Install
$ agentstack add skill-alphagbm-skills-alphagbm-bps-backtest ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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:
- With Signal — only enters when the per-ticker FearScore is ≥ your threshold
- 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 bytake_profit / stop_loss / expiry_otm / expiry_itm / close_earlytrades[]— full ledger (entry/exit date, strikes, credit, pnl, reason)equity_curve[]— per-day cumulative capitalpnl_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) andmin_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 comparisondoes FearScore work on SPY— Same call, reads the comparison summarybacktest bull put spread IWM DTE 21 delta 0.30— Custom paramswhat DTE works best for BPS on QQQ— Run a few with different DTEs, comparebps 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.
Related Skills
| Skill | Relevance | |-------|-----------| | [alphagbm-fear-score](../alphagbm-fear-score/) | The live version of the entry signal being backtested | | [alphagbm-options-strategy](../alphagbm-options-strategy/) | Build a custom BPS after deciding params | | [alphagbm-pnl-simulator](../alphagbm-pnl-simulator/) | Forward-simulate a specific BPS at various future prices |
Powered by AlphaGBM — Real-data options & research intelligence. 10K+ users.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: AlphaGBM
- Source: AlphaGBM/skills
- License: MIT
- Homepage: https://www.alphagbm.com/skills
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.