An Analysis of Centrality’s Features as a New Measure for Network Analysis, Risk Measurement & Portfolio Selection

In network theory, centrality is a measure to estimate importance and influence of a special node to the whole network structure. The aim of this research is to investigate the characteristics of stock centrality and its reliability in risk estimation and portfolio selection.

First in this paper, we analyzed the relationship between stock’s centrality & benchmark risk estimation measures like beta & standard deviation. Then, we analyzed the relationship between stock’s centrality & Markowitz framework’s weights; and finally, we introduced centrality-based portfolio selection strategy and compared it with other benchmarks, by different portfolio performance measures.

Our observations indicate that in Tehran stock exchange, centrality can have an effective role in stocks risk estimation and there is a meaningful relation between centrality and other measures. We also observed that out that low central stocks can raise the benefits of portfolio diversification, and centrality-based portfolio selection method can have a better performance than other benchmark portfolio selection methods and results in a better risk adjusted return.

Stock centrality, as a measure to estimate importance and influence of member of a network, is capable of describing stock risk characteristics like other accepted measures. We can take advantage of this capability for portfolio selection.