analyzing-market-sentiment

# Analyzing Market Sentiment

## Overview

Cryptocurrency market sentiment analysis combining Fear & Greed Index, news keyword analysis, and price/volume momentum into a composite 0-100 score.

## Prerequisites

1. **Python 3.8+** installed
2. **Dependencies**: `pip install requests`
3. Internet connectivity for API access (Alternative.me, CoinGecko)
4. Optional: `crypto-news-aggregator` skill for enhanced news analysis

## Instructions

1. **Assess user intent** - determine what analysis is needed:
   - Overall market: no specific coin, general sentiment
   - Coin-specific: extract symbol (BTC, ETH, etc.)
   - Quick vs detailed: quick score or full component breakdown

2. **Run sentiment analysis** with appropriate options:
   ```bash
   # Quick market sentiment check
   python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py

   # Coin-specific sentiment
   python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --coin BTC

   # Detailed breakdown with all components
   python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --detailed

   # Custom time period
   python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --period 7d --detailed
   ```

3. **Export results** for trading models or analysis:
   ```bash
   python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --format json --output sentiment.json
   ```

4. **Present results** to the user:
   - Show composite score and classification prominently
   - Explain what the sentiment reading means
   - Highlight extreme readings (potential contrarian signals)
   - For detailed mode, show component breakdown with weights

## Output

Composite sentiment score (0-100) with classification and weighted component breakdown. Extreme readings serve as contrarian indicators:

```
==============================================================================
  MARKET SENTIMENT ANALYZER                         Updated: 2026-01-14 15:30  # 2026 - current year timestamp
==============================================================================

  COMPOSITE SENTIMENT
------------------------------------------------------------------------------
  Score: 65.5 / 100                         Classification: GREED

  Component Breakdown:
  - Fear & Greed Index:  72.0  (weight: 40%)  -> 28.8 pts
  - News Sentiment:      58.5  (weight: 40%)  -> 23.4 pts
  - Market Momentum:     66.5  (weight: 20%)  -> 13.3 pts

  Interpretation: Market is moderately greedy. Consider taking profits or
  reducing position sizes. Watch for reversal signals.

==============================================================================
```

## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Fear & Greed unavailable | API down | Uses cached value with warning |
| News fetch failed | Network issue | Reduces weight of news component |
| Invalid coin | Unknown symbol | Proceeds with market-wide analysis |

See `${CLAUDE_SKILL_DIR}/references/errors.md` for comprehensive error handling.

## Examples

Sentiment analysis patterns from quick checks to custom-weighted deep analysis:

```bash
# Quick market sentiment
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py

# Bitcoin-specific sentiment
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --coin BTC

# Detailed analysis with component breakdown
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --detailed

# Custom weights emphasizing news
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --weights "news:0.5,fng:0.3,momentum:0.2"

# Weekly sentiment trend
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --period 7d --detailed
```

## Resources

- `${CLAUDE_SKILL_DIR}/references/implementation.md` - CLI options, classifications, JSON format, contrarian theory
- `${CLAUDE_SKILL_DIR}/references/errors.md` - Comprehensive error handling
- `${CLAUDE_SKILL_DIR}/references/examples.md` - Detailed usage examples
- Alternative.me Fear & Greed: https://alternative.me/crypto/fear-and-greed-index/
- CoinGecko API: https://www.coingecko.com/en/api
- `${CLAUDE_SKILL_DIR}/config/settings.yaml` - Configuration options