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A causality-in-variance test and its application to financial market prices. (English) Zbl 0842.62095

Summary: This paper develops a test for causality in variance. The test is based on the residual cross-correlation function (CCF) and is robust to distributional assumptions. Asymptotic normal and asymptotic \(\chi^2\) statistics are derived under the null hypothesis of no causality in variance. Monte Carlo results indicate that the proposed CCF test has good empirical size and power properties. Two empirical examples illustrate that the causality test yields useful information on the temporal dynamics and interaction between two time series.

MSC:

62P20 Applications of statistics to economics
91B28 Finance etc. (MSC2000)
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