1.
(2022 24)

2.
Company Name: ADANITRANS (Adani
Transmission Ltd)

3.
transmission company. Currently, it is one of the
largest private sector power transmission
companies operating in India, it was founded by
Gautam Adani in December 2015 after separating
the decade-old transmission business from Adani
Enterprises.

4.
In finance, a stock index, or stock market index,
is an index that measures a stock market, or a
subset of the stock market, that helps investors
compare current stock price levels with past prices
to calculate market performance.

5.
represents the next rung of liquid securities after
the NIFTY 50. It consists of 50 companies
representing approximately 10% of the traded
value of all stocks on the National Stock
Exchange of India. The NIFTY Next 50 is owned
and operated by India Index Services and Products
Ltd.

6.
Please find below the comparison between Nifty
Next Fifty’s Closing price and Adani
Transmission Ltd.’s Closing price for the time
period of 3rd Jan, 2022 to 30th Aug, 2022.

7.
Descriptives:

8.
that 50% closing price lie below 40615.4250
(Median) and 50% lie above 40615.4250 for Nifty
Next 50. For ADANITRANS, 50% closing price
lie below 2309.1000 (Median) and 50% lie above
2309.1000.

9.
understand that in 95% of the cases the closing
value will be between 40073.8274 to 40744.5402
for Nifty Next 50 and 2379.0546 to 2541.0394 for
ADANITRANS. This is a huge range because of
the standard deviation being 2174.92343 and
525.26885 for Nifty Next 50 and ADANITRANS.

10.
By 5% Trimmed Mean, we can understand that
this is not normal data as there is a huge difference
between Mean and 5% Trimmed Mean for both
Nifty Next 50 and ADANITRANS.

11.
Standard Deviation explains us the spread of the
data/score from the mean score and Variance is
square of Std Deviation, Variance gives us the
picture of the variability of the data.

12.
between 1st Quartile and 3rd Quartile. Interquartile
rang for Nifty Next 50 is very high (3741.40) in
comparison to that of ADANITRANS (704.43).
Larger Interquartile range in a group indicates
greater spread of scores indicating higher
variability in data.

13.
The Sig (Significance) value of Kolmogorov-
Smirnov and Shapiro-Wilk is less than 0.05,
which means that the data is not normal, we will
have to reject the assumption of Null Hypothesis.

14.
(present below), we can observe that the data
point is not falling on 45-degree line of Q-Q plot
and in the detrended Q-Q plot we can observe that
the data point is not falling on the horizontal line.
This signals the departure from normality.

15.
Interquartile Range 3741.40
Skewness -.333 .190 Kurtosis
-.951 .377ADANITRANS Mean
2460.0470 41.01661 Closing Price
95% Confidence Lower Bound
2379.0546 Interval for Mean
Upper Bound 2541.0394 5%
Trimmed Mean 2426.5486
Median 2309.1000 Variance
275907.365 Std. Deviation
525.26885 Minimum
1731.10 Maximum 3960.70

16.
4250 4750 5
ADANITRANS 1900. 1958.
2040.6 2309.1 2745.0 3428.8 3599.0
Closing Price 7375 0000 250 000
500 000 750 Tukey's Nifty Next Fifty
38667. 40615. 42392. Hinges
Closing Price 9250 4250 5250
ADANITRANS 2041.5 2309.1
2740.3 Closing Price 000 000
000

17.
115 35405.40 2 114 35668.20
3 117 35716.25 4
118 36141.10 5 113 36268.70
ADANITRANS Closing Price Highest 1
164 3960.70 2 163 3855.55
3 162 3751.20 4 161 3715.80
5 160 3700.40
Lowest 1 1 1731.10 2 2
1754.95 3 4 1760.05 4
3 1761.05 5 5 1776.00

18.
Tests of Normality Kolmogorov-Smirnov
Shapiro-Wilk Statistic df Sig. Statistic
df Sig. Nifty Next Fifty Closing Price .085
164 .005.956164 .000ADANITRANS
Closing

19.
Price .140 164.000 .890 164.000
a. Lilliefors Significance Correction

20.
Correlations

21.
Correlations is the extent to which two
variables are related to each other.

22.
From the best fit line present in the scatter plot
below we can conclude that there is a positive
correlation between Nifty Next Fifty Closing
Price and ADANITRANS Closing Price.

23.
Although the data is not normal but since the
sample size is large, so we have conducted the
Pearson Correlation test.

24.
Bootstrapping has been done here as the data is
not normal. We can observe that our correlation
coefficient is ranging from 0.201 to 0.430

25.
The value of correlation coefficient is 0.325 and p
value is 0.000022 which means that there is a
significant correlation between Nifty Next Fifty
Closing Price and ADANITRANS Closing Price.

