All is attached in files. This is a midterm that should not take more than two hours. I am giving you four in order to have a 90+ grade. Thank you.
midterm_spring2019_q4q5q6.docx

midterm_q1.xlsx

midterm_q2.xlsx

midterm_q3.xlsx

1.pdf

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Portfolio Management
Spring 2019
MIDTERM – answers to questions 4 to 6
Question 4 (10 points)
a) AA
b) Bb
c) CC
Question 5 (25 points)
a) aaa
b) bbb
c) cccc
Question 6 (10 points)
a) aaa
b) bbb
Date
Cash inflow* ($) cash ($) stocks ($) total ($) Russell 3000 with div. Risk-free returns
31-Dec-11
10000
108
9892
10000
3449.92
0
30-Jan-12
0
110
11430
11540
3571.83
0
28-Feb-12
0
106
14759
14865
3732.76
0
31-Mar-12
0
123
14687
14810
3866.13
0
30-Apr-12
0
165
13970
14135
3810.91
0
31-May-12
0
165
13065
13230
3638.04
0
30-Jun-12
0
140
14756
14896
3728.72
0
31-Jul-12
0
130
13791
13921
3769.23
0
31-Aug-12
0
90
14512
14602
3850.65
0
30-Sep-12
0
120
14703
14823
3955.86
0
31-Oct-12
0
120
15663
15783
3878.72
0
30-Nov-12
0
120
17600
17720
3874.14
0
31-Dec-12
10000
254
28196
28450
3956.65
0
30-Jan-13
0
320
26089
26409
4179.75
0
28-Feb-13
0
321
25022
25343
4151.61
0
31-Mar-13
0
321
26023
26344
4370.52
0
30-Apr-13
0
354
26720
27074
4452.47
0
31-May-13
0
340
26839
27179
4648.17
0
30-Jun-13
0
401
25814
26215
4543.36
0
31-Jul-13
0
320
26833
27153
4752.44
0
31-Aug-13
0
330
26023
26353
4646.54
0
30-Sep-13
0
265
25626
25891
4799.28
0
31-Oct-13
0
253
28833
29086
5024.42
0
30-Nov-13
0
249
26752
27001
5131.71
0
31-Dec-13
0
310
24752
25062
5262.98
0
31-Jan-14
-5000
410
19543
19953
5105.86
0
28-Feb-14
0
102
21831
21933
5323.05
0
31-Mar-14
0
103
22267
22370
5388.41
0
30-Apr-14
0
117
22886
23003
5349.34
0
31-May-14
0
121
26524
26645
5516.72
0
30-Jun-14
0
145
27732
27877
5650.94
0
31-Jul-14
0
165
27955
28120
5669.33
0
31-Aug-14
0
124
28709
28833
5774.29
0
30-Sep-14
0
159
28864
29023
5775.62
0
31-Oct-14
0
189
28846
29035
5635.64
0
30-Nov-14
0
210
31376
31586
5897.86
0
31-Dec-14
0
230
31970
32200
6034.34
0
*CASH INFLOWS
TAKE PLACE
JUST BEFORE
THE END OF
EACH MONTH
Quarter 1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Label
Stock A
Stock B
Stock C
Stock D
Stock E
Stock F
Stock G
Stock H
Stock I
Stock J
Stock K
Stock L
Stock M
Stock N
Stock O
Stock P
Stock Q
Stock R
Stock S
Stock T
Mkt Cap just
before
quarter
beginning
100
3
0.5
10
16
0.9
1.5
6
2.5
10
16
3
5.5
1.5
6
2.5
6
5
2.5
0.4
Magic Formula
just befor e
Return
quarter
throughout
beginning
quarter
Label
0.030
0% Stock A
0.025
-18% Stock B
0.051
9% Stock C
0.031
16% Stock D
0.080
21% Stock E
0.044
11% Stock F
0.065
2% Stock G
0.024
-7% Stock H
0.055
14% Stock I
0.059
16% Stock J
0.075
21% Stock K
0.039
6% Stock L
0.021
-3% Stock M
0.022
2% Stock N
0.034
-7% Stock O
0.036
14% Stock P
0.037
-7% Stock Q
0.038
-7% Stock R
0.061
14% Stock S
0.044
5% Stock T
Quarter 2
Mkt Cap just
before
quarter
beginning
100
2.5
0.6
11
19
1
1.5
5.5
3
10
16
0.6
11
1.5
5.5
3
5.5
5.5
3
0.4
Quarter 2
Magic Formula
just befor e
Return
quarter
throughout
beginning
quarter
Label
0.036
-8% Stock A
0.042
10% Stock B
0.050
0% Stock C
0.039
3% Stock D
0.075
11% Stock E
0.039
15% Stock F
0.019
-11% Stock G
0.023
-3% Stock H
0.061
6% Stock I
0.077
16% Stock J
0.071
21% Stock K
0.045
0% Stock L
0.036
3% Stock M
0.011
-11% Stock N
0.022
-3% Stock O
0.029
6% Stock P
0.020
-3% Stock Q
0.020
-4% Stock R
0.046
6% Stock S
0.021
2% Stock T
Quarter 3
Mkt Cap just
before
quarter
beginning
100
2.5
0.6
11
19
1
1.5
5.5
3
6
2.5
0.6
11
1.5
5.5
3
5.5
5.5
3
0.4
Magic Formula
just befor e
Return
quarter
throughout
beginning
quarter
0.033
-2%
0.044
10%
0.029
0%
0.025
3%
0.049
11%
0.056
15%
0.029
-11%
0.023
-3%
0.028
6%
0.022
-7%
0.069
14%
0.051
0%
0.023
3%
0.017
-11%
0.019
-3%
0.033
6%
0.026
-3%
0.041
9%
0.038
6%
0.026
2%
Asset Classes
Cash
Domestic Bonds
Foreign Bonds
Domestic Equities
Foreign Equities
Mortages
Real Estate
Commodities
Private Equity
Hedge Funds
Total
Portfolio
Weight
Performance
10%
0.5%
22%
1.0%
10%
3.0%
17%
-0.5%
12%
2.0%
5%
5.0%
16%
1.0%
4%
-12.0%
3%
2.0%
1%
1.0%
100.00%
Benchmark
Weight
Performance
6%
0.1%
20%
3.0%
15%
2.0%
14%
-0.1%
16%
4.0%
3%
0.5%
20%
2.0%
4%
-10.0%
1%
1.0%
1%
3.0%
100.00%
Portfolio Management
Spring 2019
