Statistical networks with applications in economics and finance

dc.contributorWang, Patrick P.
dc.contributorWang, James L.
dc.contributorChen, Yuhui
dc.contributorPorter, Michael D.
dc.contributor.advisorSong, Song
dc.contributor.authorAlli, Toyin Omolara
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2017-03-01T17:41:52Z
dc.date.available2017-03-01T17:41:52Z
dc.date.issued2016
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractDue to the vast amount of economic and financial information to be stored and analyzed, the need for the study of high dimensional networks has increased dramatically. Typical approaches for determining the groupwise information to infer statistical networks include lasso and large covariance matrix estimation regularizations. We investigate the application of the nodewise lasso algorithm to U.S. economic and financial data over the past 50 years. We use the nodewise lasso to estimate statistical networks of varying sparsity levels to describe the conditional dependence structure of a dataset consisting of 131 U.S. macroeconomic time series. With these estimated networks, we describe how they can be chosen from and interpreted in the context of both the statistical literature and the existing economic theory to enlarge our knowledge of economic and financial network structure. In particular, we focus on four key categories of economic indicators: housing starts, employment, consumer price index, and interest rates. For example, in a statistical network determined by the nodewise lasso, edges are found between nodes representing housing starts and nodes representing employment, industrial production, and interest rates. The housing starts nodewise lasso results, along with many others, are consistent with existing conclusions found in the study of economics and finance.en_US
dc.format.extent58 p.
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otheru0015_0000001_0002278
dc.identifier.otherAlli_alatus_0004D_12524
dc.identifier.urihttps://ir.ua.edu/handle/123456789/2622
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectMathematics
dc.subjectStatistics
dc.titleStatistical networks with applications in economics and financeen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Mathematics
etdms.degree.disciplineMathematics
etdms.degree.grantorThe University of Alabama
etdms.degree.leveldoctoral
etdms.degree.namePh.D.
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