Clusters of investors around initial public offering

Abstract

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.International Securities Identification Number (ISIN), company, industry, total number of transactions, total number of unique investors and the IPO day of the security. ISINs from the error-free set are marked in bold PALGRAVE COMMUNICATIONS | https://doi.

Structure of Investor Networks and Financial Crises

“…Next, to infer the annual investor category networks we follow the methodology used in [ 6 , 10 ]. First, for each security k , for each investor category i and each trading day t we calculate the net-scaled-volume as: where and respectively are the total purchased and sold volumes in some security k of investor category i on day t respectively.…”

“…Overall, there are many alternative techniques, but in this paper, we focus on using the hypergeometric test for two important reasons: (i) It can be used with sparse data, and (ii) it is not sensitive to outliers. Moreover, to our best knowledge, the method introduced in [ 6 ] is the one of the most widely used methods to estimate investor networks (see, for example, [ 10 , 11 , 12 , 13 ]).…”

“…Our methodological framework comes from complex network theory, which has been successfully applied to model investors’ behavior and interactions in stock and FX markets. There are various estimation techniques used with rich sets of shareholder registration data [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. The research on investor networks sheds light on investor’s trade timing synchronization, which is closely related to herding behavior.…”

“…At the same time, to our best knowledge, this is the first paper that statistically investigates whether investor network topology changes across market conditions, which is the main contribution of this paper. Our question is motivated by the existing empirical evidence that investors are clustered and that the clusters of investors change over time [ 6 , 10 , 12 ]. Indeed, the literature has barely addressed how investor networks’ structure reflects market conditions.…”

Trade synchronization and social ties in stock markets

“…We use this data set not only to match insiders' IDs, but we also use it to analyze insider trade synchronization. 14 More information about the Euroclear data set can be found in other research publications (see, e.g., [9,11,16,[44][45][46][47][48][49]).…”