alphagbm-bps-backtest

name	alphagbm-bps-backtest
description	Full walk-forward Bull Put Spread backtest over ~8 years of daily history. Runs both the signal (FearScore ≥ 60 entry) version AND a no-signal control in the same request, so you can quantify whether the fear-entry rule actually delivers alpha for this ticker under your parameters. Returns equity curve, 4 KPIs (annualized return / win rate / max drawdown / Sharpe), trade ledger, and a plain-language takeaway. Triggers: "backtest BPS on QQQ", "bull put spread backtest", "does FearScore work on SPY", "what DTE for BPS", "optimal bull put spread delta", "BPS strategy backtest", "credit spread backtest", "backtest short put spread"
globs	["mock-data/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:

Param	Default	Range	Meaning
ticker	required	US / HK / CN	Underlying
dte_target	14	7–45	Days to expiry on entry
short_delta	0.25	0.15–0.35	Absolute delta of the short put leg
spread_width	5.0	2–10	Dollar width of the spread
take_profit_pct	0.50	0.20–0.80	Close when realized % of max profit hits this
fear_threshold	60	40–80	FearScore ≥ X is entry signal
start_date	2018-01-01	YYYY-MM-DD	Backtest start
end_date	2026-04-20	YYYY-MM-DD	Backtest end
include_control	true	bool	Run no-signal control pass alongside

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": {...}     
  
   
         
        ...
  
   
     
     
  

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

Related Skills

Skill	Relevance
alphagbm-fear-score	The live version of the entry signal being backtested
alphagbm-options-strategy	Build a custom BPS after deciding params
alphagbm-pnl-simulator	Forward-simulate a specific BPS at various future prices

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