ARCH (Autoregressive Conditional Heteroskedasticity)

ARCH (Autoregressive Conditional Heteroskedasticity) is a statistical model used to analyze and predict the variability or volatility of time series data, such as financial returns. It recognizes that periods of high volatility tend to cluster together, meaning that if the market is turbulent now, it's likely to stay turbulent for a while. The model adjusts its predictions of future variability based on past fluctuations, allowing for more accurate risk assessment. Essentially, ARCH helps understand and forecast how unpredictable or stable a variable like stock prices may be over time.