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A Venturi Effect Can Help Cure Our Trees
Published on: October 1, 2013
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Dynamics of investor spanning trees around dot-com bubble.
Sindhuja Ranganathan1, Mikko Kivelä2, Juho Kanniainen1
1Laboratory of Industrial and Information Management/Tampere University of Technology, Tampere, Finland.
Plos One
|June 14, 2018
Summary
Household investors exhibit stronger herding behavior during market bubbles, as indicated by their stock trading networks. Their network measures reacted to the dot-com bubble
Area of Science:
- Financial economics
- Network analysis
- Behavioral finance
Background:
- Understanding investor behavior during market bubbles is crucial for financial stability.
- Temporal investor networks offer insights into collective trading patterns.
Purpose of the Study:
- To identify temporal investor networks for Nokia stock using net-volume correlations.
- To analyze network changes around the dot-com bubble for different investor types.
- To assess investor herding tendencies during market booms and crises.
Main Methods:
- Constructing temporal networks from correlations in investor-specific net-volumes.
- Analyzing spanning tree measures (maximum and minimum) of these networks.
- Segmenting analysis by investor type: households, financial institutions, and non-financial institutions.
Main Results:
- Household investor networks showed clear reactions to the dot-com bubble.
- Maximum spanning tree measures for households increased during the bull market.
- Minimum spanning tree measures for households anticipated the bubble's burst.
- Financial and non-financial institutions displayed less distinct network reactions.
Conclusions:
- Household investors demonstrate a greater herding tendency compared to institutional investors during market bubbles.
- Temporal network analysis can reveal distinct investor behaviors around market events.
- Minimum spanning tree measures may serve as leading indicators for market bubble bursts.
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