Reading 31 Evaluating Portfolio Performance Flashcards
Risk-Adjusted Performance Appraisal Measures
Three risk-adjusted performance appraisal measures have become widely used:
- ex post alpha (also known as Jensen’s alpha),
- the Treynor measure (also known as reward-to-volatility or excess return to nondiversifiable risk), and
- the Sharpe ratio (also known as reward-to-variability).
Another measure, M2, has also received some acceptance.
Manager Continuation Policy as a Filter
Two types of decision errors may occur:
- Type I error—keeping (or hiring) managers with zero value-added. (Rejecting the null hypothesis when it is correct.)
- Type II error—firing (or not hiring) managers with positive value-added. (Not rejecting the null hypothesis when it is incorrect.)
A coarse filter will be conducive to Type I errors. Conversely, a fine filter will lead the sponsor to commit more Type II errors.
If in truth the manager has no skill and we reject the null hypothesis because the manager’s value-added returns fall outside of the confidence band (particularly, in this case, on the upside), then we have committed a Type I error. Conversely, if the manager is indeed skillful yet we fail to reject the null hypothesis because the manager’s value-added returns fall inside the confidence band, then we have committed a Type II error.
Both Type I and Type II errors are expensive.
TWR versus MWR
- The MWR represents the average growth rate of all money invested in an account, while the TWR represents the growth of a single unit of money invested in the account. Consequently, the MWR is sensitive to the size and timing of external cash flows to and from the account, while the TWR is unaffected by these flows. Under “normal” conditions, these two return measures will produce similar results.
- When external cash flows occur that are large relative to the account’s value and the account’s performance is fluctuating significantly during the measurement period, then the MWR and the TWR can differ materially.
- If funds are contributed to an account prior to a period of strong performance, then the MWR will be positively affected compared to the TWR, as a relatively large sum is invested at a high growth rate.
- Conversely, if funds are withdrawn from the account prior to the strong performance, then the MWR will be adversely affected relative to the TWR. (The opposite conclusions hold if the external cash flow occurred prior to a period of weak performance.)
- The TWR is unaffected by external cash flow activity. Valuing the account at the time of each external cash flow effectively removes the impact of those flows on the TWR. Consequently, the TWR accurately reflects how an investor would have fared over the evaluation period if he or she had placed funds in the account at the beginning of the period.
- In most situations, an investment manager has little or no control over the size and timing of external cash flows into or out of his or her accounts. Therefore, practitioners generally prefer a rate-of-return measure that is not sensitive to cash flows if they want to evaluate how a manager’s investment actions have affected an account’s value.
Compare and contrast macro attribution with micro attribution. What is the difference between using a return metric and using a dollar metric?
Both macro attribution and micro attribution are different facets of performance attribution. The basic tenet behind performance attribution is that an account’s performance is compared to a designated benchmark, then the sources of differential returns are identified and quantified. The main difference between macro and micro attribution is the definition of which “account’s” performance we are analyzing. Macro attribution is done at the fund sponsor level; that is, analysis is typically done for a grouping of investment managers or investment accounts. Micro attribution is carried out at the level of the individual investment manager.
There are three main inputs to the macro attribution approach:
- policy allocations;
- benchmark portfolio returns; and
- fund returns, valuations, and external cash flows.
Fund sponsors determine policy allocations, or “normal” weightings, for each asset class and individual manager. These are typically determined after some sort of asset liability analysis and/or determination of the risk tolerance of the governing body of the fund.
Benchmark portfolio returns are an important factor in determining the value added by the fund. If the benchmarks do not adequately match the managers’ investment styles, the performance attribution will have little value. Fund sponsors may use broad market indexes as the benchmarks for asset categories (the Wilshire 5000 as the benchmark for overall US domestic equities, for example) and may use more focused indexes to represent managers’ investment styles (such as the Russell 2000 Value Index for a small-cap value manager).
