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股票工具 · 通过 Binance 执行Quantitative Analysis of SMCI · Super Micro Computer, Inc. Strategy SMCIB 0 +361925.90% 1TRAD-TWT6
This analytical study evaluates the historical quantitative performance of the algorithmic strategy SMCIB 0 +361925.90% 1TRAD-TWT6 applied to Super Micro Computer, Inc. (SMCI) on a 15-minute timeframe execution model. Covering a 6.5-year historical backtest window from February 2020 through August 2026, the strategy achieved a DevioLab score of 81.62, ranking 2nd overall for the SMCI asset universe. Characterized by an unusually low trade frequency relative to its 15-minute sampling interval, the system completed 69 trades, delivering a high historical win rate of 86.96% and a profit factor of 5.56. While the strategy demonstrates exceptional statistical metrics, including an average trade return of +15.53% and a peak winning streak of 24 consecutive trades, its profit distribution exhibits notable structural skew. The top three winning trades account for 36.06% of total gross profits, driven in part by a single +228.17% gain recorded in 2022. Furthermore, historical trade activity accelerated significantly post-June 2024, with 41 of the 69 total lifetime trades executing in this recent window. This paper provides a rigorous statistical decomposition of the strategy's position duration, profit concentration, drawdown mechanics, and temporal stability.
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Strategy profile
The algorithmic trading strategy SMCIB 0 +361925.90% 1TRAD-TWT6 operates on Super Micro Computer, Inc. (SMCI) utilizing a 15-minute price evaluation interval. Evaluated over a comprehensive 6.5-year historical testing horizon spanning from February 10, 2020, to August 12, 2026, the strategy recorded 69 fully completed round-trip trades. It earned a DevioLab performance score of 81.62, placing it at rank 2 among all evaluated algorithmic models for this specific equity ticker. Across the full historical sample, the system generated a cumulative closed-trade gain sum of 361,925.90%, driven by 60 winning exits against only 9 losing exits. This produces an overall historical win rate of 86.96% and a robust profit factor of 5.56. Although the strategy samples market data on a 15-minute interval, its operational structure reflects a highly selective trend-following or position-holding mechanism rather than a high-frequency trading approach. The system generates an average of 10.61 trades per year, or approximately 1.73 trades per active month. This sparse trade footprint indicates that the underlying parameters filter out the vast majority of short-term intraday noise, seeking instead to capture larger directional moves in SMCI while maintaining high trade selective precision.
Trading rhythm and position duration
A critical observation in the strategy's profile is the substantial divergence between its 15-minute data sampling frequency and its realized holding periods. Across all 69 completed trades, the average holding duration stands at 595.70 hours, equivalent to approximately 24.8 calendar days. However, the median holding duration is substantially lower at 168.50 hours, or roughly 7 calendar days. This wide gap between the mean and median position durations reveals a right-skewed holding distribution. While the typical trade remains open for about one week, a subset of positions is held for multiple weeks or months to ride macro trends. The temporal pacing between trade exits further reinforces this non-intraday behavior. The average time elapsed between consecutive trade exits is 22.96 days, while the median spacing between exits is 16.98 days. Rather than engaging in frequent scalping or day trading, the strategy utilizes the 15-minute timeframe primarily for timing entries and exits within a swing-to-position trading framework. Consequently, positions routinely remain open through overnight gaps and multi-week market cycles, exposing the system to broader asset volatility while minimizing portfolio turnover.
Quality of historical results
The quality of historical returns generated by the strategy is defined by a strong baseline hit rate coupled with positive payoff skewness. The average trade yield across the 69 completed positions is +15.53%, whereas the median trade yield is +10.00%. The positive distance between the mean and median indicates that performance is bolstered by oversized winning trades. The strategy recorded a maximum individual winning trade of +228.17%, compared to a maximum single loss of -21.98%. A key metric evaluating return concentration is the gross profit distribution: the three largest winning trades generated 36.06% of the strategy's total historical gross profit. This concentration highlights that while the strategy maintains an impressive 86.96% hit rate, a significant portion of its total cumulative gain is tied to capturing large, sustained upside moves in SMCI. The profit factor of 5.56 reflects a highly favorable ratio of cumulative gains to cumulative losses. Nevertheless, potential users must recognize that historical total returns rely on allowing top-performing positions to compound fully rather than relying solely on uniform, small profit target executions.
