The idea of comparing the performance of different risky investments, for example investment funds, on a quantitative basis dates back to the beginnings of the asset management industry and has been an important field of research in finance since then. Performance measures serve as valuable quantitative evidence for the portfolio manager's performance as well as for the evaluation of investment decisions ex post. Based on the idea of the capital asset pricing model proposed by Treynor, Sharpe and Lintner, Treynor developed the first quantitative performance measure intended to rate mutual funds, the Treynor Ratio. Since then, a large number of performance measures with very different characteristics have been developed. In addition to their power of rating investments ex post, their ability to predict future performance has been thoroughly analyzed by Grinblatt & Titman, Brown & Goetzmann, Carhart and others. Besides academia, the driving force behind the development of more sophisticated performance measures has always been the investors. This is understandable, as the truly poor managers are afraid, the unlucky managers will be unjustly condemned, and the new managers have no track record. Only the skilled (or lucky) managers are enthusiastic. By combining and applying the results of previous research to a new sample of nearly 10,000 mutual funds that invest in different countries and asset classes, this thesis clarifies its central research question: Is the Information Ratio a useful and reliable performance measure? In order to answer this central question, it has been split up into the following sub-parts: What are the characteristics of a useful and reliable performance measure? What actually is good performance? Is the good performance a result of luck or of skilled decisions and does it persist over time? How does the Information Ratio compare to other performance measures, and what are its strengths and weaknesses? This empirical study aims at answering all of these questions and provides a framework for performance evaluation by use of the Information Ratio.

Text Sample: Chapter 4.3, The Art of Selecting the Benchmark: The selection and allocation of benchmarks for this study (cf. Table 2), which are used to calculate the Information Ratios, has mostly been done based on popularity of the indices and their ability to cover the price development of a certain market. In fund management companies, the selection of a benchmark usually is the result of intense negotiations between the fund manager and the investors, as the benchmark has a major impact on the alpha of the fund and on the influences of specific investment restrictions. Depending on style and country focus, one benchmark might be more favorable to the fund manager than another. Therefore, it is necessary and important to analyze the sensitivity of the Information Ratio toward the selected benchmark within this paper. Lehmann & Modest have shown that benchmark selection does have a very strong influence on the resulting alphas as well as their volatility. While the Standard & Poor’s 500 Index has been used throughout this paper in connection with Equity US funds, two additional indices, the equally-weighted Dow Jones Industrial Average and the market-weighted Russell 1000 Index, will be introduced to compare the resulting Information Ratios. The Dow Jones Industrial Average is based on a basket of 30 large cap, industrial companies in the US. It has been quoted since 1896 and has a strong focus on manufacturers of industrial and consumer goods. The Russell 1000 Index is a proxy for the large cap segment of the US equity market and is based on the 1,000 largest companies in terms of market value. The Russell 1000 covers about 92% of the US equity market, has been calculated since 1984, and is in direct competition with the S&P 500. Figure 8 illustrates the development of the three indices over the 11-year observation period. It can be seen that the indices move very similarly. However, all of them emphasize different market segments and show a different behavior in certain periods. After having calculated three different Information Ratios (based on the S&P 500, the Dow Jones Industrial Average, and the Russell 1000) for all Equity US funds from 1998 to 2008, the threshold values between the first 25% of the funds and the second 25% of the funds have been calculated again. This threshold value separates the first quartile and the second quartile, that is very good” funds from good” to poor” funds. The result is charted in Figure 9. It can be recognized that the Information Ratios based on the S&P 500 and the Russell 1000 are closely related, while the Information Ratios based on the Dow Jones Industrial Average behave differently and are far more volatile. It seems that the Dow Jones Industrial Average does not cover the investment universe of the Equity US funds very well. This can be due to the fact that this index is only based on 30 companies. Differences that seemed to be little at first glance in Figure 8 had a major impact on the threshold values of the Information Ratios as presented in Figure 9. The difference of the threshold values has been tested for significance using the Wilcoxon signed-rank test. This test has been used, because all three sets of Information Ratios are not normally distributed according to the Lilliefors test and are assumed to be dependent on each other. The z-values of the Wilcoxon test are presented in Table 8, and significantly different values are flagged with an asterisk. Firstly, the Information Ratios based on the Dow Jones Industrial Average index were tested against those based on the S&P 500 index. Secondly, the Information Ratios based on the Russell 1000 index were also tested against those based on the S&P 500 index. To conclude, while some threshold values are quite close, all are significantly different from those based on the S&P 500 using a 5% level of significance. These results are in line with Goodwin, who also found that the selection of the benchmark has a strong influence on the resulting Information Ratios. The results are confirmed when looking at the rankings based on the three different Information Ratios as illustrated in both scatter plots of Figure 10. While there are noticeable differences between Information Ratios based on the Dow Jones Industrial Average and those based on the S&P 500, the changes in rankings when using the Russell 1000 versus the S&P 500 are quite small. The selection of an appropriate benchmark is, therefore, an important step during performance analyses in general. Still, the results can only provide very limited guidance as to how to select the right benchmark. One can, however, conclude that benchmark indices that cover a large part of the investment universe of the specific fund category (for example, the Russell 1000 or S&P 500) are superior to indices that are only based on a few securities and certain industry sectors (for example, the Dow Jones Industrial Average). It should also be noted that the Dow Jones Industrial Average has been criticized for its equal weighting of stocks, lack of revision of its constituents following changes in the market environment, and a missing framework that describes admission criteria. The final decision for or against a benchmark should always be based on the experience of the performance evaluator.

• Performance Measurement

• Information Ratio

• Fundamental Law of Active Management

• Performance Analysis

• Portfolio Manager

Christoph Schneider, Jahrgang 1984, hat einen Master of Science in Finance Abschluss der European Business School, Oestrich-Winkel. Während der Studienzeit an der European Business School spezialisierte er sich insbesondere in den Themen Finance, Investments und Real Estate und absolvierte Auslandssemester in Oslo, Norwegen und San Francisco, USA. Er ist derzeit bei Morgan Stanley International im Investment Banking tätig.