Alphagbm Pnl Simulator

AlphaGBM P&L Simulator

Prerequisites

• API Key: Set env ALPHAGBM_API_KEY (format agbm_xxxx...).
• Base URL: Default https://alphagbm.zeabur.app. Override with env ALPHAGBM_BASE_URL.

What This Skill Does

Simulates profit and loss for any option position across multiple dimensions -- underlying price, implied volatility, and time to expiration. Produces P&L diagrams, breakeven analysis, and probability-weighted outcome distributions.

Four Core Strategies for Context

Simulation Capabilities

Supported Position Types

• Single leg (long call, long put, short call, short put)
• Two-leg spreads (vertical, calendar, diagonal)
• Three-leg combinations (butterflies, ratio spreads)
• Four-leg combinations (iron condors, iron butterflies, double diagonals)
• Arbitrary multi-leg custom positions

API Endpoint

P&L Simulator

POST /api/options/tools/simulate
Content-Type: application/json

{
  "symbol": "AAPL",
  "spot": 150.0,
  "legs": [
    {"action": "buy", "option_type": "call", "strike": 145, "expiry_days": 30, "iv": 0.26},
    {"action": "sell", "option_type": "call", "strike": 150, "expiry_days": 30, "iv": 0.25}
  ]
}

Parameters:

• symbol (required): Ticker symbol
• spot (required): Current underlying price
• legs (required): Array of option legs, each with:
  • action: "buy" or "sell"
  • option_type: "call" or "put"
  • strike: Strike price
  • expiry_days: Days to expiration
  • iv: Implied volatility as decimal (e.g., 0.26 for 26%)

How to Use

Input

• Required: Position definition (legs with strike, expiry, type, quantity, entry price)
• Optional: Scenario parameters (price range, IV shift, target date), number of Monte Carlo paths

Output Structure

{
  "ticker": "AAPL",
  "price": 218.45,
  "position": {
    "strategy": "Bull Call Spread",
    "legs": [
      {"action": "buy", "type": "call", "strike": 215, "expiry": "2026-04-18", "price": 7.20, "qty": 1},
      {"action": "sell", "type": "call", "strike": 225, "expiry": "2026-04-18", "price": 3.40, "qty": 1}
    ],
    "net_debit": 380
  },
  "pnl_at_expiry": {
    "price_axis": [195, 200, 205, 210, 215, 218.8, 220, 225, 230, 235],
    "pnl_axis":   [-380, -380, -380, -380, -380, 0, 120, 620, 620, 620]
  },
  "pnl_over_time": {
    "dates": ["2026-03-29", "2026-04-04", "2026-04-11", "2026-04-18"],
    "curves": {
      "at_210": [-180, -220, -290, -380],
      "at_218": [50, 30, 10, -20],
      "at_225": [320, 400, 510, 620]
    }
  },
  "breakevens": [218.80],
  "max_profit": 620,
  "max_loss": 380,
  "risk_reward_ratio": 1.63,
  "probability_of_profit": 0.56,
  "expected_value": 42.50,
  "scenarios": {
    "price_down_10pct": {"pnl": -380, "pnl_pct": -100},
    "price_up_10pct": {"pnl": 620, "pnl_pct": 163},
    "iv_crush_50pct": {"pnl": -85, "note": "IV drop hurts long spread slightly"},
    "iv_spike_50pct": {"pnl": 120, "note": "IV rise helps long spread slightly"}
  }
}

Example Queries

Mock Data

Demo tickers available without API key: AAPL, NVDA, SPY, TSLA, META. Simulations use realistic pricing models calibrated to mock-data/ snapshots.

Related Skills

• alphagbm-options-strategy -- Get strategy recommendations, then simulate them here
• alphagbm-greeks -- Understand the Greeks driving the P&L changes
• alphagbm-iv-rank -- Context for whether IV scenarios are realistic
• alphagbm-vol-surface -- Full IV landscape for calibrating simulations

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