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

ROM = 20.0% +1.0(FGDP) + 1.4(FQS) + εOM
RGAR = 15.0% +0.5(FGDP) + 0.8 (FQS) + εGAR

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

A)

20.96%.
B)

18.0%.
C)

19.96%.



Since the expected factor suprises and expected errors are all 0 by definition, the macroeconomic factor model for the portfolio is:

RP = [(0.6)(20.0%) + (0.4)(15.0%)]
+ [(0.6)(−1.0) + (0.4)(−0.5)] (0)
+ [(0.6)(1.4) + (0.4)(0.8)] (0)
+ [(0.6) εOM + (0.4)εGAR]

= 18.0% −0.80(0) + 1.16(0) + (0.6)(0) + (0.4)(0)


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

The expected return on stock j is 12%.
B)

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

F1 and F2 represent priced risk.



In a macroeconomic 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.

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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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Assume you are considering forming a common stock portfolio consisting of 25% Stonebrook Corporation (Stone) and 75% Rockway Corporation (Rock). As expressed in the two-factor returns models presented below, both of these stocks’ returns are affected by two common factors: surprises in interest rates and surprises in the unemployment rate.
RStone = 0.11 + 1.0FInt + 1.2FUn + εStone
RRock = 0.13 + 0.8FInt + 3.5FUn + εRock

Assume that at the beginning of the year, interest rates were expected to be 5.1% and unemployment was expected to be 6.8%. Further, assume that at the end of the year, interest rates were actually 5.3%, the actual unemployment rate was 7.2%, and there were no company-specific surprises in returns. This information is summarized in Table 1 below:

Table 1: Expected versus Actual Interest Rates and Unemployment Rates

Actual

Expected

Company-specific returns surprises


Interest Rate

0.053

0.051

0.0


Unemployment Rate

0.072

0.068

0.0

What is the expected return for Stonebrook?
A)
11.0%.
B)
13.0%.
C)
13.2%.



The expected return for Stonebrook is simply the intercept return (ai) of 0.11, or = 11.0%. (Study Session 18, LOS 66.j, k)


What is the expected return for Rockway?
A)
13.0%.
B)
17.3%.
C)
11.0%.



The expected return for Rockway is simply the intercept term (ai) of 0.13, or 13%. (Study Session 18, LOS 66.j, k)


What is the portfolio’s sensitivity to interest rate surprises?
A)
0.95.
B)
0.25.
C)
0.85.



The portfolio composition is 25% Stonebrook and 75% Rockway. The interest rate sensitivities for Stonebrook and Rockway are 1.0 and 0.8, respectively. Thus, the portfolio's sensitivity to interest rate surprises is: (0.25)(1.0) + (0.75)(0.8) = 0.85. (Study Session 18, LOS 66.k)

What is the portfolio’s sensitivity to unemployment rate surprises?
A)
2.625.
B)
1.775.
C)
2.925.



The portfolio composition is 25% Stonebrook and 75% Rockway. The unemployment rate sensitivities for Stonebrook and Rockway are 1.2 and 3.5, respectively. Thus, the portfolio's sensitivity to unemployment rate surprises is: (0.25)(1.2) + (0.75)(3.5) = 2.925. (Study Session 18, LOS 66.k)

What is the expected return of the portfolio?
A)
12.5%.
B)
11.5%.
C)
2.75%.



The portfolio composition is 25% Stonebrook and 75% Rockway. The expected returns for Stonebrook and Rockway are 11% and 13%, respectively. Thus, the portfolio’s expected return is (0.25)(0.11) + (0.75)(0.13) = 12.5%. (Study Session 18, LOS 66.k)

What is the predicted return for Stonebrook?
A)
0.40%.
B)
11.68%.
C)
11.00%.


The predicted return uses the unemployment and interest rate surprises as follows:
The returns for a stock that are correlated with surprises in interest rates and unemployment rates can be expressed using a two-factor model as:
Ri = ai+ bi,1FInt + bi,2FUn + εi

where:
Ri = the return on stock i
ai = the expected return on stock i
bi,1 = the factor sensitivity of stock i to unexpected changes in interest rates
FInt = unexpected changes in interest rates (the interest factor) = .053 − .051 = .002
bi,2 = the factor sensitivity of stock i to unexpected changes in the unemployment rate
FUn = unexpected changes in the unemployment rate (the unemployment rate factor) = .072 − .068 = .004
εi = a mean-zero error term that represents the part of asset i’s return not explained by the two factors.
Thus the predicted return is: 0.11 + (1.0)(0.002) + (1.2)(0.004) = 0.1168 or 11.68% (Study Session 18, LOS 66.j)

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Examples of macroeconomic variables that create systematic risk include:
A)
all of these choices are correct.
B)
variability in the growth of the money supply.
C)
changes in GDP growth rates.



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)

fundamental factor model.
B)

covariance factor model.
C)

statistical 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)
10.17%.
B)
12.89%.
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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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)

macroeconomic factor model.
C)

statistical 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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Carla Vole has developed the following macroeconomic models:
  • Return of Stock A = 6.5% + (9.6 × productivity) + (5.4 × growth in number of businesses)
  • Return of Stock B = 18.7% + (2.5 × productivity) + (3.7 × growth in number of businesses)

Assuming a portfolio contains 60% Stock A and 40% Stock B, the portfolio’s sensitivity to productivity is closest to:
A)
4.72.
B)
6.76.
C)
5.34.



To calculate the portfolio’s factor sensitivity, we need the weighted average of the factor sensitivity of each stock: (9.6 × 60%) + (2.5 × 40%) = 6.76.

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