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Modelling causality in nonstationary variances with an application to carbon markets

Author

Listed:
  • Susana Campos-Martins

    (NIPE/Center for Research in Economics and Management, University of Minho; and Católica Lisbon School of Business & Economics)

  • Cristina Amado

    (NIPE/Center for Research in Economics and Management, University of Minho, Portugal)

Abstract

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 spillover effects 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 persists which is supported by the presence of variance interactions robust to nonstationarity.

Suggested Citation

  • Susana Campos-Martins & Cristina Amado, 2023. "Modelling causality in nonstationary variances with an application to carbon markets," NIPE Working Papers 13/2023, NIPE - Universidade do Minho.
    • Handle: RePEc:nip:nipewp:13/2023
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    File URL: https://repositorium.sdum.uminho.pt/handle/1822/87581
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    References listed on IDEAS

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    1. Annastiina Silvennoinen & Timo Ter�svirta, 2015. "Modeling Conditional Correlations of Asset Returns: A Smooth Transition Approach," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 174-197, February.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Variance interactions; Nonstationarity; Short- and long-term volatility; Lagrange multiplier test.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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