Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/87335 
Year of Publication: 
2013
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 13-155/III
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
In this article we introduce a new class of test statistics designed to detect the occurrence of abnormal observations. It derives from the joint distribution of moment- and quantile-based estimators of power variation sigma, under the assumption of a normal distribution for the underlying data. Our novel tests can be applied to test for jumps and are found to be generally more powerful than widely used alternatives. An extensive empirical illustration for high-frequency equity data suggests that jumps can be more prevalent than inferred from existing tests on the second or third moment of the data.
Subjects: 
Finite activity jumps
higher order moments
order statistics
outliers
realized variation.
JEL: 
C10
C12
G12
Document Type: 
Working Paper

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