Autoregressive Conditional Heteroskedasticity (ARCH) is a statistical model used to analyze time series data where the variability of the data changes over time. It helps in understanding and predicting the volatility of financial markets, where periods of high volatility can be followed by periods of low volatility. The model assumes that the current variance is influenced by past errors, making it useful for modeling financial returns. The ARCH model was introduced by economist Robert Engle in 1982, and it has since been extended to more complex forms, such as GARCH (Generalized Autoregressive Conditional Heteroskedasticity). These models are widely used in econometrics and finance to assess risk and make informed investment decisions based on changing market conditions.