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 |
21/6/15 | 0.145 | 5545.899902 |
28/6/15 | 0.175 | 5538.299805 |
5/7/15 | 0.145 | 5492 |
12/7/15 | 0.145 | 5670.100098 |
19/7/15 | 0.155 | 5566.100098 |
26/7/15 | 0.135 | 5699.200195 |
2/8/15 | 0.145 | 5474.799805 |
9/8/15 | 0.15 | 5356.5 |
16/8/15 | 0.15 | 5214.600098 |
23/8/15 | 0.145 | 5263.600098 |
30/8/15 | 0.12 | 5040.600098 |
6/9/15 | 0.12 | 5071.100098 |
13/9/15 | 0.135 | 5170.5 |
20/9/15 | 0.16 | 5042.100098 |
27/9/15 | 0.125 | 5052 |
4/10/15 | 0.15 | 5279.700195 |
11/10/15 | 0.145 | 5268.200195 |
18/10/15 | 0.16 | 5351.600098 |
25/10/15 | 0.13 | 5239.399902 |
1/11/15 | 0.13 | 5215 |
8/11/15 | 0.12 | 5051.299805 |
15/11/15 | 0.12 | 5256.100098 |
22/11/15 | 0.135 | 5202.600098 |
29/11/15 | 0.14 | 5151.600098 |
6/12/15 | 0.145 | 5029.5 |
13/12/15 | 0.12 | 5106.700195 |
20/12/15 | 0.15 | 5207.600098 |
27/12/15 | 0.135 | 5295.899902 |
3/1/16 | 0.155 | 4990.799805 |
10/1/16 | 0.175 | 4892.799805 |
17/1/16 | 0.17 | 4916 |
24/1/16 | 0.195 | 5005.5 |
31/1/16 | 0.195 | 4976.200195 |
7/2/16 | 0.18 | 4765.299805 |
14/2/16 | 0.185 | 4952.799805 |
21/2/16 | 0.175 | 4880 |
28/2/16 | 0.16 | 5090 |
6/3/16 | 0.165 | 5166.399902 |
13/3/16 | 0.19 | 5183.100098 |
20/3/16 | 0.165 | 5084.200195 |
27/3/16 | 0.175 | 4999.399902 |
3/4/16 | 0.16 | 4937.600098 |
10/4/16 | 0.175 | 5157.5 |
17/4/16 | 0.16 | 5236.399902 |
24/4/16 | 0.145 | 5252.200195 |
1/5/16 | 0.15 | 5292 |
8/5/16 | 0.16 | 5329 |
15/5/16 | 0.155 | 5351.299805 |
22/5/16 | 0.165 | 5405.899902 |
29/5/16 | 0.155 | 5318.899902 |
5/6/16 | 0.15 | 5312.600098 |
12/6/16 | 0.145 | 5162.700195 |
19/6/16 | 0.13 | 5113.200195 |
26/6/16 | 0.135 | 5246.600098 |
3/7/16 | 0.14 | 5230.5 |
10/7/16 | 0.155 | 5429.600098 |
17/7/16 | 0.14 | 5498.200195 |
24/7/16 | 0.089 | 5562.299805 |
31/7/16 | 0.084 | 5497.399902 |
7/8/16 | 0.085 | 5530.899902 |
14/8/16 | 0.078 | 5526.700195 |
21/8/16 | 0.069 | 5515.5 |
28/8/16 | 0.079 | 5372.799805 |
4/9/16 | 0.087 | 5339.200195 |
11/9/16 | 0.098 | 5296.700195 |
18/9/16 | 0.097 | 5431.299805 |
25/9/16 | 0.088 | 5435.899902 |
2/10/16 | 0.095 | 5467.399902 |
9/10/16 | 0.091 | 5434 |
16/10/16 | 0.082 | 5430.299805 |
23/10/16 | 0.07 | 5283.799805 |
30/10/16 | 0.07 | 5180.799805 |
6/11/16 | 0.052 | 5370.700195 |
13/11/16 | 0.06 | 5359.399902 |
20/11/16 | 0.062 | 5507.799805 |
27/11/16 | 0.046 | 5444 |
4/12/16 | 0.047 | 5560.600098 |
11/12/16 | 0.048 | 5532.899902 |
18/12/16 | 0.045 | 5627.899902 |
25/12/16 | 0.047 | 5665.799805 |
1/1/17 | 0.044 | 5755.600098 |
8/1/17 | 0.045 | 5721.100098 |
15/1/17 | 0.036 | 5654.799805 |
22/1/17 | 0.035 | 5714 |
29/1/17 | 0.041 | 5621.600098 |
5/2/17 | 0.042 | 5720.600098 |
12/2/17 | 0.044 | 5805.799805 |
