AkinfProject - Advanced Stock Analysis Tool

A comprehensive Haskell-based stock market analysis application that provides advanced financial analytics including trend detection, risk assessment, moving averages, and portfolio correlation analysis.

Features

📈 Stock Analytics

• Best/Worst Day Analysis: Find the highest gain and loss days for each stock
• Return on Investment (ROI): Calculate total ROI over the specified timeframe
• Trend Detection: Classify trends as Upward, Downward, or Sideways
• Risk Assessment: Evaluate volatility and assign risk levels (Low/Medium/High)

📊 Technical Indicators

• Simple Moving Averages: SMA 20, 50, and 200-day calculations
• Trading Signals: Bullish, Bearish, and Neutral signals based on MA crossovers
• Volatility Analysis: Daily volatility calculations and averaging

🔗 Portfolio Analysis

• Correlation Matrix: Calculate correlations between all stock pairs
• Diversification Assessment: Evaluate portfolio risk spread
• Multi-Stock Support: Analyze multiple stocks simultaneously

Requirements

System Requirements

• Haskell: GHC 9.6.7 or later
• Cabal: Latest version (comes with GHC)
• Operating System: Windows, Linux, or macOS

Haskell Dependencies

All dependencies are automatically managed by Cabal:

• vector - Efficient arrays
• yaml - YAML configuration parsing
• cassava - CSV file parsing
• bytestring - Byte string operations
• containers - Map and Set data structures
• tasty - Testing framework
• tasty-hunit - Unit testing

Installation

1. Clone or Download the Project

# If using git
git clone <repository-url>
cd akinf-project

# Or download and extract the project files

2. Install Haskell (if not already installed)

Windows:

• Download GHC from: https://www.haskell.org/ghc/download.html
• Or use Chocolatey: choco install ghc cabal

Linux (Ubuntu/Debian):

sudo apt-get update
sudo apt-get install ghc cabal-install

macOS:

# Using Homebrew
brew install ghc cabal-install

3. Update Cabal Package Index

cabal update

Project Structure

akinf-project/
├── app/
│   └── Main.hs                 # Application entry point
├── src/
│   └── AkinfProject/
│       ├── Calculate.hs        # Core analytics calculations
│       ├── Config.hs          # Configuration parsing
│       ├── CSV.hs             # CSV data parsing
│       ├── Filter.hs          # Data filtering
│       └── Output.hs          # Result formatting and display
├── test/
│   ├── Spec.hs               # Comprehensive test suite (29 tests)
│   └── test-config.yaml      # Test configuration
├── config.yaml               # Main configuration file
├── all_stocks_5yr.csv        # Sample stock data
├── akinf-project.cabal       # Project dependencies and build config
├── README.md                 # This file
├── run.bat                   # Windows run script
└── run.sh                    # Linux/macOS run script

Configuration

Edit config.yaml to specify which stocks to analyze and the timeframe:

stocks: ["AAPL", "MSFT", "GILD", "ADP"]  # Stock symbols to analyze
timeframe:
  start_date: "2013-09-24"               # Start date (YYYY-MM-DD)
  end_date: "2018-01-16"                 # End date (YYYY-MM-DD)

Usage

Building the Project

# Build the project
cabal build

# Build and run in one command
cabal run akinf-project

Running Tests

# Run the complete test suite (29 tests)
cabal test

# Run tests with verbose output
cabal test --test-show-details=always

Quick Start Scripts

Windows:

# Double-click or run from command prompt
run.bat

Linux/macOS:

# Make executable and run
chmod +x run.sh
./run.sh

Manual Execution

# Step-by-step manual execution
cabal update              # Update package index
cabal build              # Build the project
cabal test               # Run tests
cabal run akinf-project  # Run the application

Sample Output

==========================================
         STOCK ANALYSIS RESULTS
==========================================
Stock: AAPL
  ----------
  Best day:  2015-08-24 (8.70% gain)
  Worst day: 2015-08-25 (-6.63% loss)
  Total ROI: 152.16%
  Trend:     Upward
  Volatility: 1.64% (daily avg)
  Risk Level: Low (Conservative investment)
  Moving Averages:
    SMA 20:  $70.20
    SMA 50:  $73.24
    SMA 200: $79.24
    Signal:  Bearish (Strong sell signal)

==========================================
SUMMARY:
  Total stocks analyzed: 4
  Stocks with valid data: 4
  Highest single-day gain: 11.72%
  Average ROI: 103.99%
  Average volatility: 1.71%
  Risk distribution: Low: 4, Medium: 0, High: 0

==========================================
       PORTFOLIO CORRELATION ANALYSIS
==========================================
Stock Correlations:
  AAPL <-> MSFT: 0.415 (Moderate)
  ADP <-> MSFT: 0.421 (Moderate)
Average Correlation: 0.324
Portfolio Diversification: Moderately Diversified
==========================================

Data Format

The application expects CSV data with the following columns:

• date - Date in YYYY-MM-DD format
• open - Opening price
• high - Highest price of the day
• low - Lowest price of the day
• close - Closing price
• volume - Trading volume
• Name - Stock symbol

Technical Details

Architecture

• Modular Design: Separated concerns across multiple modules
• Type Safety: Leverages Haskell's strong type system
• Functional Programming: Pure functions with clear data flow
• Error Handling: Robust handling of missing/invalid data

Algorithms

• ROI Calculation: (final_price - initial_price) / initial_price * 100
• Volatility: Daily (high - low) / open * 100, then averaged
• Correlation: Pearson correlation coefficient between daily returns
• Moving Averages: Simple moving averages over specified periods
• Risk Assessment: Based on volatility thresholds (Low < 4%, Medium < 8%, High >= 8%)

Performance

• Efficient Data Structures: Uses Vector for numerical computations
• Lazy Evaluation: Haskell's lazy evaluation optimizes memory usage
• Streaming: Processes large CSV files efficiently

Testing

The project includes comprehensive test coverage:

• 29 Unit Tests covering all calculation functions
• Edge Case Testing for missing data and boundary conditions
• Integration Tests for complete workflow validation
• Mathematical Accuracy verification for all financial calculations

Run tests with:

cabal test

Troubleshooting

Common Issues

1. "Command not found: cabal"

   • Install GHC and Cabal tools
   • Ensure they're in your system PATH

2. Build errors

   • Run cabal update to refresh package index
   • Check GHC version compatibility

3. CSV parsing errors

   • Verify CSV file format matches expected headers
   • Check for encoding issues (should be UTF-8)

4. Empty results

   • Verify stock symbols exist in the CSV data
   • Check date range in config.yaml

Debug Mode

For detailed error information, run with verbose output:

cabal run akinf-project --verbose

Development

Adding New Indicators

1. Add calculation function to src/AkinfProject/Calculate.hs
2. Update StockAnalysis data type if needed
3. Add display logic to src/AkinfProject/Output.hs
4. Write unit tests in test/Spec.hs

Code Style

• Follow standard Haskell conventions
• Use type signatures for all top-level functions
• Include Haddock documentation comments
• Run tests before committing changes

License

This project is available under the terms specified in the LICENSE file.

Support

For issues or questions:

1. Check the troubleshooting section above
2. Review the test suite for usage examples
3. Examine the source code - it's well-documented