Analyzing Market Sentiment

Overview

This skill provides comprehensive cryptocurrency market sentiment analysis by combining multiple data sources:

Fear & Greed Index: Market-wide sentiment from Alternative.me
News Sentiment: Keyword-based analysis of recent crypto news
Market Momentum: Price and volume trends from CoinGecko

Key Capabilities:

Composite sentiment score (0-100) with classification
Coin-specific sentiment analysis
Detailed breakdown of sentiment components
Multiple output formats (table, JSON, CSV)

Prerequisites

Before using this skill, ensure:

Python 3.8+ is installed
requests library is available: pip install requests
Internet connectivity for API access (Alternative.me, CoinGecko)
Optional: crypto-news-aggregator skill for enhanced news analysis

Instructions

Step 1: Assess User Intent

Determine what sentiment analysis the user needs:

Overall market: No specific coin, general sentiment
Coin-specific: Extract coin symbol (BTC, ETH, etc.)
Quick vs detailed: Quick score or full breakdown

Step 2: Execute Sentiment Analysis

Run the sentiment analyzer with appropriate options:

# Quick sentiment check (default)
python {baseDir}/scripts/sentiment_analyzer.py

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

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

# Export to JSON
python {baseDir}/scripts/sentiment_analyzer.py --format json --output sentiment.json

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

Step 3: Present Results

Format and present the sentiment analysis:

Show composite score and classification
Explain what the sentiment means
Highlight any extreme readings
For detailed mode, show component breakdown

Command-Line Options

Option	Description	Default
`--coin`	Analyze specific coin (BTC, ETH, etc.)	All market
`--period`	Time period (1h, 4h, 24h, 7d)	24h
`--detailed`	Show full component breakdown	false
`--format`	Output format (table, json, csv)	table
`--output`	Output file path	stdout
`--weights`	Custom weights (e.g., "news:0.5,fng:0.3,momentum:0.2")	Default
`--verbose`	Enable verbose output	false

Sentiment Classifications

Score Range	Classification	Description
0-20	Extreme Fear	Market panic, potential bottom
21-40	Fear	Cautious sentiment, bearish
41-60	Neutral	Balanced, no strong bias
61-80	Greed	Optimistic, bullish sentiment
81-100	Extreme Greed	Euphoria, potential top

Output

Table Format (Default)

==============================================================================
  MARKET SENTIMENT ANALYZER                         Updated: 2026-01-14 15:30
==============================================================================

  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.

==============================================================================

JSON Format

{
  "composite_score": 65.5,
  "classification": "Greed",
  "components": {
    "fear_greed": {
      "score": 72,
      "classification": "Greed",
      "weight": 0.40,
      "contribution": 28.8
    },
    "news_sentiment": {
      "score": 58.5,
      "articles_analyzed": 25,
      "positive": 12,
      "negative": 5,
      "neutral": 8,
      "weight": 0.40,
      "contribution": 23.4
    },
    "market_momentum": {
      "score": 66.5,
      "btc_change_24h": 3.5,
      "weight": 0.20,
      "contribution": 13.3
    }
  },
  "meta": {
    "timestamp": "2026-01-14T15:30:00Z",
    "period": "24h"
  }
}

Error Handling

See {baseDir}/references/errors.md for comprehensive 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

Examples

See {baseDir}/references/examples.md for detailed examples.

Quick Examples

# Quick market sentiment check
python {baseDir}/scripts/sentiment_analyzer.py

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

# Detailed analysis
python {baseDir}/scripts/sentiment_analyzer.py --detailed

# Export for trading model
python {baseDir}/scripts/sentiment_analyzer.py --format json --output sentiment.json

# Custom weights (emphasize news)
python {baseDir}/scripts/sentiment_analyzer.py --weights "news:0.5,fng:0.3,momentum:0.2"

# Weekly sentiment comparison
python {baseDir}/scripts/sentiment_analyzer.py --period 7d --detailed

Resources

Alternative.me Fear & Greed Index: https://alternative.me/crypto/fear-and-greed-index/
CoinGecko API: https://www.coingecko.com/en/api
Sentiment Analysis Theory: Contrarian indicator - extreme readings often precede reversals
See {baseDir}/config/settings.yaml for configuration options

analyzing-market-sentiment