Optimal time-varying tail risk network with a rolling window approach

Xingmin Zhang and Shuai Zhang

Physica A: Statistical Mechanics and its Applications, 2021, vol. 580, issue C

Abstract: We contribute to the literature on financial network contagion and systemic risk by developing a time-varying framework based on the rolling window technic and high dimensional quantile regression. The new selection criterion enables us to determine the optimal rolling width, which trades off the estimation accuracy and time variation of the tail risk network. Monte Carlo simulations show that our procedure significantly improves upon the estimation performance of the time-varying model. Using Chinese banking’s market data over 2009–2019, we measure the time-varying tail risk connectedness among banks using idiosyncratic returns. We find strong evidence of prominent risk dependence across banks during the stock crash. The network model using the optimal rolling window outperforms the traditional approaches in capturing structural changes.

Keywords: Rolling window selection; Time-varying network model; Decomposition; Systemic risk; Bi-objective optimization (search for similar items in EconPapers)
JEL-codes: C22 C61 G2 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:580:y:2021:i:c:s0378437121004003

DOI: 10.1016/j.physa.2021.126127

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