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Testing Causality Between Two Vectors in Multivariate GARCH Models

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  • Tomasz Wozniak
Abstract
Spillover and contagion effects have gained significant interest in the recent years of financial crisis. Attention has not only been directed to relations between returns of financial variables, but to spillovers in risk as well. I use the family of Constant Conditional Correlation GARCH models to model the risk associated with financial time series and to make inferences about Granger causal relations between second conditional moments. The restrictions for second-order Granger noncausality between two vectors of variables are derived. To assess the credibility of the noncausality hypotheses, I employ posterior odds ratios. This Bayesian method constitutes an alternative for classical tests that makes such testing possible, regardless of the form of the restrictions on the parameters of the model. Moreover, it relaxes the assumptions about the existence of higher-order moments of the processes required in classical tests. In the empirical example, I find that the pound-to-Euro exchange rate second-order causes the US dollar-to-Euro exchange rate, which confirms the meteor shower hypothesis of Engle, Ito & Lin (1990).

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  • Tomasz Wozniak, 2012. "Testing Causality Between Two Vectors in Multivariate GARCH Models," Economics Working Papers ECO2012/20, European University Institute.
    • Handle: RePEc:eui:euiwps:eco2012/20
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    1. This Week's Reading
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2013-04-13 03:35:00

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    Cited by:

    1. Rituparna Sen & Anandamayee Majumdar & Shubhangi Sikaria, 2022. "Bayesian Testing of Granger Causality in Functional Time Series," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 191-210, September.
    2. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    3. Matthieu Droumaguet & Tomasz Wozniak, 2012. "Bayesian Testing of Granger Causality in Markov-Switching VARs," Economics Working Papers ECO2012/06, European University Institute.
    4. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    5. Tomasz Woźniak, 2018. "Granger-causal analysis of GARCH models: A Bayesian approach," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 325-346, April.
    6. Pedersen, Rasmus Søndergaard, 2017. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Journal of Econometrics, Elsevier, vol. 196(1), pages 23-36.

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    More about this item

    Keywords

    Second-Order Causality; Volatility Spillovers; Posterior Odds; GARCH Models;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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