Autoregressive Conditional Heteroskedasticity (ARCH)

Autoregressive Conditional Heteroskedasticity (ARCH) is a statistical model used to analyze time series data, particularly in finance. It recognizes that the variability of data, like stock prices, changes over time. For instance, during periods of market turbulence, price fluctuations can become more pronounced. ARCH models help capture this pattern by using past data to predict future volatility, allowing analysts to better understand risks and make informed decisions. Essentially, ARCH shows how uncertainty in data can change and helps in forecasting future trends based on observed patterns of volatility.