Work

Modelling time-varying volatility interactions

Year: 2026

Type: article

Abstract: We propose an additive time-varying (or partially time-varying) multivariate model of volatility, where a time-dependent component is added to the extended vector GARCH process for modelling the dynamics of volatility interactions. Volatility co-dependence is allowed to change smoothly between two extreme states, and second-moment interdependence is identified through these structural changes. The estimation of the new time-varying vector GARCH process is simplified using an equation-by-equation estimator for the volatility equations in the first step and estimating the correlation matrix in the second step. A new Lagrange multiplier test is derived for testing the null hypothesis of constant volatility co-dependence against a smoothly time-varying interdependence between financial markets. Monte Carlo experiments show that the test statistic has satisfactory finite-sample properties. An empirical application to sovereign bond yields illustrates the modelling strategy and the usefulness of the new specification.

Source: International Review of Financial Analysis

DOI: 10.1016/j.irfa.2026.105098

Authors: Susana Campos-Martins, Cristina Amado

Institutions: Universidade Católica Portuguesa, University of Minho

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,770

Funders: Ministério da Educação e Ciência, Programa Operacional Temático Factores de Competitividade, Fundação para a Ciência e a Tecnologia, European Regional Development Fund