GARCH, or Generalized Autoregressive Conditional Heteroskedasticity, is a statistical model used to analyze and forecast the volatility of time series data, particularly in finance. It helps in understanding how the variability of a financial asset's returns changes over time, allowing analysts to better assess risk and make informed investment decisions. The GARCH model builds on earlier models by incorporating past variances and returns to predict future volatility. This approach is particularly useful for assets that exhibit periods of high and low volatility, making it a popular tool among economists and financial analysts for modeling market behavior.