In this Project I analyzed Apple's stock price data using Python and the 'yfinance' package.

The Python code retrieves the data, cleans it,  then visualized the stock price over time using a line plot and candlestick chart

Next, we calculated the daily returns and volatility of the stock,

 and plotted its cumulative returns.

We then used a histogram and density plot to visualize the distribution of daily returns, 

We also implemented a Moving Average Crossover strategy to generate buy/sell signals based on the stock's 50-day and 200-day moving averages, and calculated the daily profit/loss based on these signals.

We then examined the correlation between Apple's stock returns and those of the S&P 500 

using a scatter plot and correlation coefficient.

Finally, We performs a Monte Carlo simulation to predict future Apple stock prices based on historical daily returns.