Applications of dynamic factor models in pricing equities, bonds and measuring monetary policy shocks
Başlık çevirisi mevcut değil.
- Tez No: 400832
- Danışmanlar: DR. ZACHARIAS PSARADAKIS, DR. STEPHAN SATCHELL
- Tez Türü: Doktora
- Konular: Ekonomi, Economics
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2010
- Dil: İngilizce
- Üniversite: University of London - Birkbeck
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 232
Özet
Özet yok.
Özet (Çeviri)
This dissertation presents new empirical applications of dynamic factor models to different asset markets and introduces a new framework for testing the level of integration within the European Monetary Union countries. The level of integration is tested using identified monetary policy shocks, which is based on recent methodological advances on structural analysis and forecasting. Estimated factor models, which mostly have a dynamic nature, are used for forecasting purposes, and different factor models are compared with respect to their forecasting performance and the size of the pricing errors. In this framework, first we use a new application of a latent multi-factor model, utilising the Fama-French industry based equity return dataset to estimate a static and dynamic factor model. While doing so, we use Bayesian inference to estimate models and employ different number of factors. The reason for using a dynamic setup and different number of factors is to observe if there is an improvement in model performance with the usage of dynamic setup over static setup. Although there appears to be a significant improvement when we use a dynamic model, including factors more than one does not contribute much to model performance. Model performance is measured within the framework of pricing errors and forecasting performance of the models that are estimated. Second, we apply a state space algorithm and estimate a model for utility sector bond yields that aims to improve the modelling performance of most commonly used cross sectional Fama-French regressions. In this respect, dynamic and time-varying implied factor returns have been modelled and we observe that, with the usage of new methodology there is considerable improvement over cross sectional Fama-French regressions. The estimation results clearly illustrate that, benefits of applying a dynamic time-varying setup for estimating bond yields are significant. To accomplish the new modelling setup, special bond price dataset of utilities industry have been used. Third, we model welfare fluctuations and monetary policy shocks of countries of the European Monetary Union, using the most common Structural Vector Autoregression (SVAR) procedure. To examine the degree of integration among the European Monetary Union countries, we use identified monetary policy shocks that we extract from SVAR and examine their common factor with a Bayesian dynamic factor model, that is similar to the one estimated while explaining industry portfolio returns in the first part of this thesis.
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