Long Memory and ARCH: Time Series Math 342

This lecture covers the concept of long memory in time series, where correlations vary slowly as time increases. It explores covariance models with polynomial decay, spectral behavior, and the FARIMA class. Additionally, it delves into Autoregressive Conditional Heteroskedasticity (ARCH) processes, inspired by financial time series, focusing on log-returns, conditional mean, and variance estimation.