Mastering Volatility Forecasting: A Step-by-Step Guide to Building a Powerful GARCH Model in Python
Develop GARCH Volatility Prediction Model using Python
This article aims to provide a comprehensive guide on developing a volatility forecasting model using Python. We will utilize the yfinance library to retrieve historical volatility data and implement the GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model to estimate and forecast volatility.
Volatility is a crucial aspect of financial markets as it measures the degree of variation in the price of a financial instrument over time. Accurate volatility forecasting can assist traders and investors in making informed decisions and managing risk effectively.
