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Oregon State University
College of Business
Department of Accounting, Finance and Information Management
BA 443
Midterm Examination
Instructor: Prem Mathew
Date: April 30, 2008
Time allowed: 1 hour and 50 minutes
Points: 50 (equivalent to 27% of the total course evaluation)
Student name:
___________________________________
Instructions:
1)
Attempt all questions.
2)
You may separate the formula sheets and additional pages at the end of the exam.
If you have work you would like to turn in on the additional pages, please slip it
inside the exam when finished.
Multiple Choice. Circle the correct answer. Each question is worth 1 point.
NOTE: In FALL 2008, we have not covered MC 7 and SA 5 yet.
1. In a value weighted index
a) Exchange rate fluctuations have a large impact.
b) Exchange rate fluctuations have a small impact.
c) Large companies have a disproportionate influence on the index.
d) Small companies have an exaggerated effect on the index.
e) None of the above.
2. Research has shown that the asset allocation decision explains % of the variation in
fund returns across all funds, and % of the variation in returns for a particular fund
over time.
a)
b)
c)
d)
e)
90 and 100.
100 and 40.
90 and 40.
40 and 100.
40 and 90.
3. ____________ is an appropriate objective for investors who want their portfolio to
grow in real terms, i.e., exceed the rate of inflation.
a) Capital preservation
b) Capital appreciation
c) Portfolio growth
d) Value additivity
e) Nominal preservation
4. The policy statement may include a __________ against which a portfolio's or
portfolio manager's performance can be measured.
a)
Milestone
b)
Benchmark
c)
Landmark
d)
Reference point
e)
Market pair
5. Value stocks would have the following characteristics
a)
Low book value/market value, low price/earnings.
b)
High book value/market value, low price/earnings.
c)
Low book value/market value, high price/earnings
d)
High book value/market value, high price/earnings
6. Which of the following is not a technique for constructing a passive index portfolio?
a)
Full replication
b)
Sampling
c)
Quadratic programming
d)
Linear programming
e)
None of the above (that is, all are techniques for constructing a passive
index portfolio)
7. An examination of the relationship between stock prices and the economy has shown
that the relationship is
a)
Weak, and that stock prices turn after the economy does.
b)
Nonexistent.
c)
Strong , and that stock prices turn after the economy does.
d)
Strong, and that stock prices turn before the economy does.
e)
Weak, and that stock prices turn before the economy does.
8. Under the risk premium approach to determining expected returns for fixed income
asset classes and securities, the difference between the real risk-free rate and an
intermediate Treasury Bond asset class is captured in the following premiums:
a) Inflation premium
b) Maturity premium
c) Inflation and maturity premiums
d) Inflation, maturity and tax premiums
e) Inflation, maturity and illiquidity premiums
9. The table below provides returns on a portfolio along with returns for the
corresponding benchmark index for the past eight quarters. The table also provides
the difference between portfolio returns and the benchmark index, the average of
these differences over the past eight quarters and the standard deviation of these
differences.
Period
1
2
3
4
5
6
7
8
Portfolio
0.05
-0.036
0.022
0.012
-0.003
-0.023
0.089
-0.008
Index
0.027
-0.046
0.019
0.022
-0.001
-0.03
0.081
0.006
Average
SD
The annualized tracking error for this period is
a)
2.36%
b)
4.08%
c)
2.89%
d)
3.33%
e)
1.18%
Difference
0.023
0.010
0.003
-0.010
-0.002
0.007
0.008
-0.014
0.003
0.011789
10. Based on an unweighted (or equal weighted) index using arithmetic means, what is
the percentage change in the index from Day T to Day T+1. Assume a base index
value of 100 on Day T.
Companies
1
2
3
4
a)
b)
c)
d)
e)
5.35%
7.48%
9.93%
6.33%
None of the above
Number of shares
Closing Prices
(per share)
outstanding
2,000
7,000
5,000
4,000
Day T
$30.00
55.00
20.00
40.00
Day T + 1
$25.00
60.00
25.00
45.00
Short Answer.
1. (6 points) Mr. Semih is an analyst at PortMgmt, Inc. In a recent presentation to the
managing directors of the firm, he made the following comments. “Noting that year-end
holiday sales have been weak over the past several years, I believe that current
expectations should be likewise muted. In fact, just last week, I had an occasion to visit
Macy’s and noticed that the number of shoppers seemed quite low. The last time I saw a
store with so little pedestrian traffic was in December 2000, and that coincided with one
of the worst holiday sales periods in the past two decades. Thus, there will be no overall
year-over-year retail sales growth this holiday season.”
Identify and describe three psychological traps that may be interfering with the creation
of Mr. Semih’s forecasts.
2. (9 points) Use the following information to answer the questions below.
Asset allocation
X
Y
Z
Expected return
12%
8.5%
5.5%
Standard deviation
19%
15%
9%
a. Client A has a risk aversion parameter of 5. Recommend an asset allocation for him.
b. Client B has a spending policy of 3.5% and therefore would like to choose an
allocation that minimizes the probability that the portfolio return will be less than that.
Recommend an asset allocation for her.
c. Client C needs to spend 5% from her portfolio annually. She anticipates that inflation
will be 2.4% annually and she incurs expenses of 0.6% a year in investing her portfolio.
Which asset allocations satisfy her return requirement?
3. (10 points) As a junior analyst at your firm, you have been assigned the task of
developing expected returns and a covariance matrix for two asset classes, a U.S. equity
asset class and a U.S. corporate fixed income asset class, that your firm invests their
clients’ money in. This analysis will compliment analyses performed by other analysts to
develop portfolios for your firm’s clients. Your firm uses a multifactor model approach to
develop these expectations.
Multifactor model specifics:
You identify two factors that you believe drive all asset class returns. The returns and
standard deviations of these two factors are given below. The covariance between the
factors is 0.011.
Factor 1
Factor 2
E(R)
8%
12%
Std Dev.
10%
20%
You run a regression for each asset class using these two factors and determine that the
factor sensitivities are as follows:
Betas
Factor 1
Factor 2
Equity AC
0
1.3
Fixed Income AC
1.1
0
a. Calculate the two asset classes expected returns.
b. Calculate a covariance matrix for the two asset classes.
c. Considering this information will be used in conjunction with analyses of other
analysts, describe one forecasting challenge that you should keep in mind when
developing asset class and factor expected returns.
4. (8 points) You use a Global Investable Market (GIM) to determine expected returns
for two asset classes, U.S. equities and U.S. real estate. The Sharpe ratio for the GIM is
0.28. U.S. equities are 80% integrated with the GIM and U.S. real estate asset class is
70% integrated. The correlation between U.S. equity and the GIM is 0.6 and the
correlation between U.S. real estate and the GIM is 0.35. The risk-free rate is 4%.
Historical information for the two asset classes is given below.
U.S. Equity AC
U.S. Real Estate AC
Std. Dev
25%
16%
a. Using the ICAPM, what are the expected returns for the two asset classes? Note: You
do not need to calculate a covariance matrix.
b. Describe one way in which the ICAPM is superior to the traditional CAPM.
5. (7 points) The business cycle can be described as having five phases. In terms of
consumer and business confidence, economic growth, monetary policy and inflation,
describe two of these phases. Which asset classes would you expect to perform well in
these two phases and why?
Extra credit. 2 points maximum.
Starting with the CAPM equation ( E ( Ri )  RF  i E ( RM )  RF  ), show how we can
derive the ICAPM expected risk premium equation for a completely segmented market.
BA 443 Midterm Formula Sheet
Return Objectives (from IPS):
Incorporating spending rate, inflation rate and expenses:
Return  (1  SR)(1  IR)(1  exp) - 1
Multiperiod return calculation:
CGR  E ( AR)  0.5 * 2
Risk objectives (from IPS):
Based on mean-variance utility:
U m  E( Rm )  0.005RA * m
2
Shortfall Risk: Roy’s safety first criterion:
SFRatio 
E ( R p )  RL
p
Adding asset classes to portfolio:
E ( Rnew )  RF
 new
 E ( R p )  RF


