Financial markets are as complex as ever due to an accelerating development in the last decades. Especially evaluations of mutual fund performance have been a subject of interest since the introduction of financial services.
In this thesis, a study on the performance of mutual funds investing in German equity from July 1995 to June 2015 is conducted. The aim is to find out if fund managers have sufficient skill to generate risk adjusted return in order to cover the cost imposed on the investors. Another purpose is to provide investors with relevant results. Inter alia, Jensen one-factor, Fama and French three-factor and the Carhart four-factor model are used as different benchmark models for performance. Paired bootstrap simulations suggest that, net of cost, a small fraction of fund managers do have sufficient skill to cover cost. For the bottom ranked funds, there is statistical evidence that their poor performance is caused by bad management, rather than by bad luck. The results for gross returns show that there is an unneglectable fraction of fund managers with good performance not due to luck. Compared to net returns, there is stronger evidence of skill, negative as well as positive. Form an investor’s point of view it seems rather beneficial to invest in passively managed vehicles. High costs eat into the return, and they are the main reason why the majority of actively managed funds end up with sub-par performance.
Table of Contents
1 Introduction
2 Theoretical Framework
2.1 The Arithmetic of Active Management
2.2 Information Efficiency of Financial Markets
2.3 Factor Models
3 Previous Empirical Findings
4 Method
4.1 Factor Creation
4.2 Data
4.3 Forming the Dataset and Limitations
4.4 Approach
4.5 Separating Skill from Luck
4.6 Summary Statistics
5 Empirical Results
5.1 Net Returns
5.2 Gross Returns
5. 3 Beating Individual Benchmarks
6 Critical Review
7 Conclusions
Appendix A: CAPM Bootstrap Simulations
Appendix B: R – Code
Objectives & Core Topics
The primary objective of this thesis is to empirically investigate whether active mutual fund managers in the German equity market possess genuine investment skill to generate risk-adjusted abnormal excess returns, or if their performance is merely a result of luck. The study evaluates performance from July 1995 to June 2015 using various benchmark models, including the CAPM, the Fama and French three-factor model, and the Carhart four-factor model, while applying bootstrap simulations to distinguish between skill and luck.
- Analysis of fund manager skill vs. luck in the German equity market.
- Application of multifactor models (CAPM, Fama-French, Carhart) to evaluate performance.
- Use of bootstrap simulations to robustly assess abnormal returns.
- Comparison of net and gross fund returns to account for management fees and costs.
Excerpt from the Book
2.1 The Arithmetic of Active Management
In 1991, William Sharpe came up with the framework of equilibrium accounting or as he called it: “the arithmetic of active management”, a constraint on the returns on active investing: The average return of an active management will always be equal to the average return of a comparable passive management. At least gross returns on an actively managed investment will be equal to that of a passive managed investment. The net returns, after costs, on an average actively managed investment are less than the return on a passively managed investment. According to Sharpe, this framework must hold at any point in time whilst only being dependent on the laws of addition, subtraction, multiplication and division.
Since a passive investment is tracking a certain market, each passive investor will receive exactly the market return before cost. Such an investor is holding a so-called cap-weighted market portfolio. Active management, in contrast, provides the chance for individual investors to add value but only at the expense of other active investors. “The arithmetic of equilibrium accounting then implies that the deviations from cap weights in one active investor's portfolio must be absorbed by other active investors who take offsetting positions.” That implies a zero sum game. Individual active managers may still generate positive abnormal returns, but only at expense of other active investors. Unfortunately, there are costs to be considered when talking about active management. Hence, net of charges the active portfolio management can be described as a negative sum game.
Summary of Chapters
1 Introduction: Defines the research motivation and the debate between active and passive management in the context of German equity funds.
2 Theoretical Framework: Outlines the theoretical foundations including market efficiency, equilibrium accounting, and the specific factor models used for benchmarking.
3 Previous Empirical Findings: Reviews existing literature and studies on mutual fund performance and bootstrap methodologies.
4 Method: Details the creation of risk factors, dataset construction, limitations, and the specific bootstrap approach used to separate skill from luck.
5 Empirical Results: Presents the analysis of net and gross returns and the effectiveness of managers against individual benchmarks.
6 Critical Review: Discusses methodological limitations, data quality issues, and potential biases in the empirical analysis.
7 Conclusions: Summarizes the findings, concluding that most active management performance is driven by luck and that investors are generally better served by passive investment strategies.
Keywords
fund performance, active, passive, German equity funds, fund management, luck, skill, bootstrapping, Fama and French, Carhart, factor model, CAPM, OLS regression
Frequently Asked Questions
What is the fundamental research question of this thesis?
The thesis investigates whether active mutual fund managers in the German market have sufficient skill to consistently generate risk-adjusted returns that cover the costs imposed on investors, or if their performance is driven by luck.
Which benchmark models are primarily used for performance evaluation?
The study employs the Capital Asset Pricing Model (CAPM), the Fama and French three-factor model, and the Carhart four-factor model.
Why are bootstrap simulations utilized in this analysis?
Bootstrap simulations are used to separate real manager skill from luck by creating a "luck distribution" of t-statistics, allowing for a more robust inference of outperformance than standard regression models alone.
How is the distinction between net and gross returns handled?
Net returns represent what the investor receives, while gross returns are calculated by adding the management fee back to the net returns to isolate the fund manager's gross performance before costs.
What is the "arithmetic of active management" as defined by William Sharpe?
It is a theoretical framework stating that the average return of active management must equal the average return of passive management before costs, implying that active management is a zero-sum game before costs and a negative-sum game after fees.
What are the primary findings regarding the skill of active fund managers in Germany?
The results show weak evidence of genuine manager skill in aggregate. While some top-tier funds demonstrate skill, the majority of active funds underperform their benchmarks after accounting for costs, suggesting passive vehicles are more beneficial for the average investor.
How does the study address the problem of autocorrelation and heteroscedasticity?
The author uses Newey-West (HAC) standard errors within the R programming language to correct for these econometric issues, ensuring that the calculated t-statistics are reliable.
Does the momentum factor (MOM) provide significant explanatory power for German fund returns?
The empirical results suggest that the momentum factor has little to no significant exposure for the analyzed sample of German equity funds, rendering it largely irrelevant for this specific dataset.
- Citation du texte
- Carsten Fritz (Auteur), 2016, Empirical Analysis of Mutual Funds investing in German Equity (1995-2015), Munich, GRIN Verlag, https://www.grin.com/document/342479