MIDTERM
Question 1 (30 points)
The spreadsheet MIDTERM_Q1 has monthly (end of month) data for an investment fund. Assume that client flows occur
just before the end of each month so that total dollar amounts at the end of each month include the client flows that
have just taken place. You are also given a Russell 3000 Total Return Index, and risk‐free returns. Assume the Russell
3000 Index is the Market Portfolio.
a) What is the annualized dollar‐weighted average return of the fund?
b) What is the annualized time‐weighted average return of the fund?
c) Which one, a) or b), is more informative about fund managers’ performance? Why?
d) What is the annualized Sharpe Ratio of fund?
e) What is the annualized CAPM alpha of the fund?
f)
Are fund managers doing a good job? Explain using your answers to previous items.
Question 2 (15 points)
The spreadsheet MIDTERM_Q2 has a hypothetical Universe of 20 stocks, labeled from A to T. You are given information
on stock returns, market cap, and Magic Formula. Magic Formula is a quantitative signal that can be easily calculated.
Your hypothesis is that high Magic Formula is associated with high future returns, on average. Consider a ranking system
based only on Magic Formula. Backtest the ranking system using the given Universe of stocks, a sample period of three
quarters, quarterly rebalancing, 5 buckets, and choose a market cap‐weighted Index as a benchmark. As Portfolio 123,
form equally‐weighted portfolios within each bucket.
a) Report the annualized (geometric average) return of each bucket and that of the benchmark.
b) Does Magic Formula forecast relative stock returns in the sample?
c) Why is the benchmark return so low compared to the bucket returns?
Question 3 (10 points)
The spreadsheet MIDTERM_Q3 has the investment performance of a large foundation over one year.
a) What is the active return of the foundation? (I.E., by how much it differs from its benchmark)
b) How much of the active return comes from Allocation and how much comes from Selection?
Question 4 (10 points)
You are a senior manager SMIF^2, a quantitative investing fund focused on US equities. Your analyst Yeswell Sortov
brings you a new quantitative signal he has just backtested. The signal is based on surveys among managers employed at
each Russell 3000 corporation. He claims that his backtest shows that stocks with high Managerial Satisfaction Ratings
(MSR) tend to be good investments on average. His analysis uses a list containing MSRs for all Russell3000 firms for the
year of 2018. He sorts the stocks on that list into three groups: HIGH MSR (top 30%), MEDIUM MSR (40%), and LOW
MSR (top 30%). Then he calculates equally‐weighted averages of stocks returns for those three groups over the ten year
period 2009‐2018. The results are below:
Group
HIGH MSR
MEDIUM MSR
LOW ESR
Average Return (2009‐2018)
7.5% per year
5 % per year
‐ 2% per year
As a senior manager, you have to analyze Sortov’s results.
a) Is there SPREAD and GRADATION?
b) Do you see problems with Sortov’s analysis? How would you fix it?
c) Can you see a specific reason why his results might be misleading? In other works, can you reason why results
come up the way they do even though ESR might not forecast relative returns? Explain.
Question 5 (25 points)
Can analyst buy/sell recommendations be used to forecast relative stock returns?
a) In Portfolio123, what is the stock factor AvgRec? (Check Full Description)
b) Backtest such factor in the MAX time period, 5 buckets, rebalancing every 4 weeks, and using a Custom Universe
of Russell3000 stocks for which AvgRec is non‐missing. Copy‐paste the back‐test results.
c) Can one forecast relative stock returns using AvgRec?
Question 6 (10 points)
a) Warren Buffet once wrote: “It’s common for promoters to cause a stock to become valued at 5 to 10 times its
true value, but rare to find a stock trading at 10 to 20% of its true value”. Does this make sense to you? Why?
Explain.
b) Explain why levered hedge funds that exploit security mispricings may not go “all‐in” in a certain opportunity
even if they are 100% sure that prices are wrong.

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