A New Method of Portfolio Selection Using Mutual Information and MST
Abstract
The stock market fluctuates randomly since it is a complex system which is formed by the interaction of individual factors. One of the approaches to researching such an interaction-based complex system is network analysis. The current paper proposes a new portfolio selection method utilizing the structural information of the network. First of all, the co-relationship between assets is worked out using mutual information, and on this basis, MST is generated. Next, the scores of three centralities - degree centrality, closeness centrality, and betweenness centrality are calculated on the network. Finally, various portfolios are constructed based on the rankings of the centralities of each asset, and their effectiveness is examined. The findings of the experiment showed that the portfolios composed of stocks with low centrality scores produce higher returns, and this proved that there is a negative relationship between the centrality of assets and the weight of portfolios in the network and verified the usefulness of mutual information in the network analysis.
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