Multi-Factor-Asset Pricing Models for German Stocks


Book Description

The large number of asset pricing models and empirical studies of stock returns are evidence of the desire to understand the return generating process of financial assets in general and for stocks in particular. One focus of the research in this area has been on multi-factor asset pricing models [Chen et al. (1986), Fama/French (1992)]. These models are based on the assumption that stock returns are generated by a limited number of economic variables such as company, industry or macroeconomic factors.The objective of this study is to analyze the importance of various economic factors in explaining the return structure for stocks in Germany and to investigate whether the impact of these factors is time varying. This is important, because in most studies of asset pricing models it is assumed that the parameters are non time varying. In particular, we investigate the time variability of the explanatory power and the beta coefficients in a multi-factor framework. For this we employ a rolling estimation procedure that allows us to analyze the time variability of the model coefficients.In the empirical analysis we use monthly data of four macroeconomic variables and the market index to explain the returns of four German industry indices for the period from 1974 to 2000. In contrast to most studies which exclude banks from their empirical analysis we use three industrial indices and a bank index. The economic factors included in our model are term spreads, interest rates, exchange rates and the ifo business index as well as the market index. The empirical results confirm that the factors used in our empirical analysis seem well suited to explain the stock returns especially for banks. Moreover, it is evident that the explanatory power and the beta coefficients are time varying.




Asset Pricing Factor Models in the German Stock Market


Book Description

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.




On the Explanatory Power of the Capm and Multifactor Models on the German Stock Market


Book Description

Bachelor Thesis from the year 2018 in the subject Business economics - General, grade: 1,0, Justus-Liebig-University Giessen, language: English, abstract: The aim of this thesis is to apply the CAPM and the Fama-French model on the German stock market and to see whether the models hold or not. The research methodology in this thesis is mostly an empirical analysis and adopts the approach of Pamane et. al (2014) and Fama and French (1993). However, I will use a different data set and run the test for the CAPM on single stocks rather than on portfolios in order to avoid covariance problems. Firstly, we will calculate the security market line in a two-step regression and then evaluate the influence of non-linear factors and non-systematic risk factors. In addition, the effects of the financial crisis have to be taken into consideration which is why, dummy variables will be used. However, before we interpret the regression results, we make sure that the data are reliable in the first place and correct them if necessary. For the purpose of assessing the Fama-French model, however, we use a quite different approach and follow the original procedure that was used by Fama and French (1993) themselves. This involves classifying the stocks according to size and value and then building a total of four portfolios. Afterwards, returns are computed and regressed against size and value factors. Even though it is quite common to use, for instance, the DAX or the NASDAQ as proxies, I see the chance of facing endogeneity issues when explaining returns of stocks that are listed in the DAX, which is why I will run all tests for a second time but this time using the MDAX instead of DAX as the market portfolio in order to avoid endogeneity problems.




Testing the CAPM on the German Stock Market


Book Description

Seminar paper from the year 2005 in the subject Business economics - Investment and Finance, grade: 1,3, European Business School - International University Schlo Reichartshausen Oestrich-Winkel, course: Asset Management Seminar, 34 entries in the bibliography, language: English, abstract: Although the model is widely accepted and practically used as explained above, it is nevertheless far from being perfect as outlined in its record of empirical studies.9 Generally criticized is on the one hand that the underlying assumptions of the model are very theoretical and thus not able to illustrate reality and on the other one that there are problems in implementing well-founded tests of the model relating to the choice of the right market portfolio.10 But, the success of the CAPM will remain as long as there is no other model which offers as " ...] powerful and intuitively pleasing predictions about how to measure risk and the relation between risk and return."11 The objective of this study is to empirically test the CAPM on the German stock market. Since most of the empirical studies that have been made in the past focus on the U.S. stock market, this paper will try to find out if the results of these U.S. empirical studies can also be shown on the German stock market. Therefore, the goal of this paper is to analyze the relationship between risk and return on the German stock market to find out whether the CAPM holds.




