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.
| Original language | English |
|---|---|
| Article number | 129 |
| Number of pages | 14 |
| Journal | Palgrave Communications |
| Volume | 5 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Dec 2019 |
| Publication type | A1 Journal article-refereed |
Funding
MB and KB are grateful for the grants received from the Finnish Foundation for Share Promotion, The Foundation for Advancement of Finnish Securities Market and Finnish Foundation for Technology Promotion. KB received funding from the EU Research and Innovation Programme Horizon 2020 under grant agreement no. 675044 (BigDataFi-nance) and from the doctoral school of Tampere University. FL and DP acknowledge partial support from the European Community H2020 Programme under the scheme INFRAIA-1-2014-2015: Research Infrastructures, grant agreement No. 654024 SoBig-Data: Social Mining and Big Data Ecosystem (http://www.sobigdata.eu). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Keywords
- investor networks
- IPO
- investor clusters
- SVN
- institutional herding
Publication forum classification
- Publication forum level 1
ASJC Scopus subject areas
- General Arts and Humanities
- General Social Sciences
- General Psychology
- Economics, Econometrics and Finance(all)