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Percorrer por autor "Amado, Cristina"

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  • Modelling dynamic interdependence in nonstationary variances with an application to carbon markets
    Publication . Campos-Martins, Susana; Amado, Cristina
    In this paper we propose a multivariate generalisation of the multiplicative decomposition of the volatility within the class of conditional correlation GARCH models. The GARCH variance equations are multiplicatively decomposed into a deterministic nonstationary component describing the long-run movements in volatility and a short-run dynamic component allowing for volatility interactions across markets or assets. The conditional correlations are assumed to be time-invariant in its simplest form or generalised into a flexible dynamic parameterisation. Parameters of the model are estimated equation-by-equation by maximum likelihood applying the maximisation by parts algorithm to the variance equations, and thereafter to the structure of conditional correlations. An empirical application using carbon markets data illustrates the usefulness of the model. Our results suggest that, after modelling the variance equations accordingly, we find evidence that the transmission mechanism of shocks is supported by the presence of dynamic interdependence in variances robust to nonstationarity.
    2025-04Artigo de investigação Acesso embargado Ver mais
  • Modelling time-varying volatility interactions
    Publication . Campos-Martins, Susana; Amado, Cristina
    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.
    2026-03-01Artigo de investigação Acesso aberto Ver mais