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.
List of Contents
1. Introduction
2. Fundamental theory and previous discoveries
2.1 Relative classification of the German stock market in an international context
2.2 The Evolution of Factor Models
2.3 Model accuracy and empirical evidence of factor models
2.4 Empirical significance of the established factors
2.5 Global and Germany specific return anomalies
3. Structural analysis of the German stock market
3.1 Basic characteristics and statistics
3.2 Factor spanning tests
3.3 Analysis of 3 x 3 sorting
3.4 Analysis of 2 x 2 x2 sorting
4. Analysis of anomalies in the German stock market
4.1 Descriptive statistics and significance of prominent anomalies
4.2 Multifactor regressions of prominent anomalies
4.3 Out-of-sample analysis of the net payout yield anomaly
5. Sector analysis of the German stock market
5.1 Descriptive statistics of sectors
5.2 Multifactor regressions for relevant sectors
5.3 Rolling window regressions of two relevant sectors
6. Fonds analysis of the German stock market
6.1 Descriptive statistics of active and passive managed fonds
6.2 Multifactor regressions of six representative fonds
6.3 Out-of-sample analysis of six representative fonds
7. Conclusion
Research Objective and Scope
This thesis examines the performance of modern multifactor asset pricing models within the German stock market. It aims to determine whether internationally recognized factor models—such as the Carhart four-factor, Fama-French five- and six-factor, q-factor, and Stambaugh-Yuan mispricing models—possess explanatory power for German equity returns, anomalies, sectors, and managed funds.
- Performance evaluation of diverse multifactor models in the German context.
- Empirical investigation of structural market characteristics and return anomalies.
- Comparative analysis of factor spanning tests and sorting methods.
- Assessment of sector-specific and equity fund performance using regression analysis.
Excerpt from the Book
2.2 The Evolution of Factor Models
In order to answer the overarching research question: "How do internationally proven factor models perform for the German stock market?", we first need to get an overview of the fundamental principles of factor models. A short dive into the evolution of factor models at this point will help us to go deeper into this area than just knowing the model structure. Based on the portfolio theory of (Markowitz, 1952), independent of each other (Sharpe, 1964), (Lintner, 1965) and (Mossin, 1966) developed the Capital Asset Pricing Model, abb. CAPM, which definitively marked a milestone in the history of economics and was crowned with the award of the Nobel Prize in Economic Sciences in 1990. This model is the fundament of many other models, especially the factor models, which are thematically based on the CAPM.
How close to reality these assumptions are in relation to the stock market can certainly be discussed controversially, but ultimately it is in the nature of modeling to make assumptions and to break down complex interconnections in a sensible way. The reader's first impulse, probably raises the criticism that assumptions five to nine in particular do not hold for the stock market. Even if this criticism seems to be justified, it remains to be said that the stock market even comes relatively close to these assumptions if one compares, for example, liquidity or information equality with other markets, such as the real estate market. Furthermore, there is also a temporal component to consider. Increasing digitalization, especially in recent years, has also made it possible, for example, to trade fractional shares, and also to massively reduce transaction costs due to online brokers.
Summary of Chapters
1. Introduction: This chapter introduces the overarching research question regarding the performance of modern asset pricing models in the German stock market and outlines the methodological approach.
2. Fundamental theory and previous discoveries: This section covers the theoretical foundations of factor models, starting from the CAPM, and discusses existing empirical evidence and identified return anomalies.
3. Structural analysis of the German stock market: This chapter provides an initial structural characterization of the German market, including factor spanning tests and various sorting techniques.
4. Analysis of anomalies in the German stock market: This section investigates a wide range of return anomalies to test their significance and explanatory power within the German equity market.
5. Sector analysis of the German stock market: This chapter analyzes industry-specific returns and performs multifactor regressions to evaluate sector performance and stability.
6. Fonds analysis of the German stock market: This final analytical chapter tests the applicability of factor models to actively and passively managed investment funds.
7. Conclusion: This chapter summarizes the empirical findings and answers the overarching research question, highlighting the versatility of the six-factor model.
Keywords
Asset Pricing, Factor Models, German Stock Market, Multifactor Models, Market Anomalies, Carhart Model, Fama-French Five-Factor Model, Six-Factor Model, q-Factor Model, Mispricing Factor Model, Equity Funds, Sector Analysis, Portfolio Theory, Systematic Risk, Empirical Finance.
Frequently Asked Questions
What is the primary objective of this thesis?
The research aims to evaluate how various internationally established multifactor asset pricing models perform when applied specifically to the German stock market.
Which specific asset pricing models are analyzed?
The study investigates the Carhart four-factor model, the Fama-French five- and six-factor models, the q-factor model by Hou et al., and the mispricing factor model by Stambaugh and Yuan.
What methodology is employed to test these models?
The paper utilizes various analytical methods including factor spanning tests, descriptive statistics, multifactor regressions of return anomalies, and rolling window regressions.
What constitutes the thematic core of the research?
The core focus involves structural market analysis, return anomalies, industrial sector performance, and the explanatory power of these models regarding actively and passively managed funds.
How is the German stock market contextualized?
The study first classifies the German market within an international context, comparing its size, industry composition, and ownership structure to major global markets like the U.S.
What are the primary findings regarding the models' performance?
The study finds that while no single model is universally superior, the six-factor model is generally considered the most versatile across the tested scenarios.
Does the size factor perform differently in Germany compared to international findings?
Yes, the study identifies evidence of an inverted size effect for the German stock market, which contrasts with standard international findings.
How does the study handle the impact of market crises?
The research utilizes rolling window regressions and specific sub-period correlation analyses (expansion vs. contraction) to observe how factor loadings change during volatile periods, such as the 2008 financial crisis.
- Quote paper
- B.A. Julian Fischer (Author), 2021, Asset Pricing Factor Models in the German Stock Market, Munich, GRIN Verlag, https://www.grin.com/document/1023138
