Dynamics of investor spanning trees around dot-com bubble

Abstract

We identify temporal investor networks for Nokia stock by constructing networks from correlations between investor-specific net-volumes and analyze changes in the networks around dot-com bubble. The analysis is conducted separately for households, financial, and non-financial institutions. Our results indicate that spanning tree measures for households reflected the boom and crisis: the maximum spanning tree measures had a clear upward tendency in the bull markets when the bubble was building up, and, even more importantly, the minimum spanning tree measures pre-reacted the burst of the bubble. At the same time, we find less clear reactions in the minimal and maximal spanning trees of non-financial and financial institutions around the bubble, which suggests that household investors can have a greater herding tendency around bubbles.

Clusters of investors around initial public offering

“…Making an investment decision is a complex procedure because it is layered with different choices that are influenced by various market factors, investors' experiences, wealth and investors' stage of life. It is crucial to understand the characteristics of the underlying investor behaviour patterns because these, when combined with their behaviours, shape the dynamics of the whole market and thus are important factors in explaining the booms and bubbles in the financial markets (Ranganathan et al, 2018). Because investors seek higher returns, one possibility is to use social networks and other private information channels to follow other investors' strategies and to exploit privately channelled information in stock markets.…”

“…We follow this idea and use observations on investor-level transactions from shareholder registration data to identify the links between investors, here with a special focus on identifying investor clusters. Prior studies have investigated the structures of investor networks in different contexts (Ozsoylev et al, 2013;Tumminello et al, 2012;Gualdi et al, 2016;Musciotto et al, 2018;Ranganathan et al, 2018;Baltakys et al, 2018b), but investor clusters around IPOs have barely been explored.…”

“…So to avoid inconsistencies in the results, we eliminated nominee transactions from our analysis. This dataset has been also analysed and described in previous research (e.g., Ilmanen and Keloharju, 1999;Baltakys et al, 2018aBaltakys et al, , 2018bRanganathan et al, 2018;Siikanen et al, 2018).…”

Clusters of Investors Around Initial Public Offering

“…We follow this idea and use observations on investor-level transactions from shareholder registration data to identify the links between investors, here with a special focus on identifying investor clusters. Prior studies have investigated the structures of investor networks in different contexts [11,12,13,14,9,15], but investor clusters around IPOs have barely been explored.We address this research gap by performing a broad multistock exploratory analysis of investor clusters over 14 stocks in the first two years of their IPO. In particular, we seek to establish whether the identified investor clusters are persistent over the first two years of the IPOs and appear across multiple IPO securities, as well as with existing, mature stocks in the market.…”

“…We follow this idea and use observations on investor-level transactions from shareholder registration data to identify the links between investors, here with a special focus on identifying investor clusters. Prior studies have investigated the structures of investor networks in different contexts [11,12,13,14,9,15], but investor clusters around IPOs have barely been explored.…”