Take for example the S&P500 universe with 500 stocks. Something interesting would be to create clusters based on stocks' correlations in order to have clusters that have the same "direction" in the market. That's easily done by a clustering algorithm, with a well-defined distance matrix from the correlation matrix.
But if we want to cluster the 500 stocks based on both stocks' correlations and features, how would we do that ? As far as I know the clustering algorithms only works with either similarity measures (often correlations) or features (P/E ratio, size...) but not both at the same time.
Do you have any idea ?