Powerful Performance Presenters (PPP) is a performance attribution and evaluation firm for pension consulting firms and has recently been hired by Stober and Robertson to conduct a performance attribution analysis for TopTech. Tom Harrison and Wendy Powell are the principals for PPP. Although performance attribution has come under fire lately because of its shortcomings, Stober believes PPP provides a needed service to its clients. Robertson shares Stober's view of performance attribution analysis.Stober and Robertson request that Harrison and Powell provide a discussion of performance measures. During a conversation on complements to attribution analysis, Harrison notes the uses of the Treynor ratio. He states that the Treynor ratio is appropriate only when the investor's portfolio is well diversified. Powell states that the Sharpe ratio and the Treynor ratio will typically yield the same performance rankings for a set of portfolios.Stober requests that PPP do some performance attribution calculations on TopTech's managers. In order to facilitate the analysis, Stober provides the information in the following table:Harrison states one of PPP's services is that it will determine if TopTech has chosen a valid benchmark. Stoher volunteers that indeed his firm's benchmark possesses the properties of a valid benchmark and describes its composition. The benchmark has the following characteristics:• It uses the top 10% of U.S. portfolio managers each year in each asset class as the benchmark for TopTech managers;• TopTech is very careful to make sure that its managers are familiar with the securities in each benchmark asset class;• The identities and weights of various securities in the TopTech benchmark are clearly defined.During a presentation to Stober, Robertson, and other TopTech executives, Harrison and Powell describe how macro attribution analysis can decompose an entire fund's excess returns into various levels. In his introduction, Robertson delineates the six levels as net contributions, risk-free return, asset categories, benchmarks, investment managers, and allocations effects.Robertson states that TopTech has performed impressively at the investment managers level tor three years in a row. Harrison and Powell then describe the levels in greater detail. Harrison describes the benchmark level as the difference between active managers' returns and their benchmark returns. Powell states that the investment managers' level reflects the returns to active management on the part of the fund's managers, weighted by the amount actually allocated to each manager.At the request of Stober, Harrison and Powell explore alternatives to the benchmark TopTech is currently using for its small-cap value manager. After some investigation of the small-cap value manager's emphasis, Harrison and Powell derive four potential custom benchmarks and calculate two measures to evaluate the benchmarks:(1) the return to the manager's active management or A = portfolio return - benchmark return; and (2) the return to the manager's style or S = benchmark return - broad market return.The following characteristics are presented below for each benchmark: (1) the beta between the benchmark and the small-cap value portfolio; (2) the tracking error (i.e., the standard deviation of A); (3) the turnover of the benchmark; and (4) the correlation between A and S.Harrison and Powell evaluate the benchmarks based on the four measures.Based on an overall attribution analysis, does TopTech demonstrate superior ability to select stocks?
Answer(s): A
The within-sector selection effect measures the manager's ability to select superior securities to represent each sector in the portfolio. It is the sum of the weight for each sector in the benchmark times the difference in that sector's return in the portfolio and in the benchmark.Within sector selection effect = (0.60)(0.187 - 0.286) + 0.25(0.158 - 0.124) + (0.15) (0.125 - 0.0885) = -0.0594 + 0.0085 + 0.0055 = -0.0454 = -4.54%.In sum, in the financial and large cap sectors, the manager chose superior stocks, so they show superior ability there. The overall within-sector selection effect is negative (-4.54%), however, so they do not show a consistent overall ability to select stocks.The remaining component of attribution analysis (the allocation/selection interaction effect) can be calculated as the difference between the portfolio and benchmark weights for each sector multiplied by the difference between the return for the sector in the portfolio and the return for the sector in the benchmark. The total allocation/ selection interaction effect is the sum of these products.Allocation/selection interaction effect = (0.50 - 0.60)(0.187 - 0.286) + (0.30 - 0.25) (0.158 - 0.124) + (0.20 - 0.15) (0.125 - 0.0885) = 0.0099 + 0.0017 + 0.0018 = 0.0134= 1.34%.The total excess return for the manager is then -1.80% + 1.34% - 4.54% = -5-00%.This should be equal to the excess return calculated using the total returns for the benchmark and the portfolio. The total return for the benchmark is calculated above as 21.6%. For the portfolio it is: = (0.5)(0.187) + (0.3) (0.158) + (0.2)(0.125) = 16.6%. Thus the excess return calculated using the total returns for the portfolio and the benchmark is 16.6% - 21.6% = -5.0%. (Study Session 17, LOS 47.1)
