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From this paper: Ledoit, Olivier, and Michael Wolf. "Honey, I shrunk the sample covariance matrix." (2003).

I learned a way of shrinking the covariance matrix to get more robust portfolio optimization performance. Yet in the note #4, it says,

The constant correlation model would not be appropriate if the assets came from different asset classes, such as stocks and bonds. But in such cases more general models for the shrinkage target are available.

Does anyone know any such "more general models"? Thanks.

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    $\begingroup$ Instead of the model "all stocks i,j have the same correlation $\phi$" we would need to implement the model "the correlation between any two stocks is $\phi$, the correlation between any two bonds is $\psi$ and the correlation between a stock and a bond is $\eta$. So we would have three parameters in the correlation matrix model (that we shrink towards) rather than one. How to actually implement this mathematically I know not. $\endgroup$ – Alex C Mar 9 '18 at 17:57
  • $\begingroup$ @AlexC, thanks! Do you know of any paper on this question? $\endgroup$ – user40780 Mar 9 '18 at 21:49

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