Financial Data Analysis and Visualization

This repository contains Jupyter notebooks for analyzing and visualizing financial data using Python libraries such as numpy, pandas, matplotlib, and yfinance.

Contents

1. Financial Metrics Analysis (Financial Metrics Analysis.ipynb)

   • This notebook calculates various financial metrics for different stock indices and individual stocks. The metrics include cumulative returns, volatility, Sharpe ratio, Sortino ratio, and maximum drawdown.
   • The data is sourced from Yahoo Finance.

2. Stock Patterns Visualization (Stock Patterns Visualization.ipynb)

   • This notebook identifies and visualizes various stock patterns such as Bull Flag, Bear Flag, Ascending Triangle, Descending Triangle, Head & Shoulders, Inverse Head & Shoulders, Cup & Handle, and Inverse Cup & Handle.
   • The patterns are plotted on historical stock closing price charts for better visualization.

3. Apple Stock Data Analysis (Buy Sell Signal.ipynb)

   • This notebook downloads and analyzes historical stock data for Apple (AAPL) from January 1, 2010, to June 15, 2023.
   • The data includes information about the stock's opening, high, low, close, adjusted close prices, and volume.
   • Makes Buy-Sell signals based on historic data

Requirements

• Python 3.x
• Jupyter Notebook
• numpy
• pandas
• matplotlib
• yfinance

Usage

Each notebook is designed to be run interactively. Follow the instructions within each notebook to understand the functionality and output.

Contributing

Contributions are welcome! Please fork this repository and submit pull requests with improvements or additional features.