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Comparison of univariate and multivariate Granger causality in international asset pricing. Evidence from Finnish and Japanese financial economies

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  • Ralf Ostermark
  • Jaana Aaltonen

Abstract

The study compares multivariate and univariate tests of causality in a rolling framework in testing whether the Japanese stock market 'causes' the Finnish cash and derivatives markets in the Granger sense. The multivariate algorithm generates the time pattern of causality of the underlying vector process. Significant causality is observed at distinct time intervals within the sample period, possibly during periods of regime switches, trend changes or major global disturbances. The multivariate causality is then decomposed into four univariate causality tests. The effect of each univariate causality pattern on the multivariate causality is tested by a recursive least squares regression (RLS) method.

Suggested Citation

  • Ralf Ostermark & Jaana Aaltonen, 1999. "Comparison of univariate and multivariate Granger causality in international asset pricing. Evidence from Finnish and Japanese financial economies," Applied Financial Economics, Taylor & Francis Journals, vol. 9(2), pages 155-165.
    • Handle: RePEc:taf:apfiec:v:9:y:1999:i:2:p:155-165
    DOI: 10.1080/096031099332410
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    References listed on IDEAS

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    1. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
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    Cited by:

    1. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
    2. Grosche, Stephanie, 2012. "Limitations of Granger Causality Analysis to assess the price effects from the financialization of agricultural commodity markets under bounded rationality," Discussion Papers 121868, University of Bonn, Institute for Food and Resource Economics.
    3. R. Scott Hacker & Abdulnasser Hatemi-J, 2006. "Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application," Applied Economics, Taylor & Francis Journals, vol. 38(13), pages 1489-1500.

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