Statistical Investigation of Connected Structures of Stock Networks in a Financial Time Series

Abstract

In the study, we have evaluated the deterministic factors that can influence the connected structure of a stock network. The representative index for the topological properties of a stock network is the number of links it has with other stocks. We utilize the coefficient of determination from the multi-factor model, which attempts to explain stock returns with several explanatory variables. In this study, factors refer to common factors that commonly affect stocks, on the basis of the arbitrage pricing theory acknowledged in the relevant financial literature. We utilize individual stocks traded on the market indices of Korea, Japan, Canada, Italy, and the UK. We find that stocks with a large number of links in a stock network can be better explained by factors in the multi-factor model than stocks with a small number of links with other stocks. These results indicate that common factors in the field of finance are significant deterministic factors that should be taken into consideration when constructing a stock network.