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Vulnerable Asset Management? The Case of Mutual Funds

Fricke, D; Fricke, C; (2021) Vulnerable Asset Management? The Case of Mutual Funds. Journal of Financial Stability , 52 , Article 100800. 10.1016/j.jfs.2020.100800.

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Abstract

Is the asset management sector a source of financial instability? This paper develops a macroprudential stress test model which enables the quantification of systemic vulnerabilities due to fire sales in this sector. The model incorporates the flow-performance relationship as an additional funding shock in the model of Greenwood et al. (2015). Using data on US equity mutual funds for the period 2003–14, we quantify both fund-specific and system-wide (aggregate) vulnerabilities to fire sales over time. Our main finding is that the aggregate vulnerability, according to this propagation mechanism, is relatively small in comparison with values reported for banks. However, during periods of low market liquidity, the vulnerability of the system can become significant. Our paper also contributes to the ongoing discussion on the SIFI designation of Non-Bank Non-Insurer entities. For this purpose, we explore the determinants of individual funds’ vulnerability to systemic asset liquidations, highlighting the importance of size and portfolio illiquidity. Therefore, regulators should monitor structural vulnerabilities in the fund sector arising through liquidity transformation.

Type: Article
Title: Vulnerable Asset Management? The Case of Mutual Funds
DOI: 10.1016/j.jfs.2020.100800
Publisher version: https://doi.org/10.1016/j.jfs.2020.100800
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10088981
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