Альфа немецкого паевого фонда. Надежный или сомнительный финансовый показатель
This paper analyses the relationship of benchmark picking behaviour of fund managers regarding German domiciled equity mutual funds and the corresponding alpha. Previous studies have shown that average mutual funds underperform the market and do not generate positive risk-adjusted returns (Reuter & Guercio, 2011). However, the benchmark picking behaviour of managers can significantly impact the risk-adjusted return and therefore explain better performance than actually achieved with a different benchmark. Studies from the Norwegian mutual funds alpha have shown that strategic benchmark picking behaviour of managers lead to an alpha with higher risk-adjusted returns (Bukhvalova, 2017). Conversely, this paper comes to the conclusion that equity funds domiciled in Germany have on average 0.7886% higher best-fit-alpha performance than fund manager selected alpha. Therefore, this paper concludes that fund managers in Germany do not choose benchmarks in order to expose better alpha performance.
1. Introduction………………………………………………………………………………………………………..1
1.1 Funds ………………………………………………………………………………………………………………………2
1.2 Benchmark……………………………………………………………………………………………………………….3
1.3 Important Fund Types ………………………………………………………………………………………………..4
1.3.1 Mutual Funds…………………………………………………………………………………………………………………………….. 4 1.3.2 ETF (Exchange Traded Funds)………………………………………………………………………………………………………. 5 1.3.3 Hedge Funds ……………………………………………………………………………………………………………………………… 5
1.4 CAPM………………………………………………………………………………………………………………………6 1.5 Alpha ………………………………………………………………………………………………………………………7 1.6 R-Squared ………………………………………………………………………………………………………………..7
2. Literature Review…………………………………………………………………………………………………9
3. Methods and Data Description……………………………………………………………………………..17
3.1 Data………………………………………………………………………………………………………………………17
3.1.1 Equity Funds and Benchmarks …………………………………………………………………………………………………… 17 3.1.2 Risk-Free Rate ………………………………………………………………………………………………………………………….. 18
3.2 Methodology ………………………………………………………………………………………………………….19
3.2.1 Best-fit-alpha …………………………………………………………………………………………………………………………… 19 3.2.2 Managers alpha ……………………………………………………………………………………………………………………….. 19 3.2.3 Approach ………………………………………………………………………………………………………………………………… 19
4. Results and Analysis……………………………………………………………………………………………22
4.1 Benchmark……………………………………………………………………………………………………………..22 4.2 Equity funds alpha……………………………………………………………………………………………………23
4.2.1 Results long-term …………………………………………………………………………………………………………………….. 23
4.3 Validity ………………………………………………………………………………………………………………….25
4.3.1 Internal Validity ……………………………………………………………………………………………………………………….. 25 4.3.2 External Validity……………………………………………………………………………………………………………………….. 25 4.3.3 Measurement ………………………………………………………………………………………………………………………….. 26
4.4 Reliability……………………………………………………………………………………………………………….26
5. Discussion and Suggestions for further studies ………………………………………………………..28
5.1 Managerial Implications ……………………………………………………………………………………………30
6. Conclusion ………………………………………………………………………………………………………..31
Bibliography ………………………………………………………………………………………………………… 32 Appendix …………………………………………………………………………………………………………….. 35 Declaration of Authorship……………………………………………………………………………………….48
In academic literature the volume of mutual funds research papers is large and has a wide range of profound analysis. This is not surprising, as for example the US market of mutual funds gathered more than 88 million shareholders and over 11 trillion dollars in assets 9 years ago (Fink, 2011). Not only the US market is highly attractive because of its volume and liquidity, but also different markets around the world have developed their own mutual fund industry. The German one is not as big as the US market. However, equity mutual funds domiciled in Germany have different jurisdictions from funds in the US and therefore every investor has to review their due diligence by themselves in order to invest into the German market. Studies by Wayne Ferson and Jerchern Lin (Ferson & Lin, 2014) have shown that alpha is not the most important indicator whether to buy a fund or not. Therefore, other indicators certainly also influence the fund picking behaviour of investors. Furthermore, studies have also shown that mutual funds have the tendency to outperform the market and not as many investor falsely assume of mutual funds underperformance to the US market according to studies by Frahm (Frahm & Huber, 2019) and Del Guercio (Del Guercio & Reuter, 2011). This in mind, the research done in this paper provides essential knowledge for the industry and especially for individual investors considering purchasing equity mutual funds domiciled in Germany.
The research goal of this master thesis is to determine whether there is a relationship between mutual fund managers benchmark picking behaviour and higher alpha values compared to benchmarks which are chosen through financial econometrics. Whether we are talking about individuals or corporations, this paper tries to provide transparency for the mutual funds market. This is the research gap this thesis tries to close in order to have additional information to choose an appropriate and risk specific asset for investors.
Furthermore, the goal is not only to give investors, but also asset managers and wealth managers, an insight in the industry they operate in. Fundamental data about competitors and the industry will certainly represent reliable data to stakeholders in the German mutual fund market. Therefore,
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this paper claims the following research hypothesis, which is going to be proved using financial econometrical approaches:
German mutual equity funds manager alpha is on average higher than the best-fit-alpha ∗.
This in mind, taking the Modern Portfolio Theory (Markowitz, 1952) into consideration, an investor can invest their assets more efficiently in the German equity market with the results presented in this paper. If the hypothesis is true, investors might take the expected return and variance into consideration while choosing a mutual fund, rather than alpha for decision making investments. The impact of the results on the industry should mainly provide data to individual investors and protect them from misleading information.
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