Fund returns, valuations, and external cash flows are all critical elements for determining the relevant performance for the portfolio as a whole and for each individual investment manager’s account.
A return metric implies that fund returns are used at the level of the individual management account to allow an analysis of the fund sponsor’s decisions regarding manager selection. A dollar-metric approach uses account valuation and external cash flow data to calculate rates of return and also to compute the dollar impacts of the fund sponsor’s investment policy decision making.
The money-weighted rate of return (MWR)
The money-weighted rate of return (MWR) measures the compound growth rate in the value of all funds invested in the account over the evaluation period. In the corporate finance literature, the MWR goes by the name internal rate of return, or IRR. Of importance for performance measurement, the MWR is the growth rate that will link the ending value of the account to its beginning value plus all intermediate cash flows. With MV1 and MV0 the values of the account at the end and beginning of the evaluation period, respectively, in equation form the MWR is the growth rate R that solves
MV1 = MV0(1 + R)m + CF1(1 + R)m–L(1) + … + CFn(1 + R)m–L(n)
where
m = number of time units in the evaluation period (for example, the number of days in the month)
CFi = the ith cash flow
L(i) = number of time units by which the ith cash flow is separated from the beginning of the evaluation period
The time-weighted rate of return (TWR)
The time-weighted rate of return (TWR) reflects the compound rate of growth over a stated evaluation period of one unit of money initially invested in the account. Its calculation requires that the account be valued every time an external cash flow occurs.
The subperiod returns can be combined through a process called chain-linking. Chain-linking involves first adding 1 to the (decimal) rate of return for each subperiod to create a set of wealth relatives. A wealth relative can be thought of as the ending value of one unit of money (for example, one dollar) invested at each subperiod’s rate of return. Next, the wealth relatives are multiplied together to produce a cumulative wealth relative for the full period, and 1 is subtracted from the result to obtain the TWR.
Treynor Measure
The Treynor measure is closely related to the ex post alpha. Like the ex post alpha, the Treynor measure relates an account’s excess returns to the systematic risk assumed by the account. As a result, it too uses the ex post SML to form a benchmark, but in a somewhat different manner than the ex post alpha. The calculation of the Treynor measure is
TA=(RA−rf)/βA
RA and rf are the average values of each variable over the evaluation period. The Treynor measure has a relatively simple visual interpretation, given that the beta of the risk-free asset is zero. The Treynor measure is simply the slope of a line, graphed in the space of mean ex post returns and beta, which connects the average risk-free return to the point representing the average return and beta of the account. When viewed alongside the ex post SML, the account’s benchmark effectively becomes the slope of the ex post SML. Thus, a skillful manager will produce returns that result in a slope greater than the slope of the ex post SML.
Both the ex post alpha and the Treynor measure will always give the same assessment of the existence of investment skill. This correspondence is evident from the fact that any account with a positive ex post alpha must plot above the ex post SML. Therefore, the slope of a line connecting the risk-free rate to this account must be greater than the slope of the ex post SML, the indication of skill under the Treynor measure.
The Treynor measure uses only systematic risk (i.e., beta) in the denominator, so lowering the unsystematic risk of the asset will have no affect on the Treynor measure.
Alpha and Treynor both measure risk as systematic risk (beta). They will agree in that a manager with positive alpha will have a Treynor in excess of the market Treynor. They may not always agree in relative ranking. A manger with the highest alpha may not have the highest Treynor.
Both Alpha and Treynor are criticized because they depend on beta and assumptions of the CAPM. The criticism include:
- the assumption of a single priced risk rather than some form of multifactor risk pricing and
- the use of a market proxy, such as the S&P 500, to stand for the market. Roll’s critque shows that small changes in what is assumed to be the market can significantly change tha alpha and Treynor calculations and even reverse the conclusions of superior or inferior perforance and rankings.
