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Alphagbm Pnl Simulator

核心功能:支持单腿、多腿期权仓位的到期盈亏模拟、随时间盈亏变化分析,可进行价格、隐含波动率、时间维度的假设场景测试,提供盈亏平衡分析、蒙特卡罗概率分布计算。典型场景:测试期权交易策略、可视化风险收益、压力测试仓位、验证盈亏平衡点。输入为期权仓位参数及可选场景设定,输出包含盈亏曲线、关键风险指标、场景结果的结构化JSON数据。

clementgu
clementgu
热度 16.47
最近更新 2026-07-23 14:14:53
分类:数据依赖:第三方 API / 读写文件应用场景:财务 / 数据处理 / 市场分析 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add alphagbm-pnl-simulator
Metadata
name
alphagbm-pnl-simulator
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".
globs
["mock-data/*.json"]

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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