A Comprehensive Guide to Monte Carlo Simulation for Stock Price Forecasting and Prediction Interval Generation

This project demonstrates how to use Monte Carlo simulation to forecast stock prices. The notebook begins with a disclaimer, emphasizing that the simulation is for informational purposes and not financial advice. It then outlines a step-by-step process, starting with importing necessary dependencies like NumPy, pandas, and yfinance. The user can define a stock ticker and a start date to import historical data. The notebook includes functions to calculate daily log returns, plot them, and determine volatility. The core of the project is the Monte Carlo simulation itself, which is used to generate multiple possible future price paths. Finally, the notebook includes sections for plotting the simulation results, testing with live data, and an implementation of the simulation within a class structure.

This project provides a tutorial on using Monte Carlo simulation to forecast stock prices and create empirical prediction intervals.