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Reading 64: Portfolio Concepts-LOS J习题精选

LOS j: Discuss and compare macroeconomic factor models, fundamental factor models, and statistical factor models.

Orb Trust (Orb) has historically leaned towards a passive management style of its portfolios. The only model that Orb’s senior management has promoted in the past is the Capital Asset Pricing Model (CAPM). Now Orb’s management has asked one of its analysts, Kevin McCracken, CFA, to investigate the use of the Arbitrage Pricing Theory model (APT).

McCracken has determined that a two-factor APT model is adequate where the factors are the sensitivity to changes in real GDP and changes in inflation. McCracken’s analysis has led him to the conclusion that the factor risk premium for real GDP is 8 percent while the factor risk premium for inflation is 2 percent. He estimates for Orb’s High Growth Fund that the sensitivities to these two factors are 1.25 and 1.5 respectively. Using his APT results, he computes the expected return of the fund. For comparison purposes, he then uses fundamental analysis to also compute the expected return of Orb’s High Growth Fund. McCracken finds that the two estimates of the Orb High Growth Fund’s expected return are equal.

McCracken asks a fellow analyst, Sue Kwon, to provide an estimate of the expected return of Orb’s Large Cap Fund based upon fundamental analysis. Kwon, who manages the fund, says that the expected return is 8.5 percent above the risk-free rate. McCracken then applies the APT model to the Large Cap Fund. He finds that the sensitivities to real GDP and inflation are 0.75 and 1.25 respectively.

Kwon wants to learn more about the APT and discusses McCracken’s results with him. McCracken says “the APT model is a variation of the CAPM.” Kwon comments that “extending the CAPM to an APT framework must require additional assumptions.”

Craig Newland joins the conversation. Newland says that the APT really is just another ad hoc multifactor model. All a researcher needs to do to compose an APT model, according to Newland, is to find a few macroeconomic factors that are correlated with stock returns and do a simple linear regression for each asset. McCracken says that it really is not that easy. For one thing, according to McCracken, the coefficients in the APT have a different interpretation from that of a basic multifactor model.

McCracken’s manager at Orb, Jay Stiles, asks McCracken to compose a portfolio that has a unit sensitivity to real GDP growth but is not affected by inflation. McCracken is confident in his APT estimates for the High Growth Fund and the Large Cap Fund. He then computes the sensitivities for a third fund, Orb’s Utility Fund, which has sensitivities equal to 1.0 and 2.0 respectively. McCracken will use his APT results for these three funds to accomplish the task of creating a portfolio with a unit exposure to real GDP and no exposure to inflation. He calls the fund the “GDP Fund.” Stiles says such a GDP Fund would be good for clients who are retirees who live off the steady income of their investments. McCracken says that the fund would be a good choice if upcoming supply-side macroeconomic policies of the government are successful.

McCracken’s estimate of the expected return of Orb’s High Growth Fund would be:

A)
the risk-free rate plus 10%.
B)
10%.
C)
the risk-free rate plus 13%.



The formula is: expected return = RF + 0.08 × 1.25 + 0.02 × 1.5 = RF + 13% (Study Session 18, LOS 66.j)


With respect to McCracken’s APT model estimate of Orb’s Large Cap Fund and the information Kwon provides, an arbitrage profit could:

A)
be earned by buying the High Growth Fund and selling short the Large Cap Fund.
B)
be earned by buying the Large Cap Fund and selling short the High Growth Fund.
C)
not be earned.



Based on the sensitivities to real GDP and inflation of 0.75 and 1.25, McCracken would calculate the expected return for the Orb Large Cap Fund to be: 

expected return = RF + 0.08 × 0.75 + 0.02 × 1.25 = RF + 8.5% 

Therefore, Kwon’s fundamental analysis estimate is congruent with McCracken’s APT estimate. If we assume that both Kwon’s and McCracken’s estimates of the return of Orb’s High Growth Fund are accurate, then no arbitrage profit is possible. Had Kwon provided an estimate of the Orb Large Cap Fund’s expected return that was less than 8.5 percent, for example, then we would consider selling that fund short and purchasing the High Growth Fund with the proceeds. (Study Session 18, LOS 66.l)


With respect to McCracken and Kwon’s comments concerning the relationship of the APT to the CAPM:

A)
both McCracken and Kwon are wrong.
B)
Kwon is correct and McCracken is wrong.
C)
McCracken is correct and Kwon is wrong.



