Common Risk Factors In The German Stock Market

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

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.

Master's Thesis from the year 2012 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 1,0, University of Bamberg, language: English, abstract: Based on a sample of German stocks listed at the Frankfurt stock exchange, the study investigated 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. The P/B hedge portfolio yields an average return of 1.59 percent per month, the P/E hedge portfolio 0.664 percent, and a portfolio formation approach ranked on DY delivers a return of 0.839. The results of multivariate regressions favor the Fama-French three-factor model in order to explain expected stock returns.

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.

Inhaltsangabe:Introduction: Measuring performance of fund managers is a topic equally interesting to practitioners and researchers. Most common performance measures rely on the assumption of constant risk during the entire evaluation period. The measure of risk is the beta from the Capital Asset Pricing Model (CAPM). In order to better assess a manager s investment ability, additional factors could be employed to capture the different sources of risk. The manager owes each portion of the achieved return to a certain risk factor. The risks a manager is running can be summed up to form his personal benchmark, which thus reflects the investment style. Still, the exposures to the included risk factors are assumed to be constant. The dynamics of the capital markets had not been captured by the prevailing performance measures before an approach that controlled for varying economic conditions was suggested. Models that are based on this approach deliver a beta conditional on the market state. The manager s exposure to the risk of the own benchmark was thus allowed to vary in time. Consequently, the search for indicators of the market states was launched and a model framework which could accommodate the chosen indicators as part of the benchmark had to be chosen. Two model frameworks emerged and a couple of indicators established themselves as standard. This study largely follows the approach of Ferson and Schadt. They introduced a linear model that can be perceived as a conditional version of the CAPM. The aim of this study is not only to obtain performance measures which result from the conditional models. Since the variation in the exposure to market risk is accounted for, one who employs conditional models gains insight into fund manager s trading. If the trading is reflected in changes of the beta, then inference on fund strategy is made possible even though information on the portfolio structure is not provided. The explanatory power of a conditional model depends on the researcher selecting a representative benchmark for the funds in the sample and indicators of economic conditions that fund managers rely on in reality. The structure of this paper is the following: chapter 2 builds the theoretical foundation of conditional models and presents their two forms; chapter 3 relates this study to previous literature in the area; chapter 4 employs conditional models to evaluate strategies and performance of German fund managers; chapter 5 sums up the [...]

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?

Victor Silverio Posadas Hernandez explores three sets of questions: What are the investment laws in the Latin American emerging markets (LAEM) and how do they compare to those of developed countries? How heterogeneous are the implicit trading costs in the LAEM and which factors are responsible for the heterogeneity? How does the predictability of stock returns in the LAEM differ from those documented for developed markets?