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2010
ACM

Threshold selection in jump-discriminant filter for discretely observed jump processes

8 years 6 months ago
Threshold selection in jump-discriminant filter for discretely observed jump processes
Threshold estimation is one of the useful techniques in the inference for jump-type stochastic processes from discrete observations. In this method, a jump-discriminant filter is used to infer the continuous part and the jump part separately. Although there are several choices for the filter, statistics constructed via filters are often sensitive to the choice. This paper presents some numerical procedures for selecting a suitable filter based on observations. Key words: threshold estimation; jump-discriminant filter; integrated-volatility, asymptotic unbiasedness, plug-in method. MSC2000: 62M09; 62P05.
Yasutaka Shimizu
Added 21 May 2011
Updated 21 May 2011
Type Journal
Year 2010
Where SMA
Authors Yasutaka Shimizu
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