bapswarrior

Analysts trying to compensate for instability in the efficient frontier are least concerned about:

A) small changes in expected returns.

B) a sharp rise in earnings restatements.

C) uncertainty in the forecast of variances and returns.

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Small changes in expected returns can have a large effect on the efficient frontier – in some cases analysts or money managers will take actions to compensate for those effects. Uncertainty in forecasts is of paramount importance to analysts, since an accurate portrayal of the efficient frontier is impossible without accurate estimates. While historical data is often used to extrapolate future values, analysts realize the limitations of such data in forecasting. As such, changes to historical statistics, such as those caused by a flood of restatements, would be of some concern, but less than the other choices.

bapswarrior

What happens to the minimum-variance frontier when:

Return forecasts fall?

Covariance forecasts fall?

A) Curve shifts left Curve shifts down

B) Curve shifts down Curve shifts down

C) Curve shifts down Curve shifts left

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When the expected return forecast declines, the minimum-variance frontier moves down. A decline in covariance forecasts will cause the curve to shift to the left.

bapswarrior

An analyst is constructing a portfolio for a new client. During an optimization procedure, it becomes apparent that small changes in input assumptions lead to broad changes in the efficient frontier. This is most likely a result of instability:

A) of the point estimate of the sample mean.

B) in the minimum variance frontier.

C) of the point estimates of the covariances.

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When small changes in input assumptions lead to broad changes in the efficient frontier, instability in the minimum variance frontier and the efficient frontier is indicated.

bapswarrior

Responses to instability in the minimum variance frontier are least likely to include:

A) improving the statistical quality of inputs.

B) adding constraints against short sales.

C) reducing the skew of the probability distribution of the sample mean.

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Improving the statistical quality of inputs and adding constraints against short sales are valid methods for reducing instability in the minimum variance frontier.

bapswarrior

Analysts attempting to compensate for instability in the minimum-variance frontier will find which of the following strategies least effective?

A) Reducing the frequency of portfolio rebalancing.

B) Gathering more accurate historical data.

C) Eliminating short sales.

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Constraining portfolio weights through the elimination of short sales and avoiding rebalancing until significant changes occur in the efficient frontier can be effective strategies for limiting instability. However, even the best historical data is often of limited use in forecasting future values. Gathering more accurate historical data would help, compensate for instability, but not as much as the other two options.

bapswarrior

Martz & Withers Enterprises has a beta of 1.6. We can most likely assume that:

A) the future beta will be less than 1.6 but greater than 1.0.

B) calculating an adjusted beta will ease the downward pressure on the forecasted beta.

C) the standard error on the future beta forecast is positive.

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The standard error is always expected to be zero, and the beta has nothing to do with that estimate. In the case of Martz & Withers, adjusted beta will almost certainly be lower than the current beta. Most adjusted beta calculations are as follows: adjusted beta = 1/3 + (2/3 × historical beta). In this case, adjusted beta is 1.2. Not everyone will use the two-thirds/one-third relationship, but any adjusted-beta equation will result in a value between 1.0 and 1.6.

bapswarrior

Conner Cans shares have a beta of 0.8. Assuming α1 is 40%, Conner’s adjusted beta is closest to:

A) 1.12.

B) 0.92.

C) 0.88.

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Adjusted beta = α0 + α1 × beta where α0 and α1 must sum to 1, so α0 = 60%.
Adjusted beta = 60% + 40% × 0.8 = 0.92.

bapswarrior

Adjusted betas were developed in an effort to compensate for:

A) traditional beta’s limitations in assessing the risk of extremely volatile stocks.

B) the weaknesses of standard deviation as a risk measurement.

C) inaccurate forecasts for the efficient frontier based on traditional beta.

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Adjusted beta was developed to compensate for the beta instability problem, or the tendency of historical betas to generate inaccurate forecasts. Extreme volatility is not an issue; nor is standard deviation.

bapswarrior

Bill Tanner is a new associate at Global Western Investments. Tanner approaches his supervisor, Eric Simms, with some questions about risk. Specifically, Tanner lacks a complete understanding of many portfolio concepts, including the following:

• How the presence of a risk-free asset will affect the efficient frontier.
• The difference between total risk, systematic risk, and unsystematic risk.
• Market and Macroeconomic models.

