QQQ / SQQQ Dynamic Hedge Studio
Explore valuation-aware hedge ratios, margin impacts, and return quality for a combined short QQQ + short SQQQ overlay using BacktestJS with daily data.
Backtest Controls
Choose a training sample and evaluation window. The optimizer fits hedge ratios using the training range you specify, then applies them inside the backtest window.
Training Sample
Backtest Window
Financing & Carry
持仓设置
Training uses all observations before the start date. Borrow + dividend drag applied daily. BacktestJS powers the execution engine when available; a local fallback keeps results responsive offline.
Current Valuation Snapshot
Cumulative Return
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Annualized Return
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Sharpe Ratio
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Annualized Std Dev
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Max Drawdown
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Avg / Max Margin
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优化后的估值分段配置
SQQQ 固定为 1 单位，QQQ 单位数根据优化目标和持仓天数自动调整。配置会根据训练期数据优化以最大化选定的目标（Sharpe / 降低回撤 / 降低波动）。
💡 提示：持仓天数不同会产生不同的最优配置。天数越长，调整频率越低，配置会更保守。
Training Sample
Awaiting first optimization…
Testing Period 可视化
根据优化后的估值分段配置显示 Testing Period 的 QQQ 价格和 NDX PE 走势，不同颜色代表不同百分位区间
Training vs Testing 回测对比
对比训练期和测试期的表现，检查策略是否过拟合
| 指标 | Training Period | Testing Period |
|---|---|---|
| 时间区间 | — | — |
| 交易天数 | — | — |
| 策略累计收益 | — | — |
| 纯 Short SQQQ 累计收益 | — | — |
| 年化收益 | — | — |
| Sharpe Ratio | — | — |
| 年化波动率 | — | — |
| 最大回撤 | — | — |
| 平均保证金 | — | — |
| 最大保证金 | — | — |
| 胜率 | — | — |
| 盈亏比 | — | — |
Equity Curve
资金曲线，初始资金 $1.00。按设定的再平衡频率调整持仓。鼠标悬停查看估值百分位和保证金使用。
Borrow + dividends deducted pro-rata (per trading day).
BacktestJS results, local fallback if CDN unavailable.
Training Period Equity Curve
训练期资金曲线对比，检查策略在训练期的表现。
回撤对比
策略回撤 vs 纯做空 SQQQ 回撤。数值越低表示回撤越大。
优化过程分析 - 为什么选择这些 QQQ/SQQQ 比率？
展示每个 Percentile 区间的优化过程，帮助理解为什么算法选择特定的 QQQ/SQQQ 比率
Hedge Ratio Blueprint
Step function of the optimized QQQ vs SQQQ shorts per valuation percentile.
Margin Load Timeline
Indicates combined Reg-T style requirement for maintaining the paired shorts.
Exposure Timeline
持仓单位数时间线（SQQQ 固定 1 单位，QQQ 根据估值调整）
Valuation & Hedge Signal
Compares NDX PE percentile against the applied QQQ/SQQQ ratio.