Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/107926
Authors: 
Bibinger, Markus
Jirak, Moritz
Vetter, Mathias
Year of Publication: 
2015
Series/Report no.: 
SFB 649 Discussion Paper 2015-008
Abstract: 
This work develops change-point methods for statistics of high-frequency data. The main interest is the volatility of an Itô semi-martingale, which is discretely observed over a fixed time horizon. We construct a minimax-optimal test to discriminate different smoothness classes of the underlying stochastic volatility process. In a high-frequency framework we prove weak convergence of the test statistic under the hypothesis to an extreme value distribution. As a key example, under extremely mild smoothness assumptions on the stochastic volatility we thereby derive a consistent test for volatility jumps. A simulation study demonstrates the practical value in finite-sample applications.
Subjects: 
high-frequency data
nonparametric change-point test
minimax-optimal test
stochastic volatility
volatility jumps
JEL: 
C12
C14
Document Type: 
Working Paper

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