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SKILL verified MIT Self-run

Alphagbm Pnl Simulator

skill-alphagbm-skills-alphagbm-pnl-simulator · by AlphaGBM

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Install

$ agentstack add skill-alphagbm-skills-alphagbm-pnl-simulator

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No 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.

View the full security report →

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Reliability & compatibility

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1mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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 →
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About

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

| Strategy | Ideal Trend | Max Profit | Max Loss | |----------|------------|------------|----------| | Sell Put | Neutral / Bullish | Premium received | Strike - Premium | | Sell Call | Neutral / Bearish | Premium received | Unlimited (uncovered) | | Buy Call | Bullish | Unlimited | Premium paid | | Buy Put | Bearish | Strike - Premium | Premium paid |

Simulation Capabilities

| Capability | Description | |-----------|-------------| | P&L at Expiry | Classic payoff diagram -- profit/loss vs. underlying price at expiration | | P&L Over Time | How the position's value evolves from now to expiry (time-series curves) | | What-If: Price | Vary underlying price by fixed amount or percentage -- see impact on P&L | | What-If: IV | Vary implied volatility -- see how IV crush or spike affects the position | | What-If: Time | Fast-forward to a specific date -- see theta decay impact | | Probability Distribution | Monte Carlo simulation of outcomes with probability of profit | | Breakeven Analysis | Exact breakeven points with time-varying breakevens before expiry |

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

| User Says | What Happens | |-----------|-------------| | "Simulate PnL for AAPL bull call spread" | Full P&L diagram at expiry + over time | | "What if NVDA drops 10%?" | Price scenario analysis for current position | | "P&L diagram" | Expiry payoff chart for any defined position | | "Test my iron condor" | Full simulation with breakevens, max P&L, probability of profit | | "Breakeven analysis for my spread" | Exact breakeven points + time-varying breakevens | | "Stress test: what if IV doubles?" | IV shock scenario with P&L impact | | "Monte Carlo for my straddle" | 10,000-path simulation with outcome distribution |

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

Powered by AlphaGBM -- Real-data options & research intelligence for traders and AI agents. 10K+ users.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

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

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.