AMZNBUSDT
Aktieninstrument · Ausführung über BinanceAMZN · Amazon.com, Inc. Quantitative Strategy Analysis: AMZNB 0 +4849.41% 1TRAD-AND4
This quantitative evaluation analyzes the historical backtest performance of the core algorithmic strategy AMZNB 0 +4849.41% 1TRAD-AND4 on AMZN · Amazon.com, Inc., evaluated across a 15-minute execution interval. Spanning nearly seven years from September 2019 to August 2026, the strategy achieved a cumulative historical gain of 4849.41 percentage points across 151 completed trades, corresponding to an annualized return of 234.70 percent. The strategy demonstrates an exceptionally high win rate of 82.78 percent alongside a profit factor of 1.67 and a maximum drawdown of 16.38 percent. Ranking first for the AMZN ticker with a DevioLab Score of 84.48, the system exhibits broad-based gross profit distribution, where the three largest winning trades account for only 13.69 percent of total gross profits. However, the performance profile presents notable analytical trade-offs, including asymmetric negative outlier risk where the worst trade of negative 16.38 percent closely matches the maximum strategy drawdown, as well as prolonged statistical dormancy marked by zero completed trades since June 1, 2024.
Vollständige Analyse lesen
Strategy profile
The core quantitative strategy designated as AMZNB 0 +4849.41% 1TRAD-AND4 operates on a 15-minute candle interval for AMZN · Amazon.com, Inc. within equity market structures. Over an evaluation window of approximately 6.93 years—starting on September 16, 2019, and concluding on August 21, 2026—the algorithm completed 151 historical trades. Across this multi-year evaluation, the strategy achieved a aggregate return of 4849.41 percent, translating to an annualized performance metric of 234.70 percent. Based on its underlying statistical profile, DevioLab assigns this model a DevioLab Score of 84.48, placing it at rank number one among tested quantitative strategies for the AMZN ticker. The dataset establishes a baseline of historical efficacy characterized by selective position taking, high trade accuracy, and robust aggregate net profit growth.
Trading rhythm and position duration
Although the algorithm evaluates price action on a short-term 15-minute timeframe, its overall execution frequency is highly selective rather than high-frequency. Over the 6.93-year statistical history, the total trade count of 151 yields an annualized trade frequency of 21.79 trades per year. This corresponds to an average exit cadence of approximately one completed position every two to three weeks. Specific holding duration metrics, such as average or median holding hours and days between exits, are not recorded in the primary dataset. Nevertheless, comparing the low annual trade volume against the granular 15-minute entry evaluation interval demonstrates that the strategy applies strict statistical thresholds, remaining flat during the vast majority of market sessions rather than engaging in continuous turnover.
Quality of historical results
The strategy's return profile is driven primarily by an exceptionally strong win rate rather than an expansive payoff ratio. Out of 151 total completed trades, 125 concluded as profitable realizations against 26 losing trades, yielding a win rate of 82.78 percent. The overall profit factor stands at 1.67, indicating that aggregate gross gains exceeded aggregate gross losses by 67 percent. The average return across all completed trades is positive 2.90 percent, while the median trade return is positive 2.34 percent. The close proximity between the average trade and median trade suggests a consistent core return distribution rather than a equity curve skewed by sporadic high-magnitude outliers. Furthermore, the top three winning trades generated 13.69 percent of the strategy's total gross profit, confirming that historical gains were broadly distributed across its 125 winning positions rather than concentrated in a brief cluster of extreme market moves.
Risk, drawdown and losing behavior
The strategy demonstrates tight consecutive loss management alongside localized loss magnitude risk. The maximum observed historical drawdown across the 6.93-year sample was 16.38 percent. Notably, this drawdown figure coincides almost exactly with the worst single trade in the dataset, which recorded a loss of negative 16.38 percent. This structural alignment suggests that peak-to-trough equity stress was heavily dictated by a single tail-risk trade event rather than prolonged structural compounding of multiple consecutive losses. This interpretation is reinforced by the strategy's streak metrics: the longest consecutive losing streak was restricted to just 2 trades, whereas the longest winning streak reached 20 consecutive trades. While the 82.78 percent accuracy rate and short losing streaks mitigate equity curve erosion, the magnitude of the single worst trade relative to the median profit of positive 2.34 percent illustrates an asymmetric payoff risk where single adverse exits require multiple standard winning trades to fully recover.
Behavior through time and yearly stability
The overall 6.93-year statistical sample reflects sustained compounding performance, generating 4849.41 percent in cumulative backtested gains. Because specific yearly breakdown tables are omitted from the available dataset, granular year-over-year comparative analysis regarding annual trade counts and annual win rate fluctuations cannot be directly computed. However, evaluated across its full multi-year lifespan, the strategy maintained an average execution pace of 21.79 trades annually. The long-term stability of the system relies on its ability to maintain high directional accuracy over extended market cycles, though the lack of discrete annual telemetry prevents verifying whether trade frequency and profit contributions were evenly distributed across individual calendar years or concentrated during specific volatility regimes.
Strengths and limitations
The primary strength of the strategy resides in its outstanding historical accuracy and structural profit distribution. An 82.78 percent win rate, a 20-trade winning streak, and a rank of number one for the AMZN ticker reflect high historical precision. Additionally, with the top three winning trades contributing only 13.69 percent of gross profit, the system does not depend on rare, unpredictable windfall events to achieve profitability. Conversely, the strategy exhibits major structural limitations. The primary limitation is payoff asymmetry: the worst single trade loss of negative 16.38 percent is roughly seven times larger than the median winning trade of positive 2.34 percent, creating severe exposure to single-event drawdowns. Furthermore, the absolute lack of trade activity since June 1, 2024 introduces empirical uncertainty regarding the system's operational frequency under recent market conditions, while missing granular annual and holding duration data limits detailed breakdown analysis.
DevioLab analytical conclusion
With a DevioLab Score of 84.48 and a first-place ranking for AMZN · Amazon.com, Inc., strategy AMZNB 0 +4849.41% 1TRAD-AND4 represents a high-accuracy quantitative model characterized by low execution frequency and robust total compounding over its multi-year test history. The statistical balance is defined by high probability execution (82.78 percent win rate) and broad profit dispersion offset by tail-risk payoff asymmetry, as evidenced by a single worst trade of negative 16.38 percent driving the strategy's peak historical drawdown. Quantitative analysts must weigh the historical top-tier ranking and 4849.41 percent overall gain against the complete absence of execution signals since mid-2024, which limits recent verification of the model's performance dynamics.
Data scope and methodology
This analysis is based strictly on backtested quantitative history generated for AMZN · Amazon.com, Inc. on a 15-minute timeframe covering September 16, 2019, through August 21, 2026. The dataset encompasses 151 completed trade cycles. All presented metrics—including win rates, drawdown percentages, profit factors, and trade frequencies—reflect historical simulated execution under fixed algorithmic parameters. The statistics do not incorporate live order execution variables, real-time slippage, order routing delays, borrow fees, or transaction costs. Historical simulation results are inherently non-predictive and do not guarantee future performance outcomes.