Tanner is concerned with providing the best investment advice possible for his clients. He seeks advice from some of his former Midwestern college friends who now happen to be CFA charterholders. One of his old roommates suggests that he look into using the market model or a multifactor model based on the arbitrage pricing theory (APT).
Tanner researches alternative pricing models and starts to become confused as all the equations look similar. He writes down the following notes from memory:

• The intercept for the market model is derived from the APT.
• The intercept for the APT is the risk free rate.
• The intercept for a macroeconomic factor model is the expected return on the stock when there are no surprises to the factors.

Simms makes the predictions for Tanner shown in Exhibit 1.

Exhibit 1: Simm’s Predictions for Tanner

Beta for Stock B	1.10
Beta for Stock C	1.50
Correlation between Stock A and the S&P 500	0.50
Standard deviation for Stock A	28%
Standard deviation for the S&P 500	20%
1-year Treasure bill rate	5%
Expected return on the S&P 500	12%

Tanner uses the market model predictions (and the S&P 500 as a proxy for the market portfolio) to calculate the covariance of Stock B and C at 0.33. Using the market model, he also determines that the systematic component of the variance for Stock B is equal to 0.048.
Next, he heads out to meet a friend, Del Torres, for lunch. Torres excitedly tells Tanner about his latest work with tracking and factor portfolios. Torres says he has developed a tracking portfolio to aid in speculating on oil prices and is working on a factor portfolio with a specific set of factor sensitivities to the Russell 2000.Which of the following is the most appropriate response to Tanner’s question about the presence of a risk-free asset and the Markowitz efficient frontier? The presence of a risk-free asset changes the characteristics of the Markowitz efficient frontier by:

A) converting the Markowitz efficient frontier from a curve into a linear risk/return relationship.

B) reducing the total risk and the systematic risk of the market portfolio.

C) allowing risk averse investors to include in their portfolios an asset that is negatively correlated with stocks, thereby reducing the risk related to investing in equities.

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The presence of a risk-free asset changes the characteristics of the Markowitz efficient frontier by converting the Markowitz efficient frontier from a curve into a straight line called the capital market line (CML). (Study Session 18, LOS 60.b)

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Which of the following statements best describes the concept of systematic risk? Systematic risk:

A) remains even for a well-diversified portfolio.

B) is approximately equal to total risk divided by unsystematic risk.

C) as measured by the standard deviation is the only risk rewarded by the market.

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Systematic risk remains even if a portfolio is well diversified. (Study Session 18, LOS 60.g)

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Are Tanner’s notes on the intercepts for the pricing models correct?

A) No, because the intercept for the market model is the return on the stock when the return on the market is zero.

B) No, because the intercept for the APT is the stock’s alpha.

C) No, because the intercept for the market model is the risk-free rate.

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Tanner is incorrect with regard to the market model. The intercept is equal to the return when the market return is zero. Tanner’s other two comments on intercepts are correct. (Study Session 18, LOS 60.g)

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The beta of Stock A is closest to:

A) 0.70.

B) 0.36.

C) 0.50.

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(Study Session 18, LOS 60.h)

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According to the predictions of the market model, did Tanner correctly calculate the covariance of Stock B and C and Stock B’s systematic component of variance?

Covariance

Systematic component

A) Yes Yes

B) No Yes

C) Yes No

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Tanner incorrectly calculated the covariance and correctly calculated the systematic variance component.
According to the market model, the covariance between any two stocks is calculated as the product of their betas and the variance of the market portfolio. Here, the S&P 500 is a proxy for the market portfolio.

Here, CovB,C = 1.10(1.50)(0.2)2 = 0.066. Tanner incorrectly used the standard deviation of the market.The variance of the returns on asset i consists of two components: a systematic component related to the asset’s beta, , and an unsystematic component related to firm-specific events, .
For Stock B, the systematic component = 1.102(0.2)2 = 0.048 (Study Session 18, LOS 60.a)

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Did Torres correctly describe tracking and factor portfolios?

Tracking

Factor

A) Yes No

B) No No

C) No Yes

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Torres reversed the concepts and is thus incorrect on both counts. A factor portfolio is a portfolio with a factor sensitivity of 1 to a particular factor and zero to all other factors. It represents a pure bet on one factor, and can be used for speculation or hedging purposes. A tracking portfolio is a portfolio with a specific set of factor sensitivities. Tracking portfolios are often designed to replicate the factor exposures of a benchmark index like the Russell 2000. (Study Session 18, LOS 60.m)

bapswarrior

The single-factor market model assumes there are how many sources of risk in asset returns?

A) Two.

B) One.

C) Three.

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The market model assumes that there are two sources of risk in asset returns, unanticipated macroeconomic events and firm-specific events.