Here is a chapter from Portfolio Performance Measurement and Benchmarking, which will help you create a system you can use to accurately measure your performance. The authors highlight common mechanical problems involved in building benchmarks and clearly illustrate the resulting fallouts. The failure to choose the right investing performance benchmarks often leads to bad decisions or inaction and, inevitably, lost profits. In this book you will discover a foundation for benchmark construction and discuss methods for all different asset classes and investment styles.

Peter Lückoff investigates why fund flows and manager changes act as equilibrium mechanisms and drive the performance of both previously outperforming and previously underperforming funds back to average levels.

This authoritative book enables readers to evaluate the various performance and risk attributes of mutual funds, while also serving as a comprehensive resource for students, academics, and general investors alike. Avoiding the less useful descriptive approach to fund selection, this book employs a balanced approach including both technique and application. The chapters combine clear summaries of existing research with practical guidelines for mutual fund analysis. Enables readers to analyze mutual funds by evaluating a fund's various performance and risk attributes. Includes templates, which provide an efficient, sound approach to fund analysis, interpretation of results, buy/sell decisions, and the timing of decisions. Combines clear summaries of existing research with practical guidelines for mutual fund analysis.

The multidimensional nature of mutual fund performance makes it a very attractive application area for Data Envelopment Analysis. The strength of this technique lies in the following attribute: its ability to handle multiple inputs and outputs, that it does not require the specification of a functional form for input-output correspondence, and that it gives a single measure of performance which takes into account the multiple dimensions of organizational activity. The goal of this work is to validate the hypothesis that DEA may be used as a tool for creating better investment portfolios while serving as a management efficiency benchmark. Production models based on the DEA methodology, with the aim of capturing the essence of fund performance, were developed to generate efficiency scores for the majority of Canadian mutual funds, in order to classify the funds into portfolios. (Abstract shortened by UMI.).