interest rates, or cash dividends. This research document is published exclusively for quantitative strategy analysis and educational purposes by DevioLab.com and must not be construed as individualized investment advice.