Quantifying impact and response in markets using information filtering networks

Seabrook, Isobel, Caccioli, Fabio and Aste, Tomaso (2022) Quantifying impact and response in markets using information filtering networks. Journal of Physics: Complexity, 3 (2). ISSN 2632-072X

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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 log-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.

Item Type:	Article
Official URL:	https://iopscience.iop.org/journal/2632-072X
Additional Information:	© 2022 The Authors
Divisions:	Systemic Risk Centre
Subjects:	H Social Sciences > HG Finance
Date Deposited:	08 Jun 2022 08:48
Last Modified:	16 Nov 2024 19:06
URI:	http://eprints.lse.ac.uk/id/eprint/115308

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