19/2/17 | 0.041 | 5739 |
26/2/17 | 0.046 | 5729.600098 |
5/3/17 | 0.046 | 5775.600098 |
12/3/17 | 0.045 | 5799.600098 |
19/3/17 | 0.044 | 5753.5 |
26/3/17 | 0.038 | 5864.899902 |
2/4/17 | 0.039 | 5862.5 |
9/4/17 | 0.036 | 5889.899902 |
16/4/17 | 0.036 | 5854.100098 |
23/4/17 | 0.038 | 5924.100098 |
30/4/17 | 0.035 | 5836.600098 |
7/5/17 | 0.032 | 5836.899902 |
14/5/17 | 0.028 | 5727.399902 |
21/5/17 | 0.022 | 5751.700195 |
28/5/17 | 0.023 | 5788.100098 |
4/6/17 | 0.038 | 5677.799805 |
11/6/17 | 0.043 | 5774 |
18/6/17 | 0.038 | 5715.899902 |
25/6/17 | 0.036 | 5721.5 |
2/7/17 | 0.04 | 5703.600098 |
9/7/17 | 0.031 | 5765.100098 |
16/7/17 | 0.032 | 5722.799805 |
23/7/17 | 0.03 | 5702.799805 |
30/7/17 | 0.032 | 5720.600098 |
6/8/17 | 0.033 | 5693.100098 |
13/8/17 | 0.04 | 5747.100098 |
20/8/17 | 0.053 | 5743.899902 |
27/8/17 | 0.078 | 5724.600098 |
3/9/17 | 0.074 | 5672.600098 |
10/9/17 | 0.056 | 5695 |
17/9/17 | 0.057 | 5682.100098 |
24/9/17 | 0.058 | 5681.600098 |
1/10/17 | 0.056 | 5710.700195 |
8/10/17 | 0.067 | 5814.200195 |
15/10/17 | 0.063 | 5907 |
22/10/17 | 0.105 | 5903.200195 |
29/10/17 | 0.19 | 5959.899902 |
5/11/17 | 0.24 | 6029.399902 |
12/11/17 | 0.2 | 5957.299805 |
19/11/17 | 0.19 | 5982.600098 |
26/11/17 | 0.215 | 5989.799805 |
3/12/17 | 0.23 | 5994.399902 |
10/12/17 | 0.275 | 5997 |
17/12/17 | 0.345 | 6069.700195 |
24/12/17 | 0.35 | 6065.100098 |
31/12/17 | 0.35 | 6122.299805 |
7/1/18 | 0.38 | 6070.100098 |
14/1/18 | 0.31 | 6005.799805 |
21/1/18 | 0.325 | 6050 |
28/1/18 | 0.245 | 6121.399902 |
4/2/18 | 0.23 | 5838 |
11/2/18 | 0.28 | 5904 |
18/2/18 | 0.22 | 5999.799805 |
25/2/18 | 0.24 | 5928.899902 |
4/3/18 | 0.24 | 5962.399902 |
8/3/18 | 0.24 | 5933.399902 |
((( Part B Financial Analysts will often try to model returns on a singular company against a market index – this is sometimes referred to as the market model. Your task is to replicate this model by regressing the returns of Digital X (Y variable) against the returns on the ASX200 index (X variable) as provided in the data file. Critically assess the veracity of this model by examining the goodness of fit, coefficients (together with the 95% confidence interval) and residuals. [Topics 7 & 9] ))
ONLY THQUESTION
Identify two factors that you believe could improve the regression model. Remember to explain why you think these factors are important, where you might source them from and whether their influence is likely to be positive or negative. [Topic 10]
The simple linear regression model from the given data is
Y=0.0953+0.000005*X
DLT Close (Y) | ASX Index (X) |
since the p-value of the regression is less than given level of significance=0.05, so model is not good fit.
