The GARCH Model, or Generalized Autoregressive Conditional Heteroskedasticity Model, is a statistical tool used to analyze and forecast the volatility of time series data, particularly in financial markets. It helps in understanding how the variability of a dataset changes over time, allowing for better risk management and investment decisions. Developed by Tim Bollerslev in 1986, the GARCH Model extends the earlier ARCH Model created by Robert Engle. By incorporating past variances into its calculations, the GARCH Model provides a more accurate representation of changing volatility, making it valuable for economists and financial analysts.