Nonstationary factor model applications of Elastic Net

buir.advisorYiğit, Taner
dc.contributor.authorKonak, Deniz
dc.date.accessioned2016-01-08T18:19:36Z
dc.date.available2016-01-08T18:19:36Z
dc.date.issued2013
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionIncludes bibliographical refences.en_US
dc.description.abstractIn this thesis, we adopted Elastic Net estimators for selecting true number of factors in factor models with stationary and nonstationary factors. Elastic Net is a member of shrinkage estimators family. As a member of shrinkage estimators family, elastic net estimators are stable to changes in data and in general they do not over parametrize the models. These two properties of elastic net estimators makes elastic net more favourable than information based criterion penalty methods for estimating true factor number. Since Principal Components Analysis (PCA) based algorithms always tends to give only single factor for nonstationary data sets, we use Sparse Principal Components Analysis (SPCA) algorithm which is a regression-type optimization formulation of PCA. Simulations show the performance of Elastic Net estimator for estimation of true factor number with stationary and nonstationary factors cases .en_US
dc.description.statementofresponsibilityKonak, Denizen_US
dc.format.extentvi, 30 leaves, graphsen_US
dc.identifier.urihttp://hdl.handle.net/11693/15505
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectElastic Neten_US
dc.subjectSparse Principal Component Analysisen_US
dc.subjectNonstationary Factor Modelsen_US
dc.subjectTrue Factor Number Estimationen_US
dc.subject.lccHG106 .K65 2013en_US
dc.subject.lcshFinance--Mathematical models.en_US
dc.subject.lcshEstimation theory.en_US
dc.subject.lcshPrincipal component analysis.en_US
dc.subject.lcshRegression analysis.en_US
dc.titleNonstationary factor model applications of Elastic Neten_US
dc.typeThesisen_US
thesis.degree.disciplineEconomics
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMA (Master of Arts)

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