Also proportion of explained variation R2=0.0005 is very low.
following regression analysis information has been generated using ms-excel
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.022382682 | |||||
R Square | 0.000500984 | |||||
Adjusted R Square | -0.005520094 | |||||
Standard Error | 0.075785444 | |||||
Observations | 168 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 0.000477883 | 0.000478 | 0.083205 | 0.773359907 | |
Residual | 166 | 0.953409968 | 0.005743 | |||
Total | 167 | 0.953887851 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 0.095301434 | 0.101290431 | 0.940873 | 0.348137 | -0.10468211 | 0.295284979 |
X Variable 1 | 5.25033E-06 | 1.82017E-05 | 0.288453 | 0.77336 | -3.06863E-05 | 4.11869E-05 |
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...
Cork price: 16 10 15 10 17 11 14 13 11 14 11 16 18 16 10 17 14 14 16 7 10 12 19 15 16 14 9 12 21 13 10 16 12 16 13 17 17 13 14 18 11 12 15 16 13 18 16 17 12 12 14 9 11 14 19 13 11 17 11 13 15 14 18 18 18 12 10 11 13 14 11 14 18 13 13 19 17 14...
Cork price: 16 10 15 10 17 11 14 13 11 14 11 16 18 16 10 17 14 14 16 7 10 12 19 15 16 14 9 12 21 13 10 16 12 16 13 17 17 13 14 18 11 12 15 16 13 18 16 17 12 12 14 9 11 14 19 13 11 17 11 13 15 14 18 18 18 12 10 11 13 14 11 14 18 13 13 19 17 14...
Day Sample (n) Number (np) Proportion (p) 1 500 12 0.024 2 500 15 0.030 3 500 19 0.038 4 500 13 0.026 5 500 9 0.018 6 500 26 0.052 7 500 18 0.036 8 500 14 0.028 9 500 17 0.034 10 500 18 0.036 11 500 16 0.032 12 500 24 0.048 13 500 11 0.022 14 500 31 0.062 15 500 16 0.032 16 500 10 0.020 17 500 16 0.032 18 500 17 0.034 19...
The manager asks you to Set up a single sample inspection plan. She wants the Probability of Acceptance to be 95% for lots with a reject rate of 0.05 and the Probability of Acceptance to be 10% for lots with a fraction defective of 0.15. (Please be detailed on how to come up with the plan- the process- I'm puzzled) Day Sample (n) Number (np) Proportion (p) 1 500 12 0.024 2 500 15 0.030 3 500 19 0.038 4...
Solve each inequality and graph its solution. 11) -12+ 3(-4 + 10x)2 3(1+ 10x)+5 12) 9-10k- 5k+ 62 5(9- 11k)+10(-7+4k) -10-8 -6 6 -5-43 -2 -1 01234 13) -5 +ks7 14) -4n> 8 4 2 0 2 468 10 12 14 7-6-5-4-3-2-1 01234 5 6 15) 6x+4 <4 16) 10p-9 s61 8 -7-6-4 -3-210 123 17) 3+-8x- 10 S-23 18) 4v-3-7>-26 6-5432-01234S 7-6-5432101 234
Problem 6. The set (Z19 − {0}, ·19) is a group with the
indicated operation; see the attached table. a.) Show that H = {1,
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H. c.) Show that if Hy = Hx then xy−1 ∈ H. [Make sure to give a
reason for each step.] d.) Show that φ : H → Hx defined by φ(h) =
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Game
Point_Differential Assists
Rebounds Turnovers Personal_Fouls
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Drive 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 16) Calculate the equivalent capacitance from points A to B using the figure if each capacitor has a capacitance of 1.0uF earch Dashb Enter your response Gm Answer Chapter 19- Homework Due Fri Mar 15th
Exercise for Section A 1. (10)3 +5)-? 3. (6-5+2)(5)-? 4.8+ (5(4)- 5. (10)(11)-1-? 6. 5+ 12/4-? 7. 10 + (2)(5)-5-? 8. 25-(92)+3-? 9. [(4 + 73- DI8-3]-? 10. [(3+5)+ (DX2)12- 11. The result of multiplication is known as the C. sum. 12. The result of addition is known as the C. sum. A. product. B. quotient. D. difference. A. product. B. quotient. 13. (4 +6(11)-? 14. (7-1+2)(4)-? 15. 20/(5 +5)-? 16. 9 +8/2-? 17. (12)(12)-3- 18. 9+ (4x8)-? 19. 15/3...
using matlab
Create the following matrix B. [18 17 16 15 14 13] 12 11 10 9 8 7 6 5 4 3 2 1 Use the matrix B to: (a) Create a six-element column vector named va that contains the elements of the second and fifth columns of B. (6) Create a seven-element column vector named vb that contains elements 3 through 6 of the third row of B and the elements of the second column of B. Create...