Powerful Performance Presenters (PPP) is a performance attribution and evaluation firm for pension consulting firms and has recently been hired by Stober and Robertson to conduct a performance attribution analysis for TopTech. Tom Harrison and Wendy Powell are the principals for PPP. Although performance attribution has come under fire lately because of its shortcomings, Stober believes PPP provides a needed service to its clients. Robertson shares Stober's view of performance attribution analysis.Stober and Robertson request that Harrison and Powell provide a discussion of performance measures. During a conversation on complements to attribution analysis, Harrison notes the uses of the Treynor ratio. He states that the Treynor ratio is appropriate only when the investor's portfolio is well diversified. Powell states that the Sharpe ratio and the Treynor ratio will typically yield the same performance rankings for a set of portfolios. Stober requests that PPP do some performance attribution calculations on TopTech's managers. In order to facilitate the analysis, Stober provides the information in the following table:Harrison states one of PPP's services is that it will determine if TopTech has chosen a valid benchmark. Stoher volunteers that indeed his firm's benchmark possesses the properties of a valid benchmark and describes its composition. The benchmark has the following characteristics:• It uses the top 10% of U.S. portfolio managers each year in each asset class as the benchmark for TopTech managers;• TopTech is very careful to make sure that its managers are familiar with the securities in each benchmark asset class;• The identities and weights of various securities in the TopTech benchmark are clearly defined.During a presentation to Stober, Robertson, and other TopTech executives, Harrison and Powell describe how macro attribution analysis can decompose an entire fund's excess returns into various levels. In his introduction, Robertson delineates the six levels as net contributions, risk-free return, asset categories, benchmarks, investment managers, and allocations effects.Robertson states that TopTech has performed impressively at the investment managers level tor three years in a row. Harrison and Powell then describe the levels in greater detail. Harrison describes the benchmark level as the difference between active managers' returns and their benchmark returns. Powell states that the investment managers' level reflects the returns to active management on the part of the fund's managers, weighted by the amount actually allocated to each manager.At the request of Stober, Harrison and Powell explore alternatives to the benchmark TopTech is currently using for its small-cap value manager. After some investigation of the small-cap value manager's emphasis, Harrison and Powell derive four potential custom benchmarks and calculate two measures to evaluate the benchmarks:(1) the return to the manager's active management or A = portfolio return - benchmark return; and (2) the return to the manager's style or S = benchmark return - broad market return.The following characteristics are presented below for each benchmark: (1) the beta between the benchmark and the small-cap value portfolio; (2) the tracking error (i.e., the standard deviation of A); (3) the turnover of the benchmark; and (4) the correlation between A and S.Harrison and Powell evaluate the benchmarks based on the four measures. The TopTech benchmark contains all the following properties of a valid benchmark except:
TopTech's benchmark appears to be reflective of current investment opinion, because the managers have knowledge of the securities in the benchmark. It also appears to be unambiguous, because the weights and identities of the securities in the benchmark are clearly identified.However, a benchmark must satisfy five other criteria to be considered valid. In TopTech's case, the benchmark is not specified in advance and is not invescable. By choosing the top 10% of managers after the fact, TopTech's managers have no knowledge of what securities constitute the benchmark before the fact.Thus, their benchmark is also not investable. TopTech's managers cannot replicate the benchmark positions before the fact because they do not know the top ten managers at the beginning of the measurement period. In sum, TopTech's benchmark does nor possess all the properties of a valid benchmark. (Study Session 17, LOS 47-f)
Powerful Performance Presenters (PPP) is a performance attribution and evaluation firm for pension consulting firms and has recently been hired by Stober and Robertson to conduct a performance attribution analysis for TopTech. Tom Harrison and Wendy Powell are the principals for PPP. Although performance attribution has come under fire lately because of its shortcomings, Stober believes PPP provides a needed service to its clients. Robertson shares Stober's view of performance attribution analysis.Stober and Robertson request that Harrison and Powell provide a discussion of performance measures. During a conversation on complements to attribution analysis, Harrison notes the uses of the Treynor ratio. He states that the Treynor ratio is appropriate only when the investor's portfolio is well diversified. Powell states that the Sharpe ratio and the Treynor ratio will typically yield the same performance rankings for a set of portfolios.Stober requests that PPP do some