rochitasundar / Stock-clustering-using-MLView external linksLinks
The project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and face lower risk by tempering potential losses when the market is down.
☆16Jan 20, 2022Updated 4 years ago
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