Common risk factors in the German stock market


Book Description

Diploma Thesis from the year 2007 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 1,3, University of Tubingen, language: English, abstract: This paper develops a multifactor model for explaining the difference in average returns for the German stock market in the period between July 1990 and June 2007. The methodology of Fama and French (1993) is adopted to determine possible common risk factors in that market. Despite the enormous and strong stock markets movements and the high volatility during that period, the three factors RM-RF, SMB and HML seem to be able to capture cross-sectional variation in average returns for portfolios formed on various sorting criteria based on publicly available financial data. In addition, the analysis shows a negative (risk?) premium for small size stocks, which is a surprising result since it contradicts previous studies for the German, but also international markets. For stocks with a high book-to-market value, a strong positive premium is found. This value effect is consistent over time and statistically significant. Positive premiums seem to exist for high E/P and C/P stocks as well. These market anomalies show that returns are indeed predictable in the German market over long time horizons. High BM, E/P and C/P stocks do outperform stocks with low ratios in these categories significantly and consistent over time. However, the evidence in this analysis highlights that the common explanation in rational asset-pricing models of an outperformance due to some economic risk factors that are proxied by HML and SMB must be strongly questioned. Portfolios consisting of value stocks outperform growth portfolios in all possible states of the stock market. This evidence is contradictory to the ‘marginal value of wealth’ assumption in the rational asset pricing models presented. Additionally, there is a January effect in stock returns which cannot be captured by a risk-based, rational asset pricing model. Thus, the evidence suggests that it is in fact investor irrationality which is causing differences in average returns across stocks. RM-RF, SMB and HML can be described as common factors helping to explain return differences, but it is very likely that it is not underlying economic risk, but investor behavior which is causing the presented market anomalies and return predictability.




Value Stocks Beat Growth Stocks: An Empirical Analysis for the German Stock Market


Book Description

Based on a 'free of survivorship-bias' sample of German stocks listed at the Frankfurt stock exchange, the study investigates the ability of hedge portfolio formation structures, built of three value premium proxies (P/B, P/E, and DY), the size factor, and the technical momentum factor, to generate excess returns in the period 1992 to 2011. First, the author characterizes and defines the significant terms that are in connection with value and growth investing. He continues with the discussion of asset pricing with the CAPM, the Fama and French three-factor model, and the Carhart extension, and then describes the expected stock returns that are of capital importance. Moreover, the author deals with related studies for the German stock market. He gives a detailed description of the empirical analysis before he draws his conclusions. The author's purpose is to answer the following core questions: Is there a value premium in the German market between 1992 and 2011? Is there a reversed size premium like recent empirical findings suggest? Do high momentum stocks perform better than low momentum stocks? Is there a significant seasonal pattern in hedge portfolio returns? The combination of which factors best explains expected stock returns?




Evaluating Conditional Asset Pricing Models for the German Stock Market


Book Description

We study the performance of conditional asset pricing models in explaining the German cross-section of stock returns. Our test assets are portfolios sorted by size and book-to-market as in the paper by Fama and French (1993). Our results show that the empirical performance of the Capital Asset Pricing Model (CAPM) can be improved substantially when allowing for time-varying parameters of the stochastic discount factor. A conditional CAPM with the term spread as a conditioning variable is able to explain the cross-section of German stock returns about as well as the Fama-French model. Structural break tests do not indicate parameter instability of the model - whereas the reverse is found for the Fama-French model. Unconditional model specifications however do a better job than conditional ones at capturing time-series predictability of the test portfolio returns.







Bank Stock Returns and Economic Variables


Book Description

The large number of asset pricing models and empirical studies of stock returns are evidence of the desire to understand the return generating process of financial assets in general and for stocks in particular. One focus of the research in this area has been on multi-factor asset pricing models [Chen et al. (1986), Fama/French (1992)]. These models are based on the assumption that stock returns are generated by a limited number of economic variables such as company, industry or macroeconomic factors.The objective of this study is to analyze the importance of various economic factors in explaining the return structure for stocks in Germany and to investigate whether the impact of these factors is time varying. This is important, because in most studies of asset pricing models it is assumed that the parameters are non time varying. In particular, we investigate the time variability of the explanatory power and the beta coefficients in a multi-factor framework. For this we employ a rolling estimation procedure that allows us to analyze the time variability of the model coefficients.In the empirical analysis we use monthly data of four macroeconomic variables and the market index to explain the returns of four German industry indices for the period from 1974 to 2000. In contrast to most studies which exclude banks from their empirical analysis we use three industrial indices and a bank index. The economic factors included in our model are term spreads, interest rates, exchange rates and the ifo business index as well as the market index. The empirical results confirm that the factors used in our empirical analysis seem well suited to explain the stock returns especially for banks. Moreover, it is evident that the explanatory power and the beta coefficients are time varying.




Empirical Asset Pricing Models


Book Description

This book analyzes the verification of empirical asset pricing models when returns of securities are projected onto a set of presumed (or observed) factors. Particular emphasis is placed on the verification of essential factors and features for asset returns through model search approaches, in which non-diversifiability and statistical inferences are considered. The discussion reemphasizes the necessity of maintaining a dichotomy between the nondiversifiable pricing kernels and the individual components of stock returns when empirical asset pricing models are of interest. In particular, the model search approach (with this dichotomy emphasized) for empirical model selection of asset pricing is applied to discover the pricing kernels of asset returns.