performance attribution calculations on TopTech's managers. In order to facilitate the analysis, Stober provides the information in the following table:Harrison states one of PPP's services is that it will determine if TopTech has chosen a valid benchmark. Stoher volunteers that indeed his firm's benchmark possesses the properties of a valid benchmark and describes its composition. The benchmark has the following characteristics:• It uses the top 10% of U.S. portfolio managers each year in each asset class as the benchmark for TopTech managers;• TopTech is very careful to make sure that its managers are familiar with the securities in each benchmark asset class; • The identities and weights of various securities in the TopTech benchmark are clearly defined.During a presentation to Stober, Robertson, and other TopTech executives, Harrison and Powell describe how macro attribution analysis can decompose an entire fund's excess returns into various levels. In his introduction, Robertson delineates the six levels as net contributions, risk-free return, asset categories, benchmarks, investment managers, and allocations effects.Robertson states that TopTech has performed impressively at the investment managers level tor three years in a row. Harrison and Powell then describe the levels in greater detail. Harrison describes the benchmark level as the difference between active managers' returns and their benchmark returns. Powell states that the investment managers' level reflects the returns to active management on the part of the fund's managers, weighted by the amount actually allocated to each manager.At the request of Stober, Harrison and Powell explore alternatives to the benchmark TopTech is currently using for its small-cap value manager. After some investigation of the small-cap value manager's emphasis, Harrison and Powell derive four potential custom benchmarks and calculate two measures to evaluate the benchmarks:(1) the return to the manager's active management or A = portfolio return - benchmark return; and (2) the return to the manager's style or S = benchmark return - broad market return.The following characteristics are presented below for each benchmark: (1) the beta between the benchmark and the small-cap value portfolio; (2) the tracking error (i.e., the standard deviation of A); (3) the turnover of the benchmark; and (4) the correlation between A and S.Harrison and Powell evaluate the benchmarks based on the four measures.Regarding their statements concerning macro attribution analysis, determine whether Harrison and Powell are correct or incorrect.
Answer(s): C
Harrison is incorrect. The benchmark level examines the difference between the return to custom benchmarks reflecting the managers' styles and the return to a broad asset category. Essentially the benchmark return measures the return to style bets resulting from the policy weighting in various styles.Powell is incorrect. Although the investment managers level does reflect the return from active management, it uses the policy weights established for each manager. Returns due to differences between policy weights and the amounts actually allocated to each manager do not show up until the last level of macro attribution analysis (i.e., allocation effects). (Study Session 17, LOS 47.k)
Powerful Performance Presenters (PPP) is a performance attribution and evaluation firm for pension consulting firms and has recently been hired by Stober and Robertson to conduct a performance attribution analysis for TopTech. Tom Harrison and Wendy Powell are the principals for PPP. Although performance attribution has come under fire lately because of its shortcomings, Stober believes PPP provides a needed service to its clients. Robertson shares Stober's view of performance attribution analysis.Stober and Robertson request that Harrison and Powell provide a discussion of performance measures. During a conversation on complements to attribution analysis, Harrison notes the uses of the Treynor ratio. He states that the Treynor ratio is appropriate only when the investor's portfolio is well diversified. Powell states that the Sharpe ratio and the Treynor ratio will typically yield the same performance rankings for a set of portfolios.Stober requests that PPP do some performance attribution calculations on TopTech's managers. In order to facilitate the analysis, Stober provides the information in the following table:Harrison states one of PPP's services is that it will determine if TopTech has chosen a valid benchmark. Stoher volunteers that indeed his firm's benchmark possesses the properties of a valid benchmark and describes its composition. The benchmark has the following characteristics:• It uses the top 10% of U.S. portfolio managers each year in each asset class as the benchmark for TopTech managers;• TopTech is very careful to make sure that its managers are familiar with the securities in each benchmark asset class;• The identities and weights of various securities in the TopTech benchmark are clearly defined.During a presentation to Stober, Robertson, and other TopTech executives, Harrison and Powell describe how macro attribution analysis can decompose an entire fund's excess returns into various levels. In his introduction, Robertson delineates the six levels as net contributions, risk-free return, asset categories, benchmarks, investment