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A test for volatility spillover with application to exchange rates

机译:波动溢出测试,适用于汇率

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摘要

This paper proposes a class of asymptotic N(0, 1) tests for volatility spillover between two time series that exhibit conditional heteroskedasticity and may have infinite unconditional variances. The tests are based on a weighted sum of squared sample cross-correlations between two squared standardized residuals. We allow to use all the sample cross-correlations, and introduce a flexible weighting scheme for the sample cross-correlation at each lag. Cheung and Ng (1996) test and Granger (1969)-typeregression-based test can be viewed as uniform weighting because they give equal weighting to each lag. Non-uniform weighting often gives better power than uniform weighting, as is illustrated in a simulation study. We apply the new tests to study Granger-causalities between two weekly nominal U.S. dollar exchange rates--Deutschemark and Japanese yen. It is found that for causality in mean, there exists only simultaneous interaction between the two exchange rates. For causality in variance, there alsoexists strong simultaneous interaction between them. Moreover, a change in past Deutschemark volatility Granger-causes a change in current Japanese yen volatility, but a change in past Japanese yen volatility does not Granger-cause a change in current Deutschemark volatility.
机译:针对存在时间异方差且可能具有无限无条件方差的两个时间序列之间的波动性溢出,本文提出了一类渐近N(0,1)检验。该测试基于两个平方标准化残差之间的平方样本互相关的加权和。我们允许使用所有样本互相关,并为每个滞后的样本互相关引入灵活的加权方案。 Cheung and Ng(1996)检验和Granger(1969)型回归检验可以看作是均匀加权,因为它们对每个滞后都赋予相同的加权。仿真研究表明,非均匀加权通常比均匀加权具有更好的功效。我们应用新的测试来研究每周两次美元名义汇率(德国马克和日元)之间的格兰杰因果关系。结果发现,对于均值的因果关系,两种汇率之间仅存在同时的相互作用。对于因果差异,它们之间也存在强烈的同时互动。此外,过去的德国马克波动率格兰杰的变化导致当前日元汇率的变化,但是过去的日元汇率波动不变化的格兰杰导致当前的日元汇率的变化。

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