Arch Generalized Autoregressive Conditional Heteroskedasticity (ARCH)

ARCH, or Autoregressive Conditional Heteroskedasticity, is a statistical model used to analyze and predict the volatility of financial time series data, such as stock prices. It recognizes that the variability of a series can change over time, often influenced by its own past behavior. For example, after a market crash, volatility tends to increase. By accounting for these changing levels of risk, ARCH helps economists and investors better understand potential future fluctuations, thereby informing their decisions in uncertain financial environments.