Data-Driven Jump Detection Thresholds for Application in Jump Regressions

35 Pages Posted: 25 Apr 2016

See all articles by Robert Davies

Robert Davies

Duke University, Department of Economics, Students

George Tauchen

Duke University - Economics Group

Date Written: September 17, 2015

Abstract

This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most likely to encounter that the usual in-fill asymptotics provide a poor guide for selecting the jump threshold. Because of this we develop a sample-based method. Our method estimates the number of jumps over a grid of thresholds and selects the optimal threshold at what we term the “take-off” point in the estimated number of jumps. We show that this method consistently estimates the jumps and their indices as the sampling interval goes to zero. In several Monte Carlo studies we evaluate the performance of our method based on its ability to accurately locate jumps and its ability to distinguish between true jumps and large diffusive moves. In one of these Monte Carlo studies we evaluate the performance of our method in a jump regression context. Finally, we apply our method in two empirical studies. In one we estimate the number of jumps and report the jump threshold our method selects for three commonly used market indices. In the other empirical application we perform a series of jump regressions using our method to select the jump threshold.

Keywords: efficient estimation, high-frequency data, jumps, semimartingale, specification test, stochastic volatility

JEL Classification: C51, C52, G12

Suggested Citation

Davies, Robert and Tauchen, George E., Data-Driven Jump Detection Thresholds for Application in Jump Regressions (September 17, 2015). Economic Research Initiatives at Duke (ERID) Working Paper No. 213, Available at SSRN: https://ssrn.com/abstract=2768899 or http://dx.doi.org/10.2139/ssrn.2768899

Robert Davies

Duke University, Department of Economics, Students ( email )

Durham, NC
United States

George E. Tauchen (Contact Author)

Duke University - Economics Group ( email )

Box 90097
221 Social Sciences
Durham, NC 27708-0097
United States
919-660-1812 (Phone)
919-684-8974 (Fax)

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
103
Abstract Views
845
Rank
469,855
PlumX Metrics