Portfolio Performance Evaluation

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2024 Curriculum CFA Program Level III Portfolio Management and Wealth Planning

Introduction

Performance evaluation is one of the most critical areas of investment analysis. Performance results can be used to assess the quality of the investment approach and suggest changes that might improve it. They are also used to communicate the results of the investment process to other stakeholders and may even be used to compensate the investment managers. Therefore, it is of vital importance that practitioners who use these analyses understand how the results are generated. By gaining an understanding of the details of how these analyses work, practitioners will develop a greater understanding of the insights that might be gathered from the analysis and will also be cognizant of the limitations of those approaches, careful not to infer more than what is explicit or logically implicit in the results.

We will first consider the broad categories of performance measurement, attribution, and appraisal, differentiating between the three and explaining their interrelationships. Next, we will provide practitioners with tools to evaluate the effectiveness of those analyses as we summarize various approaches to performance evaluation. We will cover returns-based, holdings-based, and transactions-based attribution, addressing the merits and shortcomings of each approach and providing guidance on how to properly interpret attribution results. Again, by reviewing how each approach generates its results, we reveal strengths and weaknesses of the individual attribution approaches.

Next, we will turn to the subject of benchmarks and performance appraisal ratios. We will review the long-standing tests of benchmark quality and differentiate market indexes from benchmarks. We will also review different ratios used in performance appraisal, considering the benefits and limitations of each approach.

Lastly, we will provide advice on using these tools to collectively evaluate the skill of investment managers. This advice relies heavily on understanding the analysis tools, the limitations of the approaches, the importance of data to the quality of the analysis, and the pitfalls to avoid when making recommendations.

Learning Outcomes

The member should be able to:

  1. explain the following components of portfolio evaluation and their interrelationships: performance measurement, performance attribution, and performance appraisal;
  2. describe attributes of an effective attribution process;
  3. distinguish between return attribution and risk attribution and between macro and micro return attribution;
  4. describe returns-based, holdings-based, and transactions-based performance attribution, including advantages and disadvantages of each;
  5. interpret the sources of portfolio returns using a specified attribution approach;
  6. interpret the output from fixed-income attribution analyses;
  7. discuss considerations in selecting a risk attribution approach;
  8. distinguish between investment results attributable to the asset owner versus those attributable to the investment manager;
  9. discuss uses of liability-based benchmarks;
  10. describe types of asset-based benchmarks;
  11. discuss tests of benchmark quality;
  12. describe problems that arise in benchmarking alternative investments;
  13. describe the impact of benchmark misspecification on attribution and appraisal analysis;
  14. calculate and interpret the Sortino ratio, the appraisal ratio, upside/downside capture ratios, maximum drawdown, and drawdown duration;
  15. describe limitations of appraisal measures and related metrics;
  16. evaluate the skill of an investment manager.

Summary

Performance evaluation is an essential tool for understanding the quality of the investment process. Practitioners must take care, however, to understand how performance results are generated. They need a good understanding of the performance methods used, the data inputs, and the limitations of those methods. They particularly need to be careful not to infer results beyond the capabilities of the methods or the accuracy of the data. In this reading, we have discussed the following: