Install
$ agentstack add skill-alphagbm-skills-alphagbm-pnl-simulator ✓ 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 P&L Simulator
Prerequisites
- API Key: Set env
ALPHAGBM_API_KEY(formatagbm_xxxx...). - Base URL: Default
https://alphagbm.zeabur.app. Override with envALPHAGBM_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.
- 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.