[R-SIG-Finance] Anyone interested in random matrix theory?

[Brian Lee Yung Rowe]

Hi,

Is anyone interested in portfolio optimization based on random matrix
theory? I am considering packaging some code I wrote that filters
portfolio correlation matrices based on random matrix theory. The basic
idea is that there is a predictable eigenvalue distribution for a random
matrix and based on that you can take a custom returns correlation
matrix, fit the eigenvalue distribution to the theoretical distribution
(based on Marcenko-Pastur) and then filter out those eigenvalues. You
can then reconstruct the correlation matrix, which in theory has more
signal to noise than you would get otherwise. 

>From my initial tests, when optimizing a portfolio using the cleaned
correlation matrix, you do get lower risk (and better Sharpe ratio) than
you would with an equal weighted portfolio or a portfolio optimized
using a multi-factor model. 

What is really interesting about random matrix theory is that the fit to
the Marcenko-Pastur theoretical distribution is quite resilient and can
handle small portfolios with a short window. This addresses one of my
biggest gripes I have regarding the Barra approach, that you need to
have so much data and the response is somewhat slow due to the long
windows in the regressions.

Anyway, I am considering packaging this code, but prior to doing so
wanted to get a sense if anybody has done this (cheap searches say no)
and if anyone is interested in RMT to make it worthwhile.

Regards,
Brian