Level 2 of macro attribution, Risk-free investment
Simulates what fund’s ending value would havfe been if the beggining value and external cash flows had earned the risk-free return.
Properties of a Valid Benchmark
A valid benchmark is:
- Specified in advance. The benchmark is specified prior to the start of an evaluation period and known to all interested parties.
- Owned. The investment manager should be aware of and accept accountability for the constituents and performance of the benchmark. It is encouraged that the benchmark be embedded in and integral to the investment process and procedures of the investment manager.
- Measurable. The benchmark’s return is readily calculable on a reasonably frequent basis.
- Unambiguous. The identities and weights of securities or factor exposures constituting the benchmark are clearly defined.
- Reflective of current investment opinions. The manager has current investment knowledge (be it positive, negative, or neutral) of the securities or factor exposures within the benchmark.
- Appropriate. The benchmark is consistent with the manager’s investment style or area of expertise.
- Investable. It is possible to forgo active management and simply hold the benchmark.
Manager Monitoring
- The goal of MCP manager monitoring is to identify warning signs of adverse changes in existing managers’ organizations. It is a formal, documented procedure that assists fund sponsors in consistently collecting information relevant to evaluating the state of their managers’ operations. The key is that the fund sponsor regularly asks the same important questions, both in written correspondence and in face-to-face meetings.
- As part of the manager monitoring process, the fund sponsor periodically receives information from the managers, either in written form or through face-to-face meetings. This information is divided into two parts.
- The first part covers operational matters, such as personnel changes, account growth, litigation, and so on. The staff should flag significant items and discuss them in a timely manner with the respective managers.
- The second part of the responses contains a discussion of the managers’ investment strategies, on both a retrospective and a prospective basis. The fund sponsor should instruct the managers to explain their recent investment strategies relative to their respective benchmarks and how those strategies performed.
- The goal of these discussions is to assure the fund sponsor that the manager is continuing to pursue a coherent, consistent investment approach. Unsatisfactory manager responses may be interpreted as warning signs that the manager’s investment approach may be less well-defined or less consistently implemented than the staff had previously believed.
- As part of the manager monitoring process, the staff should regularly collect portfolio return and composition data for a performance attribution analysis. The purpose of such a periodic analysis is to evaluate not how well the managers have performed, but whether that performance has been consistent with the managers’ stated investment styles.
In global performance evaluation, performance attribution seeks to?
Performance attribution seeks to identify the sources between portfolio and benchmark return.
Note that performance measurement involves the calculation of risk and return, while performance appraisal seeks to identify whether returns are a result of a manager`s luck or skill.
The Practice of Performance Evaluation
In summary, using past performance to evaluate existing managers is statistically problematic. In the long run, superior managers will outperform inferior managers. However, due to the inherent uncertainty of investment management, over typical evaluation periods (3–5 years) the odds that superior managers will underperform their benchmarks (and, conversely, that inferior managers will outperform their benchmarks) are disturbingly high. Expensive, incorrect decisions may frequently result from relying on past performance to evaluate investment managers.
Set of benchmark quality criteria
Systematic Biases
Over time, there should be minimal systematic biases or risks in the benchmark relative to the account. One way to measure this criterion is to calculate the historical beta of the account relative to the benchmark; on average, it should be close to 1.0.
Tracking Error
We define tracking error as the volatility of A or (P – B). A good benchmark should reduce the “noise” in the performance evaluation process. Thus, the volatility (standard deviation) of an account’s returns relative to a good benchmark should be less than the volatility of the account’s returns versus a market index or other alternative benchmarks.
Risk Characteristics
An account’s exposure to systematic sources of risk should be similar to those of the benchmark over time. The objective of a good benchmark is to reflect but not to replicate the manager’s investment process. Because an active manager is constantly making bets against the benchmark, a good benchmark will exhibit risk exposures at times greater than those of the managed portfolio and at times smaller. Nevertheless, if the account’s risk characteristics are always greater or always smaller than those of the benchmark, a systematic bias exists.
