Stock Market Data Analysis Project (Task - 5)

This project was created for my internship at Outrix, wherein I have created a comprehensive Python-based tool for analyzing stock market data, generating insights, and creating visualizations to support investment decision-making. I would like to thank them for allowing me to showcase my skills and give excellent project ideas for me to work on. There are more awesome project given by them which I will be uploading soon.

Features

• Real-time Data Collection: Fetch current and historical stock data from multiple sources
• Technical Analysis: Calculate popular technical indicators (RSI, MACD, Bollinger Bands, Moving Averages)
• Trend Analysis: Identify bullish and bearish patterns in stock movements
• Portfolio Tracking: Monitor multiple stocks and analyze portfolio performance
• Interactive Visualizations: Generate charts and graphs for better data interpretation
• Risk Assessment: Calculate volatility, beta, and other risk metrics
• Comparison Tools: Compare multiple stocks side-by-side
• Export Functionality: Save analysis results to CSV, Excel, or PDF formats

Installation

Prerequisites

• Python 3.8 or higher
• pip package manager

Setup

1. Clone the repository:

git clone https://github.com/loctal6/OutriX_tasks
cd OutriX_tasks

2. Create a virtual environment:

python -m venv stock_env
stock_env\Scripts\activate

3. Install required dependencies:

pip install -r requirements.txt

4. Set up API keys (optional, not really needed):

cp config/config_template.py config/config.py
# Edit config.py with your API keys

Quick Start

Basic Stock Analysis

from stock_analyzer import StockAnalyzer

# Initialize analyzer
analyzer = StockAnalyzer()

# Analyze a single stock
data = analyzer.get_stock_data('AAPL', period='1y')
analysis = analyzer.analyze_stock('AAPL')

# Generate basic chart
analyzer.plot_stock('AAPL', indicators=['SMA_20', 'SMA_50'])

Portfolio Analysis

from portfolio_analyzer import PortfolioAnalyzer

# Create portfolio
portfolio = PortfolioAnalyzer(['AAPL', 'GOOGL', 'MSFT', 'TSLA'])

# Get portfolio performance
performance = portfolio.calculate_performance()
portfolio.plot_portfolio_comparison()

Project Structure

stock-market-analysis/
├── src/
│   ├── data_collector.py               # Data fetching and cleaning
│   ├── technical_indicators.py         # Technical analysis calculations
│   ├── stock_analyzer.py               # Main analysis engine
│   ├── portfolio_analyzer.py           # Portfolio management tools
│   └── visualizer.py                   # Charting and visualization
├── notebooks/
│   ├── exploratory_analysis.ipynb
│   ├── technical_analysis_demo.ipynb
│   └── portfolio_optimization.ipynb
├── data/
│   ├── raw/                            # Raw market data
│   └── processed/                      # Cleaned and processed data
├── config/
│   ├── config_template.py              # Configuration template
│   └── settings.py                     # Application settings
├── tests/
│   └── test_*.py                       # Unit tests
├── requirements.txt
└── README.md

Limitations

• Real-time data may have slight delays
• Some technical indicators require minimum data periods
• API rate limits may restrict frequent data updates
• Historical data accuracy depends on data sources