Economics, Econometrics and Finance
6 years ago

Uncovering Hidden Volatility Patterns in Time Series Data for Better Predictions

Elsevier eBooks
Volatility and Generalized Autoregressive Conditional Heteroskedastic Processes
Terence C. Mills

Paper Summary

Volatility in a time series means periods with high variability or increasing variance. The autoregressive conditional heteroskedastic (ARCH) process is a popular model for capturing this. Ignoring ARCH can cause statistical issues, so it's important to test for it. ARCH models estimate conditional variance, giving a direct measure of volatility.

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