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2011-01-03Diskussionspapier DOI: 10.18452/4293
Mean Volatility Regressions
dc.contributor.authorLin, Lu
dc.contributor.authorLi, Feng
dc.contributor.authorZhu, Lixing
dc.contributor.authorHärdle, Wolfgang Karl
dc.date.accessioned2017-06-16T00:16:35Z
dc.date.available2017-06-16T00:16:35Z
dc.date.created2011-04-15
dc.date.issued2011-01-03
dc.date.submitted2011-01-03
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4945
dc.description.abstractMotivated by increment process modeling for two correlated random and non-random systems from a discrete-time asset pricing with both risk free asset and risky security, we propose a class of semiparametric regressions for a combination of a non-random and a random system. Unlike classical regressions, mean regression functions in the new model contain variance components and the model variables are related to latent variables, for which certain economic interpretation can be made. The motivating example explains why the GARCH-M of which the mean function contains a variance component cannot cover the newly proposed models. Further, we show that statistical inference for the increment process cannot be simply dealt with by a two-step procedure working separately on the two involved systems although the increment process is a weighted sum of the two systems. We further investigate the asymptotic behaviors of estimation by using sophisticated nonparametric smoothing. Monte Carlo simulations are conducted to examine finite-sample performance, and a real dataset published in Almanac of China’s Finance and Banking (2004 and 2005) is analyzed for illustration about the increment process of wealth in financial market of China from 2003 to 2004.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectNon-random systemseng
dc.subjectRandom systemseng
dc.subjectSemiparametric regressioneng
dc.subjectVariance built-in Meaneng
dc.subject.ddc330 Wirtschaft
dc.titleMean Volatility Regressions
dc.typeworkingPaper
dc.identifier.urnurn:nbn:de:kobv:11-100185697
dc.identifier.doihttp://dx.doi.org/10.18452/4293
local.edoc.pages21
local.edoc.type-nameDiskussionspapier
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-year2012
dc.identifier.zdb2195055-6
bua.series.nameSonderforschungsbereich 649: Ökonomisches Risiko
bua.series.issuenumber2011,3

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