Alphagbm Options Strategy

AlphaGBM Options Strategy

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

Given a market view and a ticker, recommends the best multi-leg option strategies ranked by risk/reward profile. Selects optimal strikes and expirations automatically using AlphaGBM's scoring engine.

Four Core Strategies and Trend Alignment

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

Trend alignment scoring: The scoring model rewards contracts that match the prevailing trend. For Sell Put, a downtrend scores 100 (counter-intuitive: you want to sell puts into weakness for higher premium), while an uptrend scores 30. For Buy Call, bullish momentum is weighted at 25%.

Supported Strategy Templates (15+)

| Category | Strategies | |----------|-----------| | Bullish | Bull Call Spread, Bull Put Spread, Long Call, Covered Call, Synthetic Long | | Bearish | Bear Put Spread, Bear Call Spread, Long Put, Synthetic Short | | Neutral | Iron Condor, Iron Butterfly, Short Straddle, Short Strangle, Calendar Spread | | Volatile | Long Straddle, Long Strangle, Butterfly Spread, Reverse Iron Condor | | Income | Covered Call, Cash-Secured Put, Collar, Jade Lizard |

Risk-Return Profiles

| Style | Typical Win Rate | Typical Return | |-------|-----------------|----------------| | steadyincome | 65-80% | 1-5%/month | | balanced | 40-55% | 50-200% | | highriskhighreward | 20-40% | 2-10x | | hedge | 30-50% | 0-1x |

Strategy Selection Logic

1. Match user's market view to candidate strategies
2. Filter by IV environment (high IV favors selling premium; low IV favors buying)
3. Score each candidate using risk/reward, probability of profit, and capital efficiency
4. Rank and return the top 3 recommendations with full details

API Endpoints

Strategy Templates

List all available strategy templates:

GET /api/options/tools/strategy/templates

Strategy Builder

Build a strategy from a template with specific parameters:

POST /api/options/tools/strategy/build
Content-Type: application/json

{
  "mode": "template",
  "template_id": "bull_call_spread",
  "spot": 150.0,
  "expiry_days": 30,
  "strikes": [140, 145, 150, 155, 160]
}

Options Scanner

Scan across tickers for strategies matching your criteria:

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

{
  "strategies": ["covered_call", "cash_secured_put"],
  "tickers": ["AAPL", "NVDA"],
  "min_yield_pct": 1.0
}

How to Use

Input

• Required: Ticker symbol + market view (bullish / bearish / neutral / volatile)
• Optional: Max capital, target expiration, risk tolerance (conservative / moderate / aggressive)

Output Structure

{
  "ticker": "AAPL",
  "price": 218.45,
  "market_view": "bullish",
  "iv_environment": "moderate",
  "recommendations": [
    {
      "strategy": "Bull Call Spread",
      "rank": 1,
      "score": 8.5,
      "legs": [
        {"action": "buy", "type": "call", "strike": 215, "expiry": "2026-04-18", "price": 7.20},
        {"action": "sell", "type": "call", "strike": 225, "expiry": "2026-04-18", "price": 3.40}
      ],
      "max_profit": 620,
      "max_loss": 380,
      "breakeven": [218.80],
      "probability_of_profit": 0.58,
      "risk_reward_ratio": 1.63,
      "net_debit": 380,
      "greeks": {
        "delta": 0.32,
        "gamma": 0.012,
        "theta": -0.08,
        "vega": 0.14
      },
      "rationale": "Moderate bullish exposure with capped risk. IV is fair -- debit spread preferred over naked call."
    }
  ]
}

Example Queries

| User Says | What Happens | |-----------|-------------| | "Options strategy for AAPL" | Infers view from stock analysis, returns top 3 strategies | | "Bullish strategy NVDA" | Filters to bullish strategies, ranks by score | | "Best play on TSLA earnings" | Selects volatile strategies (straddle, strangle) for event | | "Iron condor SPY" | Builds an iron condor with optimal strikes and returns full profile | | "Income strategy GOOGL" | Filters to covered call, cash-secured put, collar | | "Conservative bearish play on META" | Bear put spread or collar with tight risk parameters |

Mock Data

Demo tickers available without API key: AAPL, NVDA, SPY, TSLA, META. Strategy recommendations use realistic chain data from mock-data/.

Related Skills

• alphagbm-options-score -- Scores the individual contracts used in each leg
• alphagbm-pnl-simulator -- Simulate P&L over time for any recommended strategy
• alphagbm-greeks -- Deep-dive into position Greeks for the chosen strategy
• alphagbm-iv-rank -- Check if IV environment favors buying or selling premium

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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.