Crowded trades by similarly trading peers influence the dynamics of asset prices, possibly creating systemic risk. We propose a market clustering measure using granular trading data. For each stock, the clustering measure captures the degree of trading overlap among any two investors in that stock, based on a comparison with the expected crowding in a null model where trades are maximally random while still respecting the empirical heterogeneity of both stocks and investors. We investigate the effect of crowded trades on stock price stability and present evidence that market clustering has a causal effect on the properties of the tails of the stock return distribution, particularly the positive tail, even after controlling for commonly considered risk drivers. Reduced investor pool diversity could thus negatively affect stock price stability.
Crowded Trades, Market Clustering, and Price Instability
Marc van Kralingen,D. Garlaschelli,K. Scholtus,I. V. Lelyveld
Published 2020 in Entropy
ABSTRACT
PUBLICATION RECORD
- Publication year
2020
- Venue
Entropy
- Publication date
2020-02-04
- Fields of study
Medicine, Computer Science, Economics
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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