# Alphagbm Bps Backtest

> |

- **Type:** Skill
- **Install:** `agentstack add skill-alphagbm-skills-alphagbm-bps-backtest`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [AlphaGBM](https://agentstack.voostack.com/s/alphagbm)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [AlphaGBM](https://github.com/AlphaGBM)
- **Source:** https://github.com/AlphaGBM/skills/tree/main/skills/alphagbm-bps-backtest
- **Website:** https://www.alphagbm.com/skills

## Install

```sh
agentstack add skill-alphagbm-skills-alphagbm-bps-backtest
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## 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:

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:

```json
{
  "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:

```json
{
  "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](https://alphagbm.com) — 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](https://github.com/AlphaGBM)
- **Source:** [AlphaGBM/skills](https://github.com/AlphaGBM/skills)
- **License:** MIT
- **Homepage:** https://www.alphagbm.com/skills

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-alphagbm-skills-alphagbm-bps-backtest
- Seller: https://agentstack.voostack.com/s/alphagbm
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.