I am trying to compute equity VaR, forex VaR and total VaR on an international portfolio (10 stocks x 4 countries). Since I am not interested in the risk disaggregation among diffrent countries I was thinking to apply PCA directly on $\sigma_E$, $\sigma_X$ and $\sigma$ respectively; where $\sigma_E$ is the covariance matrix of the stocks log-returns in local currencies, $\sigma_X$ is the covariance matrix of log-returns on exchange rates and $\sigma$ the covariance matrix of all log-returns (stocks and exchange rates).
While there shouldn't be any problem for the forex VaR, I am not quite sure I can use PCA on log-returns denominated in different currencies in order to find the equity VaR. My main concern is on how to find and interpret the principal components coefficients. Let’s say that I decide to use 5 PCs that will replace my 40 stocks log-returns, how do I find the coefficients?
Would it be possible to create an a-doc portfolio from the log returns denominated in different currencies (without converting them):
$r_p = w_1 r_1^€+ … + w_{10} r_{10}^€ + w_{11} r_1^{DKK} + … + w_{20} r_{10}^{DKK}+ ...$
And then regress it on the principal component factors like this:
$r_p = α + β_1 PC_1 + ... + β_5 PC_5 + ϵ$
The reason I am trying to do this is because I would prefer avoid having PCA (or a foundamental factor model) for each country, otherwise I would still have an equity and total variance-covariance matrix with nonzero covariance’s and I would then have to use a multivariate GARCH.