McCracken is correct in saying the APT is a variation of the CAPM. Both the APT and the CAPM are equilibrium asset-pricing models. For example, both models assume there are no arbitrage opportunities available. The APT requires fewer (not more) assumptions, however, e.g., the APT does not assume all investors will hold the same portfolio and have the same expectations. (Study Session 18, LOS 66.n)


In the conversation between Newland and McCracken concerning the relationship of multifactor models in general and the APT:

A)
Newland was correct and McCracken was wrong.
B)
they were both wrong.
C)
McCracken was correct and Newland was wrong.




The GDP Fund composed from the other three funds would have a weight in Utility Fund equal to:

A)
-2.2.
B)
-3.2.
C)
0.3.



In order to eliminate inflation, the following three equations must be solved simultaneously, where the GDP sensitivity will equal 1 in the first equation, inflation sensitivity will equal 0 in the second equation and the sum of the weights must equal 1 in the third equation.

1. 1.25wx + 0.75wy + 1.0wz = 1 
2. 1.5wx+ 1.25wy + 2.0wz = 0 
3. wx + wy + wz = 1 

Here, “x” represents Orb’s “High Growth Fund”, “y” represents “Large Cap Fund” and “z” represents “Utility Fund.” By multiplying equation 1 by 2.0 and subtracting equation 2 from the result, McCracken will get wx + 0.25wy = 2. McCracken can also subtract equation 3 from equation 1 and get 0.25wx – 0.25wy = 0. This means wx = wy. Thus, the equation wx + 0.25wy = 2 becomes 1.25wy = 2 and wy = wx = 1.6. It follows from any of the other equations that wz = -2.2.

(Study Session 18, LOS 66.j)


With respect to the comments of Stiles and McCracken concerning for whom the GDP Fund would be appropriate:

A)
both were correct.
B)
McCracken was correct and Stiles was wrong.
C)
Stiles was correct and McCracken was wrong.



Since retirees living off a steady income would be hurt by inflation, this portfolio would not be appropriate for them. Retirees would want a portfolio whose return is positively correlated with inflation, to preserve value, and less correlated with the variable growth of GDP. Thus, the fund would not be appropriate for retirees and Stiles is wrong. McCracken is correct in that supply side macroeconomic policies are generally designed to increase output at a minimum of inflationary pressure. Increased output would mean higher GDP, which in turn would increase returns of a fund positively correlated with GDP. (Study Session 18, LOS 66.j)

 

In a multi-factor macroeconomic model the mean-zero error term represents:

A)

the portion of the individual asset's return that is not explained by the systematic factors.

B)

sampling error in estimating factor sensitivities.

C)

the no-arbitrage condition imposed in multi-factor models.




The mean-zero error term represents the unsystematic, firm-specific, diversifiable risks that are not explained by the systematic factors.

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The factor models for the returns on Omni, Inc., (OM) and Garbo Manufacturing (GAR) are:

ROM = 20.0% –1.0(FCONF) + 1.4(FTIME) + εOM
RGAR = 15.0% –0.5(FCONF) + 0.8 (FTIME) + εGAR

What is the expected return on a portfolio invested 60% in Omni and 40% in Garbo?

A)

20.96%.

B)

19.96%.

C)

18.0%.




The factor model for the portfolio is:

RP = [(0.6)(20.0%) + (0.4)(15.0%)]
+ [(0.6)(?1.0) + (0.4)(?0.5)] (FCONF)
+ [(0.6)(1.4) + (0.4)(0.8)] (FTIME)
+ [(0.6) εOM + (0.4)εGAR]

= 18.0% ?0.80(FCONF) + 1.16(FTIME) + (0.6)εOM + (0.4)εGAR

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Which of the following statements concerning the multi-factor model for returns on stock j {Rj = 12% + 1.4F1 – 0.8F2 + εj} is FALSE?

A)

The return on stock j will decrease as factor 2 is expected to increase.

B)

The expected return on stock j is 12%.

C)

F1 and F2 represent priced risk.




 

In a multi-factor model, only unexpected changes in systematic factors are priced in the sense that they affect stock returns. The return on stock j will decrease only if factor 2 increases unexpectedly (because the factor sensitivity is less than zero). Expected increases will NOT cause stock j returns to decrease.

