The 3 main components of this repository: 👜

1. Stock Data Analysis 📈

• Using Python, fetched historical stock data for any 5 stocks from the Nifty 50 index using the yfinance library. Used a time range of the last 6 months.
• Performs the following analyses on the data:
  • Calculates the daily percentage change for each stock.
  • Plots the closing prices and daily percentage changes for the 5 stocks.
  • Calculates the moving average (20-day) for each stock and plot it against the stock's closing price.

2. Strategy Development 🪖

• Developed a simple moving average crossover strategy for one of the 5 stocks. The strategy involves a short-term moving average (e.g., 50-day) and a long-term moving average (e.g., 200-day).
• Back-tested this strategy on the historical data to identify buy and sell signals.
• Calculated the returns generated by the strategy compared to a simple buy-and-hold approach.

3. Risk Management 🚨

• Calculated the maximum drawdown for each stock over the 6-month period.
• For the stocks selected in module 2, implemented a stop-loss mechanism. Assumed a stop loss of 5%. Re-ran the strategy with the stop-loss and compared the performance to the original strategy.

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The Jupyter Notebook contains all the necessary plots 📊 and explanations 👨‍🏫, and is well-documented with comments and explanations where necessary.✨