~Stock evaluation case study~ Apple :aapl Buffalo wild wings inc

CLU Business 521-Red Team: Brannen,
De Lorimier, Kaeberle, Pham
~ Data and Histograms
~ Descriptive Statistics
~ Time Plots
~ Derived Data
~ Correlation/Covariance
~ Comparing two sample averages

~Histograms help us visually understand trends of stocks by distributing data to show
common trends such as daily closing prices. Histograms allow investors to view the
level of performance and general idea of what to expect regarding past performance
measures.
 ~Coming up: Histograms of AAPL, BWLD, CVX, DNA, NWA, SHLD ~
What is lost in converting the raw data into
histograms?
What is gained?
About our stocks and their:
~ Mean
~ Variance
~ Standard deviation
~ Coefficient of variation
Stock Means:
AAPL:
101.92
CVX:
71.54
BWLD:
DNA:
26.79
79.71
NWA:
SHLD:
18.67
149.55
39.93
8.41
5.17
CVX:
NWA:
SHLD:
12.86
2.76
25.24
30.18%
31.4%
6.48%
CVX:
NWA:
SHLD:
17.97%
14.76%
16.88%
Standard Deviation:




AAPL:
BWLD:
DNA:
Coefficient Variation:
AAPL:
BWLD:
DNA:

Time plots are another simple tool for comparing price series over time...



~ How we analyze our stocks returns.
~ Mean return, variance, and standard of their
returns.
~ What is risky what is not????

CONSIDERATIONS FOR BASIS OF DATA:

Substituted U. S. Airways (LCC) for Northwest Airlines (NWA)
 Bankruptcy prior to May 2007




Time Span of the Stock Data
Time Frame for Conducting the Analysis
Professional Statistical Analysis Norms
REASONS FOR OUR BASIS SELECTION:

Quarterly Returns Eliminated
 Sample Size (n = 8)
 Matching Time Frame and Return period

Daily Returns Eliminated
 Sample Size (n = 525)
 Time Frame for Conducting Analysis

Monthly or Weekly?
 Sample Size (n=25 vs. 108)
 Time Span of Data and Analysis
 Professional Norms for Returns
Stock / Statistic Value
Mean *
(Monthly
Returns)
Variance
(Monthly
Returns)
Standard Deviation
(Monthly Returns)
Standard Deviation
(Monthly Price)
AAPL
3.067
149.262
12.217
41.71
BWLD
2.797
194.973
13.963
8.11
CVX
1.671
21.520
4.639
12.75
DNA
-0.692
16.014
4.002
5.22
LCC
-1.697
166.253
12.894
12.87
SHLD
-0.043
76.134
8.725
26.52






BWLD
LCC
AAPL
SHLD
CVX
DNA
Buffalo Wild Wings
Northwest Airlines
Apple Computer
Sears Holding
Chevron
Genentech
13.96
12.89
12.22
8.73
4.64
4.00
Risky
Safe







Symbol
AAPL
SHLD
CVX
DNA
BWLD
LCC
Stock
Apple Computer
Sears Holding
Chevron
Genentech
Buffalo Wild Wings
Northwest Airlines
SD Current Price (Monthly)
41.71
$133.75
26.52
$108.31
12.75
$81.90
4.00
$70.81
12.87
$25.35
12.87
$15.39
y = 2.915x + 1.965
-8
-6
-4
-2
30
20
10
0
-10 0
-20
-30
-40
Buffalo Wild Wings Beta
2
4
6
BLWD Return
APPL Return
Apple Computer Beta
y = 1.453x + 2.247
-8
-6
-4
-2
S$P Return
AAPL Return
Linear (AAPL Return)
BWLD Return
-6
-4
-2
10
5
5
2
4
6
-10
-8
-6
-4
-2
y = -0.0902x - 0.6579
-15
Linear (Cvx Return)
DNA Return
20
-2
-20
0
2
4
6
SHLD Return
Lcc Return
-4
4
6
-10
Linear (DNA Return)
10
0
-8
-6
-4
-2
S&P Return
Linear (Retrun LCC)
-10 0
-20
-40
Retrun LCC
6
20
0
-6
4
SHLD Beta
40
-8
2
S&P Return
LCC Beta
y = 0.8972x - 2.0357
0
-5 0
-15
S&P Return
Cvx Return
6
Linear (BWLD Return)
10
0
-5 0
4
DNA Beta
DNA Return
CVX Return
-8
2
S&P Return
Chevron Beta
y = 1.0936x + 1.2571
40
30
20
10
0
-10 0
-20
-30
-30
2
y = 1.0137x - 0.4265
S&P Return
SHLD Return
Linear (SHLD Return)
Stock
AAPL
BWLD
CVX
SHLD
LCC
DNA
Beta
2.915
1.454
1.094
1.014
0.897
-0.090
Yahoo
3.06
1.40
1.35
0.61
0.90
-0.40
Risky
Reverse

Let’s assume you invested $1,000 into each stock at the close of the market on
January 3,2006. Based on the stock prices, what would each stock be worth on
January 31, 2008? What would your portfolio be worth?
Stock prices at close
AAPL
BWLD
CVX
DNA
LCC
SHLD
January 3, 2006
$74.75
33.95
59.08
94.00
37.45
117.08
January 31, 2008
$135.36
25.17
83.25
70.16
13.84
110.49
At the close on January 31, 2008, each stock would be worth:
AAPL
BWLD
CVX
DNA
LCC
SHLD
$1,810.84
$1,482.77
$1,409.11
$746.38
$369.56
$943.71
With this given information, we calculate that our total portfolio would
be worth $6,762.37, giving us a profit of $762.37.
As calculated in our excel spreadsheet, our portfolio has a
standard deviation of 1,038.01 and a coefficient of variation
of 14.25%. This compares to individual stocks:
AAPLE
BWLD
CVX
DNA
LCC
SHLD
SD
557.83
490.80
218.26
58.76
337.69
250.20
COV
40.53%
31.38%
17.96%
6.86%
33.63%
19.47%
Difference from Portfolio
SD
-480.18
-547.21
-819.75
-979.25
-700.32
-787.81
COV
26.28%
17.13%
3.71%
-7.39%
19.38%
5.22%
Portfolio Beta
-0.1000

0.2000
0.1500
0.1000
0.0500
0.0000
-0.0500 -0.05000.0000
-0.1000
-0.1500
-0.2000
y = 1.5519x + 0.0003
Series1
0.0500
Linear
Weighted average beta: (2.915 + 1.454 + 1.094 - 0.09 + 0.897 + 1.014)/6 = 1.214
Set up a model under the assumption that the returns of your stocks in
those industries (AAPL & DNA) are simple random samples from the
populations of interest and use the model to find a 95% confidence
interval for the difference in average returns of the two portfolios and a
significance test of the hypothesis that this difference is zero. What do
you conclude? Are the returns of tech stocks and biotech/pharma
stocks different from each other? Explain.



Confidence Interval = -0.01 to 0.10
P-value = between 0.10 and 0.20
P-value > 0.05; “Do not reject” the null hypothesis
Do you think it is reasonable to assume that the
data are representative of the populations of all
stock price data for the two industries? If not, what
do you think the effect would be on the inferences
you draw of any biases in the samples presented?