Date SP500 DJIA NASDAQ Apple RSP500 RDJIA RNASDAQ RAPPLE 11/1/15 2080.40991 17719.9199 5108.66992 115.725212 -1.7685659 -1.6781788...
| Date | SP500 | DJIA | NASDAQ | Apple | RSP500 | RDJIA | RNASDAQ | RAPPLE |
| 11/1/15 | 2080.40991 | 17719.9199 | 5108.66992 | 115.725212 | -1.7685659 | -1.6781788 | -2.0020235 | -11.67903 |
| 12/1/15 | 2043.93994 | 17425.0293 | 5007.41016 | 102.969025 | -5.2067617 | -5.6591722 | -8.1834481 | -7.822354 |
| 1/4/16 | 1940.23999 | 16466.3008 | 4613.9502 | 95.221397 | -0.4136906 | 0.30439657 | -1.2211362 | -0.1288313 |
| 2/1/16 | 1932.22998 | 16516.5 | 4557.9502 | 95.098801 | 6.39049904 | 6.83620216 | 6.61901521 | 11.9746127 |
| 3/1/16 | 2059.73999 | 17685.0898 | 4869.8501 | 107.196381 | 0.26957617 | 0.49945931 | -1.9593821 | -15.073119 |
| 4/1/16 | 2065.30005 | 17773.6406 | 4775.35986 | 92.197342 | 1.52083667 | 0.07625576 | 3.55241851 | 6.93142781 |
| 5/2/16 | 2096.94995 | 17787.1992 | 4948.04981 | 98.814621 | 0.09105065 | 0.79956894 | -2.1527315 | -4.3596423 |
| 6/1/16 | 2098.86011 | 17929.9902 | 4842.66992 | 94.599213 | 3.49904331 | 2.7626575 | 6.38830569 | 8.62352802 |
| 7/1/16 | 2173.6001 | 18432.2402 | 5162.12988 | 103.11908 | -0.1219987 | -0.1702782 | 0.9848486 | 2.33764785 |
| 8/1/16 | 2170.94995 | 18400.8809 | 5213.22022 | 105.558037 | -0.1235213 | -0.5052199 | 1.87706639 | 6.34482053 |
| 9/1/16 | 2168.27002 | 18308.1504 | 5312 | 112.472542 | -1.9616837 | -0.9093499 | -2.3400406 | 0.43249806 |
| 10/3/16 | 2126.1499 | 18142.4199 | 5189.14014 | 112.960037 | 3.62877172 | 5.05544641 | 3.62467864 | -1.5433945 |
| 11/1/16 | 2204.71997 | 19083.1797 | 5380.68018 | 111.230003 | . | . | . | . |
- Regress monthly returns of Apple on: a) monthly returns of SP500, b) monthly returns of DJIA and c) monthly returns of NASDAQ. (I have already calculated returns for you, see last 4 columns). Note, we have 3 regression lines: Apple returns as dependent variable and returns of SP500, returns of DJIA and returns of NASDAQ as independent variable one at the time.
- Make a table in which you show intercepts, slopes, and R-squares of all three regression lines (i.e. your table contains 9 numbers: 3 intercepts, 3 slopes, and 3 R-squares).
- In 6 lines discuss which market index (SP500, or DJIA, or NASDAQ) explains the variations in Apple returns better and why?
Please include excel file so I can see how it was done.
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Date
SP500
DJIA
NASDAQ
Apple
RSP500
RDJIA
RNASDAQ
RAPPLE
11/1/15
2080.40991
17719.9199
5108.66992
115.725212
-1.7685659
-1.6781788...
Consider time series yt , defined as the daily percentage change in SP500 index. A researcher...
Consider time series yt , defined as the daily
percentage change in SP500 index. A researcher estimated the
following model:
(a) There is one partial
autocorrelation coefficient that you can find from the estimation
result. What is the value of it? What is order (k ) of
it?
(b) Test the null hypothesis that the partial autocorrelation
coefficient that you have is zero against the alternative that it
is not zero.
Dependent Variable: GROWTH Method: Least Squares Date: 03/08/15 Time:...
3) 6 11 12 15 17 19 TO 7 12 :12 Use least-squares regression to fit a straight line to the list o...
please solve it with codes in Matlab
3) 6 11 12 15 17 19 TO 7 12 :12 Use least-squares regression to fit a straight line to the list of data in the accompanying table. Give the slope and the intercept Compute the correlation coefficient Give an estimation of y for r 10 Slope: Intercept: Your answer: Your Answer Page 1 of 1
3) 6 11 12 15 17 19 TO 7 12 :12 Use least-squares regression to fit a...
Date DLT Close ASX Index 28/12/14 0.145 5435.899902 4/1/15 0.135 5465.600098 11/1/15 0.1 5299.200195 18/1/15 0.097...
