| By: |
Rice, Gregory;
Wirjanto, Tony;
Zhao, Yuqian |
| Abstract: |
Crude oil intra-day return curves collected from the commodity futures market
often appear to be serially uncorrelated and long-range dependent. Existing
functional GARCH models, while able to accommodate short range conditional
heteroscedasticity, are not designed to capture long-range dependence. We
propose and study a new functional GARCH-X model for this purpose, where the
covariate X is chosen to be weakly stationary and long-range dependent.
Functional analogs of autocorrelation coefficients of squared processes for
this model are derived, and compared to those estimated from crude oil return
curves. The results show that the FGARCH-X model provides a significant
correction to existing functional volatility models in terms of an in-sample
fitting, while its out-of-sample performances do not appear to be more
superior than those of the existing functional GARCH models. |
| Keywords: |
Crude oil intra-day return curves, volatility modeling and forecasting, functional GARCH-X model, long-range dependence, basis selection |
| JEL: |
C13 C32 C58 G10 G17 |
| Date: |
2021–08–18 |
| URL: |
http://d.repec.org/n?u=RePEc:pra:mprapa:109231&r= |