Asset Pricing Factor Models in the German Stock Market
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Sprache:Englisch
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Erscheinungsdatum
14.06.2021
Verlag
GRINSeitenzahl
109 (Printausgabe)
Dateigröße
5237 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9783346420091
Master's Thesis from the year 2021 in the subject Business economics - Investment and Finance, grade: 1,7, University of Hannover (Institut für Finanzwirtschaft und Rohstoffmärkte), language: English, abstract: In this paper, we examine how various modern multifactor models, such as the Carhart factor model, five-factor model and its complement six-factor model by Fama and French, the q-factor model by Hou, Wue and Zhang, and the mispricing factor model by Stambaugh and Yuan perform in the German stock market. It is discernible that, depending on the application model, like factor spanning tests, different sortings, return anomalies, sector- and equity fund investigation, they often provide quite similar explanatory power, while in individual cases sometimes one and sometimes the other model performs better. The underlying factors contribute differently to the explanatory power depending on the time period. Thus, in case of doubt, the six-factor model is preferable, as it is the most versatile model.
Since the establishment of the capital asset pricing model as a cornerstone of modern capital market theory in the 1960s, new investigations and studies have been built on this model on an ongoing basis. This continuously leads to extensions and modifications of the asset pricing models since then. These models can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. These can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. In this paper, we aim to answer the overarching research question of how modern asset pricing models perform for the German stock market. For this purpose, we first discuss the characteristics of the German stock market, followed by the milestones of the development of factor models, their empirical evidence and their factors, as well as internationally known return anomalies. In the subsequent part, five modern asset pricing models are tested in different scenarios of the German stock market, including factor spanning tests, different sortings, anomalies, sectors and in equity funds. For this purpose, various analytical methods are used and performed with the software "Stata". Finally, the comprehensive results are summarized and concluded.
Since the establishment of the capital asset pricing model as a cornerstone of modern capital market theory in the 1960s, new investigations and studies have been built on this model on an ongoing basis. This continuously leads to extensions and modifications of the asset pricing models since then. These models can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. These can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. In this paper, we aim to answer the overarching research question of how modern asset pricing models perform for the German stock market. For this purpose, we first discuss the characteristics of the German stock market, followed by the milestones of the development of factor models, their empirical evidence and their factors, as well as internationally known return anomalies. In the subsequent part, five modern asset pricing models are tested in different scenarios of the German stock market, including factor spanning tests, different sortings, anomalies, sectors and in equity funds. For this purpose, various analytical methods are used and performed with the software "Stata". Finally, the comprehensive results are summarized and concluded.
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