Theories: GARCH (Generalized Autoregressive Conditional Heteroskedasticity)

GARCH (Generalized Autoregressive Conditional Heteroskedasticity) is a statistical model used to analyze and forecast financial market volatility—how much prices fluctuate. It assumes that the variability (volatility) of returns today depends on past fluctuations and previous levels of volatility, meaning periods of high or low volatility tend to cluster over time. By capturing this behavior, GARCH helps traders and analysts better estimate future risks, improve pricing of financial instruments, and develop more accurate investment strategies. It’s widely used because it reflects how real markets often experience unpredictable swings that tend to persist in clusters.