managers, and allocations effects.Robertson states that TopTech has performed impressively at the investment managers level tor three years in a row. Harrison and Powell then describe the levels in greater detail. Harrison describes the benchmark level as the difference between active managers' returns and their benchmark returns. Powell states that the investment managers' level reflects the returns to active management on the part of the fund's managers, weighted by the amount actually allocated to each manager.At the request of Stober, Harrison and Powell explore alternatives to the benchmark TopTech is currently using for its small-cap value manager. After some investigation of the small-cap value manager's emphasis, Harrison and Powell derive four potential custom benchmarks and calculate two measures to evaluate the benchmarks:(1) the return to the manager's active management or A = portfolio return - benchmark return; and (2) the return to the manager's style or S = benchmark return - broad market return.The following characteristics are presented below for each benchmark: (1) the beta between the benchmark and the small-cap value portfolio; (2) the tracking error (i.e., the standard deviation of A); (3) the turnover of the benchmark; and (4) the correlation between A and S. Harrison and Powell evaluate the benchmarks based on the four measures.Of the three benchmarks, determine which would be most appropriate for the small cap value manager.
Answer(s): B
Benchmark B is the best benchmark for the small-cap value manager. A good benchmark will have a beta relative to the portfolio that is close to one, so the tracking error (i.e., the standard deviation of the excess return of the portfolio relative to the benchmark) will be low. The benchmark turnover should be low so that it is investable by a passive manager. The correlation between the return to the managers active management (A) and the return to the managers style (S) should be low. Otherwise, the benchmark has not adequately captured the managers style.Benchmark B is the best benchmark using all four measures. (Study Session 17, LOS 47.i) Sample Scoring Key: 3 points for each correct response.
Security analysts Andrew Tian, CFA, and Cameron Wong, CFA, are attending an investment symposium at the Singapore Investment Analyst Society. The focus of the symposium is capital market expectations and relative asset valuations across markets. Many highly-respected practitioners and academics from across the Asia- Pacific region are on hand to make presentations and participate in panel discussions.The first presenter, Lillian So, President of the Society, speaks on market expectations and tools for estimating intrinsic valuations. She notes that analysts attempting to gauge expectations are often subject to various pitfalls that subjectively skew their estimates. She also points out that there are potential problems relating to a choice of models, not all of which describe risk the same way. She then provides the following data to illustrate how analysts might go about estimating expectations and intrinsic values. The next speaker, Clive Smyth, is a member of the exchange rate committee at the Bank of New Zealand. His presentation concerns the links between spot currency rates and forecasted exchange rates. He states that foreign exchange rates are linked by several forces including purchasing power parity (PPP) and interest rate parity (IRP). He tells his audience that the relationship between exchange rates and PPP is strongest in the short run, while the relationship between exchange rates and IRP is strongest in the long run. Smyth goes on to say that when a country's economy becomes more integrated with the larger world economy, this can have a profound impact on the cost of capital and asset valuations in that country.The final speaker in the session directed his discussion toward emerging market investments. This discussion, by Hector Ruiz, head of emerging market investment for the Chilean Investment Board, was primarily concerned with how emerging market risk differs from that in developed markets and how to evaluate the potential of emerging market investments. He noted that sometimes an economic crisis in one country can spread to other countries in the area, and that asset returns often exhibit a greater degree of non-normality than in developed markets.Ruiz concluded his presentation with the data in the tables below to illustrate factors that should be considered during the decision-making process for portfolio managers who are evaluating investments in emerging markets.When the first presenter refers to skewed estimates and problems with a choice of models, she is referring to:
Ms. So is referring to psychological traps and model and input uncertainty. Psychological traps are behavioral characteristics such as anchoring, status quo, overconfidence, etc. The main point is that these traps can result in biased capital market expectations. Problems relating to the choice of models and accuracy of data are known as model and input uncertainty. The analyst wants to choose the model that most correctly describes the marker valuation process, bur any time there is a choice, there is a chance that the incorrect model will be chosen. (Study Session 6, LOS 23.a)
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