alphagbm-options-strategy
GitHub根据市场观点推荐最佳多腿期权策略,支持15+模板,自动选择行权价和到期日。提供P&L、盈亏平衡点及胜率,适用于选策略、财报交易规划及多空中性策略对比。
Trigger Scenarios
Install
npx skills add AlphaGBM/skills --skill alphagbm-options-strategy -g -y
SKILL.md
Frontmatter
{
"name": "alphagbm-options-strategy",
"globs": [
"mock-data\/*.json"
],
"description": "Recommends optimal multi-leg option strategies based on your market view (bullish, bearish, neutral, volatile). Supports 15+ strategy templates including spreads, condors, straddles, and income plays. Returns full P&L profile, breakevens, and probability of profit. Use when: choosing an options strategy, planning a trade around earnings, building a multi-leg position, comparing strategy alternatives. Triggers on: \"options strategy for AAPL\", \"bullish strategy NVDA\", \"what's the best play on TSLA earnings\", \"iron condor SPY\", \"bear put spread META\", \"income strategy for GOOGL\", \"neutral play on QQQ\".\n"
}
AlphaGBM Options Strategy
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
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 |
|---|---|---|
| steady_income | 65-80% | 1-5%/month |
| balanced | 40-55% | 50-200% |
| high_risk_high_reward | 20-40% | 2-10x |
| hedge | 30-50% | 0-1x |
Strategy Selection Logic
- Match user's market view to candidate strategies
- Filter by IV environment (high IV favors selling premium; low IV favors buying)
- Score each candidate using risk/reward, probability of profit, and capital efficiency
- 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
Powered by AlphaGBM -- Real-data options & research intelligence for traders and AI agents. 10K+ users.
Version History
- c69fa1b Current 2026-07-05 20:18


