Hi Jason - Yes, I am currently working on developing an asset allocation model under the MVO framework. But firstly I am trying to understand, rather qualitatively, the risk of asset classes and their behavior in pairs i.e covariance. I think risk, and its statistical measure such as standard deviation, has got its utility largely as inputs to MVO. And the theory behind it that risks are not additive.

I think there is low correlation even among extreme events. For example I took a vector of 15 worst returns between India Equity and MSCI EM ex Japan (arrange the daily returns of these two in a single continuous array and pick the worst - Rank function). Now, for every return, I pick the alternate asset class's return (same day return). I find the correlation between these two arrays is +0.36. I think that is low, given that I am testing the tail.

Are there any other tests (especially non-parametric) that you think is useful to test and understand risks between asset classes. What I like about non-parametric is they are intuitive and easy to explain.