3D Subspace Clustering for Value Investing

Using Graham´s rules on picking stocks has been proven to generate profits for value investors. The authors propose using 3D subspace clustering to generate rules to pick potential undervalued stocks; 3D subspace clustering is effective in handling high-dimensional financial data and is adaptive to new data. In addition, its results aren´t influenced by human biases and emotions, and are easily interpretable.