Risk, drawdown and losing behavior
The strategy's historical risk profile exhibits remarkable discipline, though it carries structural risks inherent to concentrated holding durations. The maximum drawdown recorded across the entire 6.5-year backtest was -21.98%. Notably, this peak historical drawdown matches the exact percentage of the worst individual trade (-21.98%), indicating that the strategy's maximum equity decline occurred during a single adverse trade exit rather than through a series of compounded multi-trade losses. The system's losing behavior is further characterized by brief and shallow losing streaks. The longest consecutive losing streak observed throughout the historical dataset was just 2 trades. In contrast, the strategy achieved a peak consecutive winning streak of 24 trades. With only 9 total losses occurring across 69 trades, equity declines were historically rare and quickly isolated. However, because individual positions are held for an average of 595.70 hours, holding equity through multi-week drawdowns before exit triggers are hit remains the primary operational risk of this strategy model.
Behavior through time and yearly stability
An examination of the strategy's yearly performance breakdown demonstrates a pronounced evolution in trading activity and profit generation over time. During the initial period from February 2020 through 2021, no closed trade exits were logged. In 2022, the strategy executed just 1 trade, but that single trade resulted in a +228.17% gain, marking the single best trade in the strategy's history. In 2023, trade frequency increased to 15 completed trades, achieving a perfect 100.00% win rate (15 wins, 0 losses) and a combined trade return sum of +339.67%. In 2024, activity expanded further to 22 completed trades, yielding 18 wins and 4 losses for an 81.82% win rate and a cumulative trade sum of +195.81%. The strategy maintained this heightened pacing into 2025 with 19 trades (16 wins, 3 losses, 84.21% win rate, +153.04% sum) and through the partial year of 2026 with 12 trades (10 wins, 2 losses, 83.33% win rate, +155.14% sum). This yearly progression shows that while early historical gains relied on rare, explosive single trades, the strategy's recent years shifted toward higher trade density while maintaining win rates consistently above 80%.
Recent period since 2024-06-01 versus full history
A focused analysis of the sample period beginning June 1, 2024, reveals a distinct acceleration in trade execution relative to the strategy's historical baseline. Of the 69 total completed trades recorded over the 6.5-year lifetime, 41 trades were closed on or after June 1, 2024. This means that nearly 60% of all historical trade exits occurred within the final two years of the test window. During this recent sub-period, the strategy accumulated a combined trade return sum of +387.43%. Comparing this recent pacing against the full history underscores a structural shift in activity: while the full history averaged 10.61 trades per year, the trade frequency since mid-2024 exceeded 20 trades per year. Despite the increased execution rate, the strategy's win rate remained highly stable, operating in the 81% to 84% range across 2024, 2025, and 2026. The recent evidence sample is statistically robust, confirming that the strategy's edge remained intact during higher volatility regimes in SMCI without suffering performance degradation or drawdown expansion.
Strengths and limitations
The primary strength of the SMCIB 0 +361925.90% 1TRAD-TWT6 strategy lies in its exceptional historical hit rate (86.96%) and profit factor (5.56), supported by an extraordinary 24-trade winning streak and a modest peak drawdown of -21.98%. Its ability to capture macro trend movements while operating on a 15-minute sampling grid allows it to filter out daily noise effectively. However, several analytical limitations must be highlighted. First, the total historical sample size consists of only 69 completed trades over 6.5 years, which represents a relatively small sample for statistical validation on an intraday interval. Second, profit concentration is notable: the top 3 trades generated 36.06% of gross profits, meaning overall performance is heavily dependent on capturing rare tail events. Third, the long holding times (averaging nearly 25 days) expose traders to prolonged market exposure, overnight gap risks, and corporate earnings events. Finally, the shift in trade frequency post-2024 indicates that market regimes significantly influence trade generation rates.
DevioLab analytical conclusion
With a DevioLab score of 81.62 and a overall rank of #2 for SMCI, this strategy demonstrates a historically potent quantitative profile for managing Super Micro Computer, Inc. price action. The empirical evidence reveals a system that successfully bridges intraday timing with macro trend holding. Its historical risk metrics are exceptionally tightly bounded, featuring a max drawdown identical to its single worst trade (-21.98%) and a maximum losing streak of only 2 trades. Quant analysts evaluating this model should weigh its exceptional profit factor (5.56) and strong recent performance (+387.43% across 41 trades since June 2024) against its concentration risks and low lifetime trade count (69 total trades). The strategy is best categorized as a high-precision, low-turnover trend capture system rather than a high-frequency operational model.
Data scope and methodology
All metrics, returns, drawdowns, trade frequencies, and holding durations presented in this analysis are derived strictly from backtested historical simulations of closed trades for asset SMCI across the evaluation window from February 10, 2020, to August 12, 2026. Cumulative percentage figures represent the direct sum of individual historical closed trade yields and do not account for dynamic capital compounding, slippage, brokerage commissions, margin costs, or order execution delays. Recent performance metrics evaluated since June 1, 2024, include only trades whose sell timestamps occurred on or after that date. Historical simulated results are presented strictly for quantitative research purposes and do not constitute financial advice or guarantees of future trading performance.