Heterogeneity and clustering of defaults. Issue 9 (2nd September 2021)

• Record Type: Journal Article
• Authors: Karlis, A. K.; Galanis, G.; Terovitis, S.; Turner, M. S.
• Is Part Of: Quantitative finance. Volume 21:Issue 9(2021)
• Page Start: 1533
• Page End: 1549
• Publication Date: 2021-09-02
• Subjects: Long memory -- Financial crises -- Hedge funds -- Survival statistics -- Bankruptcy; C22 -- G01 -- G23 -- G32 -- G33; Finance -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Investments -- Mathematics -- Periodicals; Economics -- Periodicals; Finances -- Modèles mathématiques -- Périodiques; 332.015118
• DOI: 10.1080/14697688.2021.1882686
• Languages: English
• ISSNs: 1469-7688

Abstract

Abstract : This paper studies how the degree of heterogeneity among hedge funds' demand orders for a risky asset affects the possibility of their defaults being clustered. We find that fire-sales caused by margin calls is a necessary, yet not a sufficient condition for defaults to be clustered. We show that when the degree of heterogeneity is sufficiently high, poorly performing HFs are able to obtain a higher than usual market share, which leads to an improvement of their performance. Consequently, their survival time is prolonged, increasing the probability of them remaining in operation until the downturn of the next leverage cycle. This leads to an increase in the probability of poorly and high-performing hedge funds to default in sync at a later time, and thus also in the probability of collective defaults. Our analytical results establish a connection between the nontrivial aggregate statistics and the presence of infinite memory in the process governing the hedge funds' defaults.