Discussion
When the variance of financial time series varies over time, which of the following models is more suitable ?
Answer: D
The suitable models are ARCH and GARCH.
Financial returns often show volatility clustering: calm periods and turbulent periods, with the variance changing over time (heteroscedasticity). Engle's ARCH model makes the conditional variance depend on past squared errors, and Bollerslev's GARCH adds past variances as well, so they model this time-varying volatility directly.
AR, MA and ARMA models describe the conditional mean of a series and assume a constant error variance, so they cannot capture changing volatility.
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