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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/71617


    Title: Testing Jumps via False Discovery Rate Control
    Authors: 顏佑銘
    Yen, Yu-Min
    Contributors: 國貿系
    Date: 2013-04
    Issue Date: 2014-11-24 14:17:02 (UTC+8)
    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 Barndorff-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.
    Relation: PloS One, 8, 58365
    Data Type: article
    DOI link: http://dx.doi.org/10.1371/journal.pone.0058365
    DOI: 10.1371/journal.pone.0058365
    Appears in Collections:[Department of International Business] Periodical Articles

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