Albano, Donatella (2016) Latent factor in Large-Dymensional datasets: forecasting and data analysis using factor models. An application to the insurance sector. [Tesi di dottorato]

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Item Type:	Tesi di dottorato
Lingua:	English
Title:	Latent factor in Large-Dymensional datasets: forecasting and data analysis using factor models. An application to the insurance sector
Creators:	Creators Email Albano, Donatella donaalb@gmail.com
Date:	31 March 2016
Number of Pages:	93
Institution:	Università degli Studi di Napoli Federico II
Department:	Scienze Economiche e Statistiche
Scuola di dottorato:	Scienze Economiche e Statistiche
Dottorato:	Scienze Economiche
Ciclo di dottorato:	27
Coordinatore del Corso di dottorato (extra):	nome email Acconcia, Antonio antonio.acconcia@unina.it
Tutor:	nome email Lippi, Marco UNSPECIFIED
Date:	31 March 2016
Number of Pages:	93
Uncontrolled Keywords:	factor models, insurance sector
Settori scientifico-disciplinari del MIUR:	Area 13 - Scienze economiche e statistiche > SECS-P/06 - Economia applicata
Date Deposited:	05 Dec 2016 10:36
Last Modified:	05 Dec 2016 10:36
URI:	http://www.fedoa.unina.it/id/eprint/11154
DOI:	10.6092/UNINA/FEDOA/11154

Abstract

The purpose of this thesis is to retrace the main steps that were taken in the evolution of the factor models and, in addition, to introduce two examples of how to apply the newest techniques developed in such fields to two different typologies of dataset, one traditional, meaning that it is composed mainly by macroeconomic and financial time series, and the other one 'new' which includes time series relevant to the Italian insurance sector and a set of macroeconomic and financial series related to them.

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