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Levy density estimation via information projection onto wavelet subspaces

Authors
Song, Seongjoo
Issue Date
1-Nov-2010
Publisher
ELSEVIER SCIENCE BV
Keywords
Levy processes; Density estimation; Information projection
Citation
STATISTICS & PROBABILITY LETTERS, v.80, no.21-22, pp.1623 - 1632
Indexed
SCIE
SCOPUS
Journal Title
STATISTICS & PROBABILITY LETTERS
Volume
80
Number
21-22
Start Page
1623
End Page
1632
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/115350
DOI
10.1016/j.spl.2010.07.001
ISSN
0167-7152
Abstract
This paper proposes a nonparametric method for producing smooth and positive estimates of the density of a Levy process, which is widely used in mathematical finance. We use the method of logwavelet density estimation to estimate the Levy density with discretely sampled observations. Since Levy densities are not necessarily probability densities, we introduce a divergence measure similar to Kullback-Leibler information to measure the difference between two Levy densities. Rates of convergence are established over Besov spaces. (C) 2010 Elsevier B.V. All rights reserved.
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College of Political Science & Economics (Department of Statistics)
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