[此贴子已经被作者于2010-4-14 15:48:20编辑过]

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The factor models for the returns on Omni, Inc., (OM) and Garbo Manufacturing (GAR) are:

ROM = 20.0% ? 1.0(FCONF) + 1.4(FTIME) + εOM
RGAR = 15.0% ? 0.5(FCONF) + 0.8 (FTIME) + εGAR

What is the factor sensitivity to the time-horizon factor (TIME) of a portfolio invested 20% in Omni and 80% in Garbo?

A)

0.92.

B)

-0.60.

C)

0.16.




The factor model for the portfolio is:
RP = [(0.2)(20.0%) + (0.8)(15.0%)]
+ [(0.2)(-1.0) + (0.8)(-0.5)] (FCONF)
+ [(0.2)(1.4) + (0.8)(0.8)] (FTIME)
+ [(0.2) εOM + (0.8)εGAR]

= 16.0% ?0.60(FCONF) + 0.92(FTIME) + (0.2)εOM + (0.8)εGAR

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Examples of macroeconomic variables that create systematic risk include:

A)
variability in the growth of the money supply.
B)
changes in GDP growth rates.
C)
all of these choices are correct.



Systematic risk factors are those variables that: (1) exhibit correlation with other variables and (2) explain the returns of many different assts. GDP growth and the money supply are each examples of systematic risk factors.

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A multi-factor model that identifies the portfolios that best explain the historical cross-sectional returns or covariances among assets is called a:

A)

statistical factor model.

B)

fundamental factor model.

C)

covariance factor model.




A statistical factor model identifies the portfolios that best explain the historical cross-sectional returns or covariances among assets. The returns on these portfolios represent the factors. In fundamental factor models, the factors are characteristics of the stock or the company that have been shown to affect asset returns, such as book-to-market or price-to-earnings ratios.

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Identify the most accurate statement regarding multifactor models from among the following.

A)
Macrofactor models include explanatory variables such as real GDP growth and the price-to-earnings ratio and fundamental factor models include explanatory variables such as firm size and unexpected inflation.
B)
Macrofactor models include explanatory variables such as firm size and the price-to-earnings ratio and fundamental factor models include explanatory variables such as real GDP growth and unexpected inflation.
C)
Macrofactor models include explanatory variables such as the business cycle, interest rates, and inflation, and fundamental factor models include explanatory variables such as firm size and the price-to-earnings ratio.



Macrofactor models include multiple risk factors such as the business cycle, interest rates, and inflation. Fundamental factor models include specific characteristics of the securities themselves such as firm size and the price-to-earnings ratio.

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A two-stock portfolio consists of the following:

  • The portfolio consists of stock of Green Company (portfolio weight 30%) and Blue Company (portfolio weight 70%).

  • Green’s expected return is 12%, Blue’s is 8%.

  • Interest rates are expected to be 6%.

  • Oil prices are expected to rise 2%.

  • The two-factor model for Green Company is R(green) = 12% ? 0.5 Fint ? 0.5 Foil + egreen

  • The two-factor model for Blue Company is R(blue) = 8% + 0.8 Fint + 0.4 Foil + eblue

If interest rates are actually 9% and oil prices do not rise, the return on the portfolio will be:

A)
12.89%.
B)
10.17%.
C)
10.55%.



R(green) is [12 ? (0.5 × 3) ? (0.5 × (?2))] = 11.5%.

R(blue) is [8 + (0.8 × 3) + (0.4 × (?2))] = 9.6%.

The portfolio return is [(0.30)(11.5) + (0.70)(9.6)] = 10.17%.

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A multi-factor model that uses unexpected changes (surprises) in macroeconomic variables (e.g., inflation and gross domestic product) as the factors to explain asset returns is called a:

A)

fundamental factor model.

B)

statistical factor model.

C)

macroeconomic factor model.




Macroeconomic factor models use unexpected changes (surprises) in macroeconomic variables as the factors to explain asset returns. One example of a factor in this type of model is the unexpected change in gross domestic product (GDP) growth. In fundamental factor models, the factors are characteristics of the stock or the company that have been shown to affect asset returns, such as book-to-market or price-to-earnings ratios. A statistical factor model identifies the portfolios that best explain the historical cross-sectional returns or covariances among assets. The returns on these portfolios represent the factors.

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