Alphagbm Bps Backtest

AlphaGBM BPS Backtest

Backtests the Bull Put Spread (short put + long put at lower strike) as a mechanical strategy over 2018–present on any ticker, with two passes per call:

1. With Signal — only enters when the per-ticker FearScore is ≥ your threshold
2. No Signal (Control) — enters unconditionally every Monday

The side-by-side comparison shows whether the signal is doing work, or whether you're paying 1 credit for noise.

Parameters

All optional except ticker:

What's Returned

Per pass (with_signal and no_signal):

• total_trades, win_rate_pct, annual_return_pct, sharpe, max_drawdown_pct, roc_pct, avg_holding_days, avg_pnl_per_trade, total_pnl, final_capital
• exit_reasons — count by take_profit / stop_loss / expiry_otm / expiry_itm / close_early
• trades[] — full ledger (entry/exit date, strikes, credit, pnl, reason)
• equity_curve[] — per-day cumulative capital
• pnl_histogram — bucket counts for the P&L distribution

Plus:

• summary — one-paragraph zh/en takeaway comparing signal vs control, with ⚠️ flags when drawdown or win rate look problematic

Methodology Notes

• IV is proxied by 20-day historical volatility (HV20) for BS pricing. Historical option-chain IV is unaffordable to source at scale; HV20 is a reasonable proxy but will under-estimate IV around events. Live results typically outperform backtest because of this.
• FearScore is reconstructed from the same 6 indicators the live version uses, but computed from cheap historical price + volume data only.
• Entries filtered by max_positions (3) and min_entry_spacing_days (3) and a risk_per_trade cap (0.5% of capital).

How to Use

Example Queries:

• backtest BPS on QQQ — Default params, signal vs control comparison
• does FearScore work on SPY — Same call, reads the comparison summary
• backtest bull put spread IWM DTE 21 delta 0.30 — Custom params
• what DTE works best for BPS on QQQ — Run a few with different DTEs, compare
• bps fear threshold 70 vs 60 on NVDA — Run two calls with different thresholds

Mock Data

Mock data in mock-data/bps-backtest/ — examples for QQQ with signal ON and OFF.

API Endpoint

POST /api/options/bps-backtest
Content-Type: application/json

Request body:

{
  "ticker": "QQQ",
  "dte_target": 14,
  "short_delta": 0.25,
  "spread_width": 5.0,
  "take_profit_pct": 0.50,
  "fear_threshold": 60,
  "start_date": "2018-01-01",
  "end_date": "2026-04-20",
  "include_control": true
}

Response:

{
  "success": true,
  "ticker": "QQQ",
  "period": {"start": "2018-01-01", "end": "2026-04-20"},
  "with_signal": {
    "total_trades": 28, "win_rate_pct": 100, "annual_return_pct": 10.8,
    "sharpe": 16.3, "max_drawdown_pct": 0.0, "trades": [...], "equity_curve": [...],
    "pnl_histogram": {...}, "exit_reasons": {"take_profit": 20, "expiry_otm": 8}
  },
  "no_signal": {
    "total_trades": 185, "win_rate_pct": 82, "annual_return_pct": 3.5,
    "sharpe": 2.1, "max_drawdown_pct": -8.2, ...
  },
  "summary": {
    "zh": "QQQ · 2018-2026 · 使用 FearScore ≥ 60 触发 BPS 入场，共交易 28 笔，年化 +10.8%，胜率 100%，最大回撤 0.0%。 同参数无信号对照组年化 +3.5%、胜率 82%；信号版本高出无信号组 7.3 个百分点。",
    "en": "QQQ · 2018-2026 · BPS entry on FearScore ≥ 60 over 28 trades: annualized +10.8%, win rate 100%, max drawdown 0.0%. The no-signal control under the same params: annualized +3.5%, win rate 82%. Signal version outperforms by 7.3 pp."
  }
}

Pricing: 1 option-analysis credit per call; 30-min cache per parameter hash (cache hits free). Expect ~5-10s compute for a fresh hash.

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