autoregressive conditional heteroskedasticity

Autoregressive Conditional Heteroskedasticity (ARCH) is a statistical model used to analyze time series data, particularly in finance. It recognizes that the variability or volatility of a variable like stock returns can change over time—sometimes it's more unpredictable, other times more stable. ARCH models assume that current volatility depends on past errors or shocks, meaning recent large changes can lead to higher future variability. This helps in better understanding and forecasting periods of market instability, allowing investors and analysts to manage risks more effectively.