Modeling Multivariate Time Series with Fractional Integration in Macroeconomics and Finance

URN to cite this document:: urn:nbn:de:bvb:355-epub-365401
DOI to cite this document:: 10.5283/epub.36540

Weigand, Roland

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Date of publication of this fulltext: 20 Aug 2018 06:27

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Item type:	Thesis of the University of Regensburg (PhD)
Date:	January 2018
Referee:	Prof. Dr. Rolf Tschernig and Prof. Dr. Enzo Weber
Date of exam:	17 July 2014
Institutions:	Business, Economics and Information Systems > Institut für Volkswirtschaftslehre und Ökonometrie > Lehrstuhl für Ökonometrie (Prof. Dr. Rolf Tschernig) Business, Economics and Information Systems > Institut für Volkswirtschaftslehre und Ökonometrie > Lehrstuhl für Empirische Wirtschaftsforschung, insbesondere Makroökonomie und Arbeitsmarkt (Prof. Dr. Enzo Weber)
Keywords:	Structural vector autoregression, long-run restriction, finite-horizon identification, fractional integration, impulse response function, long memory, misspecification, fractional cointegration, state space, unobserved components, factor model, realized covariance matrix, dynamic correlation, semiparametric estimation, density forecasting
Dewey Decimal Classification:	300 Social sciences > 310 General statistics 300 Social sciences > 330 Economics
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Partially
Item ID:	36540

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Abstract (English)

The dissertation covers four essays on multivariate time series modeling. Different long memory specifications are proposed and applied both in the context of structural macroeconomic models and for forecasting the risk of multiple financial assets. A new transformation-based approach is discussed for modeling realized covariance matrices.

Translation of the abstract (German)

Die Dissertation umfasst vier Aufsätze zur multivariaten Zeitreihenanalyse. Verschiedene Modellspezifikationen mit langem Gedächtnis werden vorgeschlagen und im Kontext struktureller makroökonomischer Modelle sowie zur Prognose von Risiken mehrerer Anlagegüter angewandt. Ein neuer transformationsbasierter Ansatz wird zur Modellierung realisierter Kovarianzmatrizen herangezogen.

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