I am wondering if it's mathematically 'correct' to employ a correlation matrix based on Kendall-correlation when constructing a covariance matrix?

I.e., is it wrong to multiply standard deviations of e.g. returns with the Kendall-correlation-matrix to form a covariance matrix?

That is, I am only changing the correlation estimates to be based on Kendall's tau instead of the standard Pearson linear correlation coefficient when 'constructing' my covariance matrix.

  • $\begingroup$ I have the same problem. I wonder if there is anyone to answer this question... $\endgroup$
    – Sara
    Commented Nov 27, 2018 at 17:14

1 Answer 1


A first hint:

To convert Kendall's $\tau$ to the Pearson correlation coefficient $\rho$, one could use the relationship: $$\rho = \sin\Bigl(\frac{\pi}{2}\tau\Bigr)$$

But keep in mind that this only holds for the bivariate normal copula assumption, I don't know if this also holds to convert "plain vanilla" correlation matrices, see McNeil et al. (2005: Proposition 5.29).


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.