Coverage
Benchmark coverage is defined as the proportion of a portfolio’s market value that is contained in the benchmark. For example, at a point in time, all of the securities and their respective weights that are contained in the account and the benchmark can be examined. The market value of the jointly held securities as a percentage of the total market value of the portfolio is termed the coverage ratio. High coverage indicates a strong correspondence between the manager’s universe of potential securities and the benchmark. Low coverage indicates that the benchmark has little relationship, on a security level, with the opportunity set generated by the manager’s investment process.
Turnover
Benchmark turnover is the proportion of the benchmark’s market value allocated to purchases during a periodic rebalancing of the benchmark. Because the benchmark should be an investable alternative to holding the manager’s actual portfolio, the benchmark turnover should not be so excessive as to preclude the successful implementation of a passively managed portfolio.
Positive Active Positions
An active position is an account’s allocation to a security minus the corresponding weight of the same security in the benchmark. When a good custom security-based benchmark has been built, the manager should be expected to hold largely positive active positions for actively managed long-only accounts.
Note that when an account is benchmarked to a published index containing securities for which a long-only manager has no investment opinion and which the manager does not own, negative active positions will arise. A high proportion of negative active positions is indicative of a benchmark that is poorly representative of the manager’s investment approach.
Hedge Funds and Hedge Fund Benchmarks
- Hedge funds attempt to expose investors to a particular investment opportunity while minimizing (or hedging) other investment risks that could impact the outcome. In most cases, hedging involves both long and short investment positions.
- The ambiguity of hedge fund manager opportunity sets has led to the widespread use of the Sharpe ratio to evaluate hedge fund manager performance.
- Typically, a hedge fund’s Sharpe ratio is compared to that of a universe of other hedge funds that have investment mandates assumed to resemble those of the hedge fund under evaluation. Unfortunately, this approach is exposed to the same benchmark validity criticisms leveled against standard manager universe comparisons. Further, the standard deviation as a measure of risk (the denominator of the Sharpe ratio) is questionable when an investment strategy incorporates a high degree of optionality (skewness), as is the case for the strategies of many hedge funds.
- Problems with using traditional techniques to assess long-short hedge funds include:
- It is possible for MV0 (market value at the beginning of the period) to be zero for a long-short portfolio, making the return calculation nonsensical.
- Many hedge funds use “absolute return” approach, which makes relative performance comparison with a traditional benchmark less useful.
- Alternative performance methods that can be used instead:
- Value-added return
- Creating separate long/short benchmarks
- the Sharpe ratio
Seven primary types of benchmarks
There are seven primary types of benchmarks in use.
- Absolute
- Manager Universes
- Broad Market Indexes
- Style Indexes
- Factor-Model-Based
- Returns-Based
- Custom Security-Based
Performance Attribution
- Performance attribution provides an informed look at the past. It identifies the sources of different-from-benchmark returns (differential returns) and their impacts on an account’s performance.
- We refer to the performance attribution conducted on the fund sponsor level as macro attribution. Performance attribution carried out on the investment manager level we call micro attribution.
Level 4 of macro attribution, the benchmark level
Allows the sponsor to select and assign managers a benchmark different from the policy benchmark. This is tactical asset allocation by the sponsor. For example, 60% in the S&P 500 might fit the fund’s strategic ibjective but the sponsor may expect value stocks to outperform the S&P. The sponsor could direct the manager to use the S&P value index as the manager’s target or manager benchmark. Level 4 simulates the returns of the beginning market value and external cash flows if invested in manager benchmarks. The Level 4 result can also be passively achieved but reflects active decision making by the sponsor to deviate from strategic benchmarks. The level 4 incremental return could be calculated as:
RB = Σ(i=1;A)Σ(j=1;M)(wi)(wi,j)(RB,i,j - Ri)
where:
RB = incremental return fot benchmark strategy
wi = policy weight for asset category i
wi,j = weight assigned to manager j in asset category i
RB,i,j = return for manager j’s benchmark in category i
Ri = return on asset category i
A = number of asset categories
M = number of managers in asset category i
Performance measurement
Performance measurement is a component of performance evaluation. Performance measurement is the relatively simple procedure of calculating returns for an account. Performance evaluation, on the other hand, encompasses the broader and much more complex task of placing those investment results in the context of the account’s investment objectives.
