Bivariate GARCH model to obtain dynamic optimal hedge ratio - R The optimal hedge ratio is the ratio of the covariance between the futures and spot price, to the variance of the future price. I estimated it already as the slope coefficient of an OLS regression of spot prices on futures prices. But it is static and I want to see its evolution.
Some authors tried modeling a bivariate GARCH (1,1) model, and that's what I am trying to do, using R.
I have no idea how to do it (using R), and what GARCH parameters would be the estimates of the optimal hedge ratio.
Thanks a lot in advance!

Define and estimate a bivariate GARCH model. Extract fitted (for in-sample analysis) or predicted (for out-of-sample analysis) conditional variances $\{\hat\sigma_{x,t}^2\}$ and covariances $\{\hat\sigma_{xy,t}\}$. The minimum-variance hedge ratio at time $t$ will be $\frac{ \hat\sigma_{xy,t} }{ \hat\sigma_{x,t}^2 }$. (Parameters of the GARCH model are not directly needed for obtaining the hedge ratio.)
How to do it in R? Try the rmgarch package for building and fitting multivariate GARCH models. See its vignette. The author's website contains some examples, too. (If you do not like rmgarch, there are several other packages by other authors for fitting multivariate GARCH models.)
