Abstract-- Successful investment management relies on allocating assets so as to beat the stock market. Asset classes are affected by different market dynamics or latent trends. These interactions are crucial to the successful allocation of monies. The seminal work on portfolio management by Markowitz prompts the adroit investment manager to consider the correlation between the assets in his portfolio and to vary his selection so as to optimize his riskreturn profile. The factor model, a popular model for the return generating process has been used for portfolio construction and assumes that there is a low rank representation of the stocks. In this work we contribute a new approach to portfolio diversification by comparing a recently developed clustering technique, SemiNMF, with a new sparse low-rank approximate factorization technique, Sparse-semiNMF, for clustering stocks into latent trend based groupings as opposed to the traditional sector based groupings. We evaluate these techniq...