LO 69.10: Describe the objectives of performance measurement.

LO 69.10: Describe the objectives of performance measurement.
Performance measurement looks at a portfolio managers actual results and compares them to relevant comparables such as benchmarks and peer groups. Therefore, performance measurement seeks to determine whether a manager can consistently outperform (through excess returns) the benchmark on a risk-adjusted basis. Similarly, it seeks to determine whether a manager consistently outperforms its peer group on a risk-adjusted basis.
Furthermore, performance measurement may help to determine whether the returns achieved are commensurate with the risk taken. Finally, performance measurement provides a basis for identifying managers who are able to generate consistent excess risk-adjusted returns. Such superior processes and performance could be replicated on an on-going basis, thereby maximizing the entitys long-run returns and profitability.
Comparison of Performance with Expectations
>From a risk perspective (e.g., tracking error), portfolio managers should be assessed on the basis of being able to produce a portfolio with risk characteristics that are expected to approximate the target. In addition, they should also be assessed on their ability to actually achieve risk levels that are close to target.
>From a returns perspective (e.g., performance), portfolio managers could be assessed on their ability to earn excess returns.
Goldman Sachs Asset Management utilizes a so-called green zone to identify instances of actual tracking error or performance that are outside of normal expectations. An acceptable amount of deviation (from a statistical perspective) is determined, and any deviations up to that amount are considered a green zone event. Unusual events that are expected to occur with some regularity are considered yellow zone events. Truly unusual events that require immediate investigation are considered red zone events. In using this simple color-coded system, the various zones are predefined and provide clear expectations for the portfolio managers. The movements of portfolios into yellow or red zones are triggering events that require further investigation and discussion.
Return Attribution
The source of returns can be attributed to specific factors or securities. For example, it is important to ensure that returns result from decisions where the manager intended to take risk and not simply from sheer luck.
Variance analysis is used to illustrate the contribution to overall portfolio performance by each security. The securities can be regrouped in various ways to conduct analysis by industry, sector, and country, for example.
In performing return attribution, factor risk analysis and factor attribution could be used. Alternatively, risk forecasting and attribution at the security level could also be used.
2018 Kaplan, Inc.
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Topic 69 Cross Reference to GARP Assigned Reading – Litterman, Chapter 17
Sharpe and Information Ratio
The Sharpe ratio is calculated by taking the portfolios actual return and subtracting the risk-free rate in the numerator. The denominator is the portfolios standard deviation. The information ratio is calculated by taking the portfolios excess returns and subtracting the benchmarks excess returns (if applicable) in the numerator. The denominator is the portfolios tracking error. These two measures are both considered risk-adj usted return measures.
Strengths of these metrics include the following: (1) easy to use as a measure of relative performance compared to a benchmark or peer group; (2) easy to determine if the manager has generated sufficient excess returns in relation to the amount of risk taken; and (3) easy to apply to industrial sectors and countries.
Weaknesses of these metrics include the following: (1) insufficient data available to perform calculations; and (2) the use of realized risk (instead of potential risk) may result in overstated performance calculations.
Comparisons with Benchmark Portfolios and Peer Groups