Abstract
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.
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Shimizu, Y. Threshold selection in jump-discriminant filter for discretely observed jump processes. Stat Methods Appl 19, 355–378 (2010). https://doi.org/10.1007/s10260-010-0134-z
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DOI: https://doi.org/10.1007/s10260-010-0134-z
Keywords
- Threshold estimation
- Jump-discriminant filter
- Integrated-volatility
- Asymptotic unbiasedness
- Plug-in method