Performance Evaluation of Constrained Portfolios

Conventional performance evaluation methods strongly differentiate between the universe which is used for portfolio construction, and the universe which is used for the performance evaluation. Whilst by composing the portfolio we consider the complete opportunity set, in the last case we use a very restricted, general representation of this opportunity set: a peer group or (a) benchmark portfolio(s). In this thesis we present a conceptual framework, which allows to incorporate the decision-making context of any constrained investment portfolio into the performance evaluation process. The main feature that distinguishes our methodology from conventional performance evaluation methods is that it tackles the performance at the decision-making level: the portfolio weights. We consider all possible portfolios that can be constructed given the specific investment objective(s) as well as the prescribed investment constraints, and then evaluate all these portfolios according to (a) selected performance measure(s). The performance of the investment portfolio is calculated simultaneously and then evaluated against the performance of this complete opportunity set. Consequently, our methodology extends the conventional performance metrics with the insights into the performance of all opportunities that existed at the time of the investment decision.Igor Pouchkarev graduated with honors in Microprocessor techniques in Russia and then obtained the Master’s degree in Informatics and Computer Science (GPA 1.1) from the University of Saarbr¨ucken (Germany) in 1999. In May 2000 he joined ERIM Ph.D. program. Throughout his study he developed an interest in performance evaluation, portfolio and risk management, and asset & liability management. His work in these fields have been presented at international conferences and published in academic journals and books. During his Ph.D. studies he was affiliated with the Asset & Liability Management department of the United Bank of Switzerland in Z¨urich, Switzerland. In 1997-1999 he worked as a research assistant at the Max-Planck Institute for Computer Science, Algorithm and Complexity group, and in 1993-1997 developed software for business process re-engineering at the IDS Prof. Scheer AG in Saarbr¨ucken, Germany

A Relative View on Tracking Error

When delegating an investment decisions to a professional manager, investors often anchor their mandate to a specific benchmark. The manager’s exposure to risk is controlled by means of a tracking error volatility constraint. It depends on market conditions whether this constraint is easily met or violated. Moreover, the performance of the portfolio depends on market conditions. In this paper we argue that these mandated portfolios should not only be evaluated relative to their benchmarks in order to appraise their performance. They should also be evaluated relative to the opportunity set of all portfolios that can be formed under the same mandate – the portfolio opportunity set. The distribution of performance values over the portfolio opportunity set depends on contemporary market dynamics. To correct for this, we suggest a normalized version of the information ratio that is invariant to these market conditions

Portfolio Return Characteristics of Different Industries

Over the last decade we have witnessed the rise and fall of the so-called new economy stocks. One central question is to what extent these new firms differ from traditional firms. Empirical evidence suggests that stock returns are not normally distributed. In this article we investigate whether this also holds for portfolios of stocks from a growth industry. Furthermore, we will compare this type of portfolios with portfolios of stocks from a more traditional industry. Usually, only value weighted and equally weighted portfolios are used to describe and compare portfolio return characteristics. Instead, in our analysis, we use a novel approach in which we use an infinite number of portfolios that together represent the set of all feasible portfolio opportunities