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An Information Filtering approach to stress testing: an application to FTSE markets

Seabrook, Isobel; Caccioli, Fabio; Aste, Tomaso; (2021) An Information Filtering approach to stress testing: an application to FTSE markets. ArXiv Green open access

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Abstract

We present a novel methodology to quantify the "impact" of and "response" to market shocks. We apply shocks to a group of stocks in a part of the market, and we quantify the effects in terms of average losses on another part of the market using a sparse probabilistic elliptical model for the multivariate return distribution of the whole market. Sparsity is introduced with an L0-norm regularization, which forces to zero some elements of the inverse covariance according to a dependency structure inferred from an information filtering network. Our study concerns the FTSE 100 and 250 markets and analyzes impact and response to shocks both applied to and received from individual stocks and group of stocks. We observe that the shock pattern is related to the structure of the network associated with the sparse structure of the inverse covariance of stock returns. Central sectors appear more likely to be affected by shocks, and stocks with a large level of underlying diversification have a larger impact on the rest of the market when experiencing shocks. By analyzing the system during times of crisis and comparative market calmness, we observe changes in the shock patterns with a convergent behavior in times of crisis.

Type: Working / discussion paper
Title: An Information Filtering approach to stress testing: an application to FTSE markets
Open access status: An open access version is available from UCL Discovery
Publisher version: https://doi.org/10.48550/arXiv.2106.08778
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.
Keywords: q-fin.RM, q-fin.RM, q-fin.CP
UCL classification: UCL
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/10161358
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