Free CFA-Level-III Exam Braindumps (page: 28)

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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 sectors?

  1. No the pure allocation effect is -1.8%.
  2. Yes the pure allocation effect is 1.8%.
  3. Yes the pure allocation effect is 3.2%.

Answer(s): A

Explanation:

The pure allocation effect is calculated by taking the differences between the portfolio and benchmark weights for each sector and multiplying it by the difference between the benchmark return for that sector and the total benchmark return. The products are then summed across the sectors:
benchmark return = (0.6)(0.286) + (0.25)(0.124) + (0.15)(0.0885) = 0.216
The pure allocation effect = (0.5 - 0.6)(0.286 - 0.216) + (0.3 - 0.25)(0.124 - 0.216) +(0.2 - 0.15)(0.0885 - 0.216)= -1.80%.
SoTopTech does not demonstrate superior ability to choose sectors, because the allocation effect is negative at -1.80%. (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.
Based on an overall attribution analysis, does TopTech demonstrate superior ability to select stocks?

  1. No, the within-sector selection effect is -4.5%.
  2. No, the within-sector selection effect is -3.2%.
  3. Yes, the within-sector selection effect is 1.3%.

Answer(s): A

Explanation:

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:

  1. it is investable.
  2. it is unambiguous.
  3. it is reflective of current investment opinion.

Answer(s): A

Explanation:

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.

  1. Only Harrison is correct.
  2. Only Powell is correct.
  3. Both Harrison and Powell are incorrect.

Answer(s): C

Explanation:

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)






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