Monte Carlo Simulation

Think of it as a way to predict how a stock's price might behave in the future, considering factors like how much it usually goes up or down each day. The code grabs historical stock price information for Nvidia from the internet. It's like looking at past performance to try and guess what might happen in the future. We're interested in Nvidia because we want to predict its future stock prices. we calculate on average expected return and the volatility for Nvidia over the last 3 years. These numbers give us an idea of what we think might happen to Nvidia's stock price in the future.

We calculate two important numbers, the average daily change in stock price (mu), and how much the stock price usually varies each day (sigma). These help us make our predictions. It's like figuring out how much a stock typically changes each day on average. This helps us understand its normal behavior.

We decide how long we want to predict into the future (T), and how many different future scenarios we want to consider (num_simulations). It's like deciding how far ahead we want to look and how many guesses we want to make about what might happen.

We use the recipe from the monte carlo paths function to create many different possible future scenarios for Nvidia's stock price. Think of it like making lots of guesses about what might happen to the stock price based on its past behavior.