Alphagbm Hedge Advisor

AlphaGBM Hedge Advisor

"I own AAPL at $140 and it's now $180 — how do I protect the gains?"

Takes that question literally. Given a ticker + cost basis + position purpose, the skill classifies the holding into one of four scenarios and returns ready-to-trade hedge specs with strikes and costs already resolved from the live option chain.

Scenarios

What's Returned

For each recommendation spec, the skill resolves actual strikes and prices from the live option chain:

• Long Put: strike, DTE, cost_per_share, cost_per_contract, cost_pct_of_spot, delta, IV
• Collar: long_put_strike, short_call_strike, put_cost, call_credit, net_cost_per_share (negative = you receive a credit), breakeven analysis
• Tier-down / Position rules: static rules copy only

Also returns a position_rules[] array (single-name ≤20%, sector ≤30-35%, cash reserve 10-15%, etc.) for the normal-hold case.

How to Use

Input:

• ticker (required)
• cost_basis (required, float — your average entry price)
• purpose (optional, default long_term) — one of long_term / short_term / pre_earnings / just_bought

Output:

• Scenario label + reason (zh/en)
• Current price, cost basis, unrealized P&L %, recent drawdown %
• recommendations[] — each with type, priority, title, rationale, and resolved block containing the actual priced hedge
• position_rules[] — always-applicable sizing rules

Example Queries:

• hedge my AAPL at $140, now it's $180 → Gain Protection → Collar 95/110 quote
• I just bought NVDA at $110 on the dip, should I hedge? → Falling Knife or Bottom Fishing → Long Put 5% OTM 60-90 DTE
• how to protect my TSLA position → Gain Protection or Bottom Fishing based on PnL
• collar MSFT at cost 340 current 410 → Full collar pricing

Mock Data

Mock responses in mock-data/hedge-advisor/ — sample across all four scenarios.

API Endpoint

GET /api/options/hedge-advisor?ticker={SYMBOL}&cost_basis={PRICE}&purpose={PURPOSE}

Query params:

• ticker (required)
• cost_basis (required, float > 0)
• purpose (default long_term) — one of long_term / short_term / pre_earnings / just_bought

Response shape:

{
  "success": true,
  "ticker": "AAPL",
  "current_price": 180.0,
  "cost_basis": 140.0,
  "unrealized_pnl_pct": 28.57,
  "recent_drawdown_pct": 3.1,
  "purpose": "long_term",
  "scenario": {
    "scenario": "gain_protection",
    "label_zh": "浮盈怕坐电梯",
    "label_en": "Gain Protection",
    "reason_zh": "已浮盈 28.6%，需要保护已实现收益。",
    "reason_en": "Up 28.6% on cost — protect unrealized gains.",
    "unrealized_pnl_pct": 28.57
  },
  "recommendations": [
    {
      "type": "collar",
      "priority": 1,
      "title_zh": "Collar 95/110 锁定收益",
      "title_en": "Collar 95/110 lock-in",
      "rationale_zh": "...",
      "rationale_en": "...",
      "resolved": {
        "long_put_strike": 170.0,
        "short_call_strike": 200.0,
        "put_cost": 2.15,
        "call_credit": 2.45,
        "net_cost_per_share": -0.30,
        "net_cost_per_contract": -30,
        "is_credit": true,
        "dte": 62
      }
    },
    {"type": "tier_down", "priority": 2, ...}
  ],
  "position_rules": [
    {"rule_zh": "单票仓位 ≤ 20%", "rule_en": "Single ticker ≤20%", ...},
    ...
  ]
}

Pricing: 1 option-analysis credit per call; 5-min cache per (ticker, cost_basis, purpose).

Related Skills

Powered by AlphaGBM — Real-data options & research intelligence. 10K+ users.