alphagbm-fear-score

name	alphagbm-fear-score
description	Per-ticker panic index (0-100) that weights six real signals: VIX, IV Rank, RSI-14, options volume anomaly, Put/Call ratio, and consecutive-down days. Scores ≥ 60 trigger a Bull Put Spread entry signal. Based on the FearDesk methodology; tested at ~10.8% annualized ROC for BPS entries on signal vs ~3.5% unconditional. Triggers: "fear score QQQ", "is NVDA oversold", "panic index SPY", "BPS signal TSLA", "is it fear time", "BPS entry timing", "when to sell put", "is AAPL panic", "contrarian entry signal", "oversold reading", "VIX plus RSI"
globs	["mock-data/fear-score/**"]

AlphaGBM FearScore

A weighted composite panic gauge, per ticker. Reconstructs the FearDesk framework in one API call: six orthogonal fear signals, each scored 0–100, then combined with fixed weights into a single number. Score ≥ 60 is the historical trigger for Bull Put Spread entries.

Scoring Weights

Indicator	Weight	Source
VIX level	20%	Global fear floor (market-wide)
IV Rank	25%	Per-ticker option premium expensiveness
RSI-14	15%	Oversold intensity
Volume anomaly	15%	Options or stock volume spike vs 5-day avg
Put/Call ratio	15%	Bearish positioning skew
Consecutive down days	10%	Selloff persistence

Each indicator has its own 0–100 sub-score with thresholds tuned so extreme readings contribute most. Missing inputs fall back to neutral values (and are flagged in components.*.fallback), so the endpoint never 500s on partial data.

Why It Exists

Most fear gauges are either VIX-only (miss per-ticker divergence) or opaque ("sentiment index: 72"). This breaks down exactly what drove the score so you can decide whether to trust it.

Backtest evidence: Across 146 live Bull Put Spread trades, entries at FearScore ≥ 60 delivered ~10.8% annualized ROC vs ~3.5% for unconditional entries — roughly 3× the alpha from a single filter. Use this as the market-timing layer on any premium-selling strategy.

How to Use

Input: A ticker symbol.

Output:

• fear_score — weighted total 0-100
• signal — boolean, true when fear_score ≥ threshold (default 60)
• threshold — current trigger value
• confidence — 0-1, fraction of the 6 indicators that used real (non-fallback) data
• components.{vix,iv_rank,rsi,volume_anomaly,pc_ratio,consecutive_down}:
  • value — raw input
  • score — 0-100 per-indicator score
  • weight — contribution weight
  • fallback — true if neutral default was used

Example Queries:

• fear score QQQ — Full breakdown of the 6 indicators for QQQ
• is NVDA oversold right now — RSI + FearScore composite
• BPS signal SPY — Check if entry threshold is hit
• when should I sell put AAPL — Timing via FearScore ≥ 60 rule
• how panicked is TSLA today — Per-ticker panic index with component breakdown
• why is QQQ fear score low — Component-by-component explanation

Mock Data

Mock data in mock-data/fear-score/ — example responses at neutral / elevated / signal-triggered readings.

API Endpoint

GET /api/options/fear-score?ticker={SYMBOL}

Query params:

• ticker (required) — stock symbol (US / HK / CN supported if whitelisted)

Response shape:

{
  "success": true,
  "ticker": "QQQ",
  "fear_score": 68.2,
  "signal": true,
  "threshold": 60,
  "confidence": 1.0,
  "components": {
    "vix": {"value": 28.4, "score": 82, "weight": 0.20, "fallback": false},
    "iv_rank": {"value": 78, "score": 78, "weight": 0.25, "fallback": false},
    "rsi": {"value": 24.1, "score": 88, "weight": 0.15, "fallback": false},
    "volume_anomaly": {"value": 2.3, "score": 72, "weight": 0.15, "fallback": false},
    "pc_ratio": {"value": 1.6, "score": 80, "weight": 0.15, "fallback": false},
    "consecutive_down": {"value": 3, "score": 60, "weight": 0.10, "fallback": false}
  },
  "timestamp": "2026-04-24T08:00:00"
}

Pricing: 1 option-analysis credit per call; per-ticker 5-min cache (cache hits free).

Related Skills

Skill	Relevance
alphagbm-vix-status	Market-wide version of the VIX input
alphagbm-iv-rank	IV Rank (25% of the composite) standalone
alphagbm-options-strategy	BPS/Sell-Put strategies that should respect the ≥60 signal

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