Expected Returns in the Time Series and Cross Section: Empirical Evidence on Multifactor Asset Pricing Models and their Applications
- Do expected asset returns vary through time? Why do some assets exhibit higher average returns than others? How can factors that drive expected returns in the time series be linked to factors that explain the cross-sectional dispersion in average returns? How do these findings affect applications? These questions are so essential that Eugene Fama, Lars Peter Hansen, and Robert Shiller received the 2013 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for their empirical methods and applied work aimed at answering them. This thesis seeks to provide small but important contributions to these questions by investigating the time-series predictability of commodity futures returns through various factors, by testing various multifactor asset pricing models in the cross section of European stocks, and by examining whether these models are qualified to estimate the cost of equity capital of European industries.
Author: | Fabian Lutzenberger |
---|---|
URN: | urn:nbn:de:bvb:384-opus4-30360 |
Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/3036 |
Advisor: | Andreas W. Rathgeber |
Type: | Doctoral Thesis |
Language: | English |
Publishing Institution: | Universität Augsburg |
Granting Institution: | Universität Augsburg, Mathematisch-Naturwissenschaftlich-Technische Fakultät |
Date of final exam: | 2014/10/27 |
Release Date: | 2015/06/30 |
Tag: | asset pricing; predictability of returns; multifactor models; predictive regressions; cost of equity capital |
GND-Keyword: | Kapitalmarktforschung; Kapitalmarkttheorie; Kapitalmarkteffizienz; Capital-Asset-Pricing-Modell; Warentermingeschäft; Internationaler Vergleich |
Note: | Universität Augsburg, Dissertation, 2014 |
Institutes: | Mathematisch-Naturwissenschaftlich-Technische Fakultät |
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management | |
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management / Professur für Applied Data Analysis | |
Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Licence (German): | Deutsches Urheberrecht mit Print on Demand |