Performance measurement is the first step in the performance evaluation process. Yet it is a critical step, because to be of value, performance evaluation requires accurate and timely rate-of-return information. Therefore, we must fully understand how to compute an account’s returns before advancing to more involved performance evaluation issues.
Performance appraisal involves interpretation of performance attribution.
Factors on which can be based the test of benchmark’s quality
- Over time, there should be minimal systematic biases or risks in the benchmark relative to the portfolio. One measure of this criterion is the historical beta of the portfolio relative to the benchmark; on average it should be close to 1.0
- A high quality benchmark should reduce the “noise” in the performance evaluation process. Therefore, the tracking error of the portfolio relative to a hich quality benchmark should be lower than the tracking error relative to alternative benchmarks.
- ! Market cap is used as a method of evaluation the appropriateness of a benchmark given a manager’s investment style, rather than as a test of benchmark quality.
Factor-Model-Based Benchmark
The simplest form of factor model is a one-factor model, such as the familiar market model. In that relationship, the return on a security, or a portfolio of securities, is expressed as a linear function of the return on a broad market index, established over a suitably long period (for example, 60 months):
Rp = ap + βpRI + εp
These benchmarks are not always intuitive to the fund sponsor and particularly to the investment managers (who rarely think in terms of factor exposures when designing investment strategies), are not always easy to obtain, and are potentially expensive to use. In addition, they are ambiguous. We can build multiple benchmarks with the same factor exposures, but each benchmark can earn different returns. For example, we can construct two different portfolios, each with a beta of 1.2 (“normal beta”), but the portfolios can have materially different returns. Also, because the composition of a factor-based benchmark is not specified with respect to the constituent securities and their weights, we cannot verify all the validity criteria (the benchmark may not be investable, for example).
M2
Like the Sharpe ratio, M2 uses standard deviation as the measure of risk and is based on the ex post CML. M2 is the mean incremental return over a market index of a hypothetical portfolio formed by combining the account with borrowing or lending at the risk-free rate so as to match the standard deviation of the market index. M2 measures what the account would have returned if it had taken on the same total risk as the market index. To produce that benchmark, M2 scales up or down the excess return of the account over the risk-free rate by a factor equal to the ratio of the market index’s standard deviation to the account’s standard deviation.
M<span>2</span><span>A</span>=rf+(RA−rf) * (σM/σA)
M2 will evaluate the skill of a manager exactly as does the Sharpe ratio. However, it is possible for the Sharpe ratio and M2 to identify a manager as not skillful, although the ex post alpha and the Treynor measure come to the opposite conclusion. This outcome is most likely to occur in instances where the manager takes on a large amount of nonsystematic risk in the account relative to the account’s systematic risk.
Ex Post Alpha
The ex post alpha uses the ex post Security Market Line (SML) to form a benchmark for performance appraisal purposes.
RAt – rft = αA + βA(RMt – rft) + εt
where for period t, RAt is the return on the account, rft is the risk-free return, and RMt is the return on the market proxy (market index). The term αA is the intercept of the regression, βA is the beta of the account relative to the market index, and ε is the random error term of the regression equation. The estimate of the intercept term αA is the ex post alpha (Jensen measure). We can interpret ex post alpha as the differential return of the account compared to the return required to compensate for the systematic risk assumed by the account during the evaluation period. The level of the manager’s demonstrated skill is indicated by the sign and value of the ex post alpha.