Agent Skills › AlphaGBM/skills › alphagbm-pnl-simulator

alphagbm-pnl-simulator

GitHub

AlphaGBM期权P&L模拟引擎，支持单腿至多腿复杂策略的收益损失分析。提供到期盈亏图、时间演变、IV/价格情景测试、蒙特卡洛概率分布及盈亏平衡点计算，用于交易压力测试与风险可视化。

skills/alphagbm-pnl-simulator/SKILL.md AlphaGBM/skills

Trigger Scenarios

模拟特定期权组合的损益情况生成到期或随时间变化的盈亏图表执行价格或隐含波动率的情景假设分析计算策略的盈亏平衡点对持仓进行压力测试查看蒙特卡洛模拟的概率分布

Install

npx skills add AlphaGBM/skills --skill alphagbm-pnl-simulator -g -y

More Options

Use without installing

npx skills use AlphaGBM/skills@alphagbm-pnl-simulator

指定 Agent (Claude Code)

npx skills add AlphaGBM/skills --skill alphagbm-pnl-simulator -a claude-code -g -y

安装 repo 全部 skill

npx skills add AlphaGBM/skills --all -g -y

预览 repo 内 skill

npx skills add AlphaGBM/skills --list

SKILL.md

Frontmatter

{
    "name": "alphagbm-pnl-simulator",
    "globs": [
        "mock-data\/*.json"
    ],
    "description": "P&L simulation engine for any single-leg or multi-leg option position. Generates profit\/loss diagrams at expiry, P&L over time, what-if scenarios (price, IV, time), breakeven analysis, and probability distributions. Use when: testing a trade idea, visualizing risk\/reward, running what-if scenarios, checking breakeven points, stress-testing a position. Triggers on: \"simulate PnL for AAPL bull call spread\", \"what if NVDA drops 10%\", \"P&L diagram\", \"test my iron condor\", \"breakeven analysis\", \"stress test my position\", \"what happens at expiry\".\n"
}

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

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