Abstract
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.
Original language | English |
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Article number | 336 |
Pages (from-to) | 1-29 |
Number of pages | 29 |
Journal | Entropy |
Volume | 23 |
Issue number | 3 |
Early online date | 12 Mar 2021 |
DOIs | |
Publication status | Published - Mar 2021 |
Bibliographical note
Funding Information:D.G. acknowledges support from the Dutch Econophysics Foundation (Stichting Econo-physics, Leiden, the Netherlands), and the EU project SoBigData++ (Grant No. 871042).
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Funding
D.G. acknowledges support from the Dutch Econophysics Foundation (Stichting Econo-physics, Leiden, the Netherlands), and the EU project SoBigData++ (Grant No. 871042).
Funders | Funder number |
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European Commission | |
Dutch Econophysics Foundation | |
Horizon 2020 Framework Programme | 871042 |
Keywords
- Crowded trading
- Entropy
- Financial stability
- Tail-risk