The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPOs) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki Stock Exchange by using a statistically validated network method to infer investor links based on the co-occurrences of investors’ trade timing for 69 IPO stocks. Our findings show that a rather large part of statistically similar network structures form in different securities and persist in time for mature and IPO companies. We also find evidence of institutional herding.

Previous studies suggest that individuals sharing similar characteristics establish stronger social relationships. This motivates us to examine what combinations of socioeconomic investor attributes are more likely to be associated with joint trading behavior. We use a unique data set on actual social ties between investors and find that similarities in investors’ age, geographical location, or length of the co-employment can affect trade synchronization under certain circumstances. Our findings have implications for the analysis of investor networks.

The starting point of this paper is that neighboring investors may talk to each other sharing information about their transactions in stock markets, leading to similar trading behavior. We find that pairwise trade timing similarities between investor pairs are negatively associated to geographical distance between corresponding investor pairs. This suggests that local information transfer channels between neighboring individual investors are used in decision making. We also observe that differences in age and language moderate this association. The analysis is conducted using investor level data from different regions of Finland.