Abstract

http://ssrn.com/abstract=1586281
 
 

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Testing Jumps via False Discovery Rate Control


Yu-Min Yen


Institute of Economics, Academia Sinica

March 21, 2013

PLOS ONE, Forthcoming

Abstract:     
Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such situation becomes even worse when the jump occurrence is a rare event. To obtain more reliable results, we aim to control the false discovery rate (FDR), an efficient compound error measure for erroneous rejections in multiple testing problems. We perform the test via the Barndor -Nielsen and Shephard (BNS) test statistic, and control the FDR with the Benjamini and Hochberg (BH) procedure. We provide asymptotic results for the FDR control. From simulations, we examine relevant theoretical results and demonstrate the advantages of controlling the FDR. The hybrid approach is then applied to empirical analysis on two benchmark stock indices with high frequency data.

Number of Pages in PDF File: 42

Keywords: False Discovery Rate, BH procedure, BNS nonparametric jump Test

JEL Classification: C12, C14, G10

Accepted Paper Series





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Date posted: April 10, 2010 ; Last revised: March 22, 2013

Suggested Citation

Yen, Yu-Min, Testing Jumps via False Discovery Rate Control (March 21, 2013). PLOS ONE, Forthcoming. Available at SSRN: http://ssrn.com/abstract=1586281 or http://dx.doi.org/10.2139/ssrn.1586281

Contact Information

Yu-Min Yen (Contact Author)
Institute of Economics, Academia Sinica ( email )
128 Academia Road, Section 2
Nankang
Taipei, 115
Taiwan
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