26.
Correlations
Nifty Next

27.
Fifty Closing Price

28.
ADANITRANS

29.
Pearson Correlation 1 .325** Sig.
(2-tailed) 0.000022 N
164 164 Bootstrapc Bias 0 -
.002 Std. Error 0 .060
BCa 95%

30.
Confidence Interval Lower . .201
Upper . .430 ADANITRANS

31.
Closing Price Pearson Correlation
.325** 1 Sig. (2-tailed)
0.000022 N 164 164
Bootstrapc Bias -.002 0
Std. Error .0600 BCa 95%

32.
Confidence Interval Lower .201. Upper
.430. **. Correlation is significant at the
0.01 level (2-tailed). c. Unless otherwise noted,
bootstrap results are based on 1000 bootstrap
samples

33.
Regression

34.
Regression helps us study the cause-and-
effect relationship between the variables.

35.
Square is the measure of total influence of
independent variable on the dependant variable. R
square is the percentage of influence explained by
the independent variable in the dependant
variable.

36.
Independent Variable is Nifty Next Fifty and
Dependant Variable is ADANITRANS.

37.
Durbin Watson test value is 0.17 which is in the
range of -3.29 and +3.29, so we can conclude that
the sample is independent.

38.
10.5% of ADANITRANS closing value can be
accounted by the Nifty Next 50 closing value. Std
Error of Estimate is quite high as 498.36682, this
indicates the error in prediction.

39.
we can say that the regression as a whole is
significant up to 99% level so it is statistically
significant and we have rejected the null
hypothesis that all the variable is equal to zero and
model is essentially explaining none of the
variation in our dependant variable.

40.
We can conclude that Nifty Next Fifty closing
price’s 1 unit has 0.078 unit of positive
effect/influence on ADANITRANS closing price.

41.
1 standard deviation change in Nifty Next Fifty
closing price is going to cause 0.325 standard
deviation change in ADANITRANS closing price.

42.
Model Summaryb

43.
Model

44.
R

45.
the Estimate Durbin- Watson 1 .325a .105
.100498.36682 .017a. Predictors:
(Constant), Nifty Next Fifty Closing Price
b. Dependent Variable: ADANITRANS
Closing Price

46.
ANOVAa

47.
Model Sum of Squares

48.
df

49.
Mean Square

50.
F

51.
Sig. 1 Regression 4737042.8271
4737042.82719.073 .000b Residual
40235857.59

52.
6 162248369.491 Total
44972900.42

53.
3 163 a. Dependent
Variable: ADANITRANS Closing Price
b. Predictors: (Constant), Nifty Next Fifty
Closing Price

54.
Coefficientsa Unstandardized

55.
Coefficients Standardized Coefficients
Model B Std. Error Beta t Sig. 1
(Constant) -707.302726.299 -.974
.332 Nifty Next Fifty Closing

56.
Price .078.018.3254.367 .000a. Dependent
Variable: ADANITRANS Closing Price

57.
Residuals Statisticsa

58.
Minimum

59.
Maximum

60.
Mean Std.

61.
Deviation

62.
2460.0470 170.47467 164 Residual-
896.72473 1241.99536 .00000 496.83574
164 Std. Predicted Value -2.301 1.595
.0001.000 164 Std. Residual-1.799 2.492
.000.997164 a. Dependent Variable:
ADANITRANS Closing Price

63.
27-Jan-22 40299.3 2009.3 28-Jan-22
40633.2 1986.8 31-Jan-22 41097.25
1970.9 01-Feb-22 41810.6 1986.9 02-
Feb-22 42249.1 2016 03-Feb-22 42030.15
2006.2 04-Feb-22 41998 2033.1 07-
Feb-22 41716.9 2028.5 08-Feb-22 41522.1
1968.3 09-Feb-22 41991.9 1955.2 10-
Feb-22 42165.35 2036.4 11-Feb-22
41553.05 2016.05 14-Feb-22 40164.8
1915.25 15-Feb-22 41138.8 1926.95 16-
Feb-22 41058.2 1932.55 17-Feb-22 41145.65
2020.85 18-Feb-22 40709.15 1958.1
21-Feb-22 40177.45 1895.9 22-Feb-22

64.
2443.85 06-Apr-22 42910.45 2484.05
07-Apr-22 42784.3 2449.65 08-Apr-22
43445.9 2540.25 11-Apr-22 43878.15
2756.5 12-Apr-22 43382.2 2680.55 13-
Apr-22 43443.9 2690.75 18-Apr-22 43289.4
2728.3 19-Apr-22 42500.45 2598.05
20-Apr-22 42713 2687.55 21-Apr-22
43256.15 2699.6 22-Apr-22 42934.55
2658.55 25-Apr-22 42084.35 2615.9
26-Apr-22 43072.25 2812.55 27-Apr-22
42504.75 2712.2 28-Apr-22 43086.1
2796.65 29-Apr-22 42533.95 2789.5

65.
Jun-22 36955.45 2057.5 15-Jun-22
37036.1 2057.3 16-Jun-22 36268.7
2124.65 17-Jun-22 35668.2 2032.6 20-
Jun-22 35405.4 2060.25 21-Jun-22 36381.05
2215.05 22-Jun-22 35716.25 2122.35
23-Jun-22 36141.1 2105 24-Jun-22
36616.3 2152.1 27-Jun-22 36882.45
2140.55 28-Jun-22 36937.25 2163.4
29-Jun-22 36679.25 2347.9 30-Jun-22
36505.4 2473.65 01-Jul-22 36901.2
2400.65 04-Jul-22 37273.9 2423.1 05-
Jul-22 37306 2476.3 06-Jul-22 37937.65