Date DLT Close ASX Index 28/12/14 0.145 5435.899902 4/1/15 0.135 5465.600098 11/1/15 0.1 5299.200195 18/1/15 0.097 5501.799805 25/1/15 0.098 5588.299805 1/2/15 0.082 5820.200195 8/2/15 0.072 5877.5 15/2/15 0.076 5881.5 22/2/15 0.1 5928.799805 1/3/15 0.14 5898.899902 8/3/15 0.135 5814.5 15/3/15 0.12 5975.5 22/3/15 0.1 5919.899902 29/3/15 0.1 5898.600098 5/4/15 0.1 5968.399902 12/4/15 0.091 5877.899902 19/4/15 0.115 5933.299805 26/4/15 0.11 5814.399902 3/5/15 0.215 5634.600098 10/5/15 0.22 5735.5 17/5/15 0.25 5664.700195 24/5/15 0.255 5777.200195 31/5/15 0.185 5498.5 7/6/15 0.195 5545.299805 14/6/15 0.18 5597...
Exercise 1. For this exercise use the bdims data set from the openintro package. Type ?bdims to r...
Exercise 1. For this exercise use the bdims data set from the openintro package. Type ?bdims to read about this data set in the help menu. Of interest are the variables hgt (height in centimeters), wgt (weight in kilograms), and sex (dummy variable with 1-male, 0-female). Since ggplotO requires that a categorical variable be coded as a factor type in R, run the following code: library (openintro) bdíms$sex2 <-factor (bdins$sex, levels-c (0,1), labels=c('F', 'M')) (a) Use ggplot2 to make a...
B =X Y 1 17 3 15 5 10 7 7 9 1 HW 1 For...
B =X Y 1 17 3 15 5 10 7 7 9 1 HW 1 For the date above 1-1. Construct an Analysis of Regression table, below (Below is the regression table I made) Source of Variation Degrees of Freedom, d.f. Sums of Squares, SS Mean Squares, MS F, FR, MSR/MSE Total 4 164 Regression 1 160 160 120.3 Residual 3 4 1.33 (I need a help with this) 1-2. Test B= 0 with a = 1%
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Garfield Company manufactures a popular brand of dog repellant known as Dog Gone It, which it...
Garfield Company manufactures a popular brand of dog repellant known as Dog Gone It, which it sells in gallon-size bottles with a spray attachment. The majority of Garfield's business comes from orders placed by homeowners who are trying to keep neighborhood dogs out of their yards. Garfield's operating information for the first six months of the year follows: Number of Operating Month Bottles Sold Cost January 1,060 $10,770 February 1,460 15,670 March 1,850 15,920 April 2,420 19,540 May 3,420 27,820...
Consider time series yt , defined as the daily
percentage change in SP500 index. A researcher estimated the
following model:
(a) There is one partial
autocorrelation coefficient that you can find from the estimation
result. What is the value of it? What is order (k ) of
it?
(b) Test the null hypothesis that the partial autocorrelation
coefficient that you have is zero against the alternative that it
is not zero.
Dependent Variable: GROWTH Method: Least Squares Date: 03/08/15 Time:...
please solve it with codes in Matlab
3) 6 11 12 15 17 19 TO 7 12 :12 Use least-squares regression to fit a straight line to the list of data in the accompanying table. Give the slope and the intercept Compute the correlation coefficient Give an estimation of y for r 10 Slope: Intercept: Your answer: Your Answer Page 1 of 1
3) 6 11 12 15 17 19 TO 7 12 :12 Use least-squares regression to fit a...
Exercise 1. For this exercise use the bdims data set from the openintro package. Type ?bdims to read about this data set in the help menu. Of interest are the variables hgt (height in centimeters), wgt (weight in kilograms), and sex (dummy variable with 1-male, 0-female). Since ggplotO requires that a categorical variable be coded as a factor type in R, run the following code: library (openintro) bdíms$sex2 <-factor (bdins$sex, levels-c (0,1), labels=c('F', 'M')) (a) Use ggplot2 to make a...
11 Garfield Company manufactures a popular brand of dog repellant known as DogGone It, which it sells in gallon-size bottles with a spray attachment. The majority of Garfield's business comes from orders placed by homeowners who are trying to keep neighborhood dogs out of their yards. Garfield's operating information for the first six months of the year follows: 0.33 points Skipped Month January February March April May June Number of Bottles Sold 970 1,390 1,820 2,410 3,550 3,750 Operating Cost...
The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data (i.e., n = 16) with the following results: Regression Statistics Multiple R 0.802 R Square 0.643 Adjusted R Square 0.618 Standard Error SYX 0.9224 Observations 16 ANOVA df Regression 1 Error 14 Total 15 SS MS F Sig.F 31.497 21.497 25.27 0.000 21.912 0.851 53.409 Predictor...
17. Because Apple needs to bring their books up to date before the New Year, which con willed to be updated on this day? What type of entry is this? ACCT 201 Supplemental struction Analyzing Journalining and Posting Business Transactions Journalise the following tractions for the month of December Allerwan, post all of the r ations in the Inter and prepare a trial balance 1. Apple receives $30.000 cash from Mr. Brown, a local San Marcos resident, in exchange for...
Garfield Company manufactures a popular brand of dog repellant known as Dog Gone It, which it sells in gallon-size bottles with a spray attachment. The majority of Garfield's business comes from orders placed by homeowners who are trying to keep neighborhood dogs out of their yards. Garfield's operating information for the first six months of the year follows: Number of Operating Month Bottles Sold Cost January 1,060 $10,770 February 1,460 15,670 March 1,850 15,920 April 2,420 19,540 May 3,420 27,820...
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