p


Corr ( Rnew, R p )


Tracking error:
TE    P
 
T
Where
 
t 1
t


2
and
 t  R pt  Rbt
T 1
Index calculations:
N
Price-weighted:
Indext  
i 1
Pit
Dadj
N
Value-weighted
Indext 
P Q
i 1
N
it
it
P Q
i 1
ib
ib
* Beginning Index Value
Formulating Capital Market Expectations:
Multifactor models:
Rit  ai  bi1F1t  bi 2 F2t  ...  biK FKt  eit
General Expression:
Calculating expected returns, variance, correlations with two factors and
two asssets:
M1t  b11F1t  b12 F2t
Expected return:
Variance:
M ii  bi21Var( F1 )  bi22Var( F2 )  2bi1bi 2Cov( F1, F2 )
Covariance: M ij  bi1b j1Var( F1 )  bi 2b j 2Var( F2 )  (bi1b j 2  bi 2b j1 )Cov( F1, F2 )
Calculating expected returns with four factors (Mkt, SMB, HML, MOM)
E ( R)  RFR  b1 * ( MKT  RFR )  b2 * SMB  b3 * HML  b4 * MOM
Discounted Cash Flow Model:
Expected Return:
E ( Re ) 
D0 (1  g )
g
P0
Risk Premium Approach:
Fixed Income expected return:
E ( Rb )  real risk free interest rate inflation premium 
default risk premium  illiquidit y premium  maturity premium 
tax premium
Equity expected return:
E ( Re )  30  yr T - bond rate  equity risk premium
ICAPM Approach:
Expected Return:
E ( Ri )  RF  i E ( RM )  RF 
where
i  Cov( Ri , RM ) / Var ( RM )
Expected Risk premium assuming fullly integrated market:
 E ( RM )  RF
E ( Ri )  RF   i i ,M 
M




Expected Risk premium assuming completely segmented market:
 E ( RM )  RF
E ( Ri )  RF   i 
M




Expected Return assuming partially integrated market:
E ( Ri )  RF  (deg of integratio n * asset risk premium if fully integrated )
 ((1  degree of integratio n) * segmented risk premium)
Covariance of two assets:
2
Cov(AC1, AC2)   AC1 *  AC 2 *  mkt
Beta, covariance, and correlation
a 
Cov (rmkt , ra )
2
 mkt

 a ,mkt *  a
 mkt
Cov(rmkt , ra )  Corr(rmkt , ra ) * a * mkt
Taylor rule to predict interest rates:
Roptimal  Rneutral  [0.5 * (GDPg forecast  GDPgtrend )  0.5 * ( I forecast  I t arg et )]