Investment Advisor

A Reddit-based sentiment analysis tool for stock investment recommendations.

Overview

This tool collects stock mentions from Reddit, analyzes sentiment, and provides BUY/SELL/HOLD recommendations based on community sentiment.

Features

• Data Collection: Scrapes stock mentions from Reddit (r/WallStreetBets)
• Sentiment Analysis: Analyzes sentiment of mentions using keyword-based scoring
• Investment Recommendations: Provides BUY/SELL/HOLD advice based on sentiment thresholds
• CLI Tools: Easy-to-use command line interfaces for data collection and analysis

Quick Start

1. Install Dependencies

pip3 install -r requirements.txt

2. Configure Reddit API

1. Go to https://www.reddit.com/prefs/apps
2. Create a new "script" application
3. Copy .env.example to .env:

   cp .env.example .env

4. Edit .env with your Reddit API credentials:

   CLIENT_ID="your_reddit_client_id"
   CLIENT_SECRET="your_reddit_client_secret"
   USER_AGENT="script:advisor-sentiment:v1.0 (by /u/your_username)"
   

3. Collect Data

python3 run_assistant.py

This will:

• Connect to Reddit API
• Scan r/WallStreetBets for stock mentions (AAPL, TSLA, GOOG)
• Store mentions in local SQLite database

4. Get Investment Recommendations

python3 run_advisor.py

This will:

• Analyze sentiment of all collected mentions
• Provide BUY/SELL/HOLD recommendations
• Show sentiment scores and mention counts

CLI Usage

Data Collection (Assistant)

# Collect data from Reddit (default)
python3 run_assistant.py

# Specify source explicitly
python3 run_assistant.py --source reddit

# Use custom config file
python3 run_assistant.py --config my_config.json

Analysis & Recommendations (Advisor)

# Analyze all tracked stocks
python3 run_advisor.py

# Analyze specific stocks
python3 run_advisor.py --stocks AAPL TSLA

# Get detailed analysis for one stock
python3 run_advisor.py --detail AAPL

Configuration

Stock Symbols

Edit advisor/scrapers/reddit/config.json to change tracked stocks:

{
  "max_days": 3,
  "min_days": 1,
  "subreddits": ["WallStreetBets"],
  "tickers": ["AAPL", "TSLA", "GOOG", "MSFT"]
}

Sentiment Thresholds

Recommendation logic (configured in advisor/core/config.py):

• BUY: Sentiment ≥ 0.7 with ≥5 mentions
• SELL: Sentiment ≤ 0.3 with ≥5 mentions
• HOLD: Otherwise (neutral sentiment or insufficient data)

Project Structure

advisor/
├── core/           # Core functionality
│   ├── config.py   # Configuration management
│   ├── database.py # SQLite operations
│   └── data_source.py # Base scraper class
├── scrapers/       # Data collection
│   └── reddit/     # Reddit scraper
├── analysis/       # Sentiment analysis
│   └── sentiment.py
└── cli/           # Command line interfaces
    ├── assistant.py # Data collection CLI
    └── advisor.py   # Analysis CLI

Database

The tool uses SQLite with two main tables:

• stocks: Stock symbols being tracked
• mentions: Individual Reddit mentions with sentiment scores

Database file: advisor.db (created automatically)

Security

• API credentials are stored in .env file (not committed to git)
• No sensitive data is logged or exposed
• All database queries use parameterized statements

Extending

Add New Data Sources

1. Create new scraper in advisor/scrapers/
2. Inherit from DataSource base class
3. Implement required methods
4. Add to assistant CLI

Enhanced Sentiment Analysis

The current implementation uses keyword-based sentiment analysis. To integrate with LLM APIs:

1. Add API credentials to .env
2. Modify SentimentAnalyzer.analyze_text() method
3. Replace keyword logic with API calls

License

This project is for educational purposes. Ensure compliance with Reddit's API terms and rate limits.