Data Collection and Descriptive Statistics of the Walt Disney Company _phase II _group project_MBAF
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1 Data Collection and Descriptive Statistics of the Walt Disney Company Phase - 3
University Canada West MBAF 502: Quantitative Reasoning and Analysis S-37 March 25, 2024 5.1 What method was used for forecasting? Linear regression analysis was used to forecast the stock price of Walt Disney and Ne:lix companies. The technique of regression analysis allows us to examine the rela@onship or correla@on between the dependent variable (stock costs), and the independent variable (@me period with days and months). The linear trend obtained by regression analysis allows us to assess the nature of the rela@onship between two variables and predict future values. The main indicators in forecasting using regression analysis are the strength, direction and reliability (validity) of the relationship. The strength of the relationship is determined by the absolute value of correlation varies from 0 to 1 (Pearson correlation coefficient). The direction of
2 the relationship is determined by the sign of the correlation coefficient: a positive coefficient - the relationship is direct; a negative coefficient - the relationship is inversed. Reliability of the relationship is determined by the p-level of statistical significance (the smaller the p-level, the higher the statistical significance or reliability of the relationship). 5.2 What were the forecast results? The results of the forecast were the predicted values of the companies' shares for three months - December 2023, January 2024 and February 2024 in Canadian dollars. 5.3 How did the forecast results agree with the actual historical data? 5.6 Were the correlations statistically significant? The forecast values differ from the actual values in both companies, and for the Walt Disney Company, the difference is very significant. The forecast values of Walt Disney's stock price. Table 1 Summary Output Walt Disney
3 The forecast of Walt Disney Company's stock value should be considered unreliable because the correlation between the forecast and actual values of prices is low at 0.48 (figure 1). Figure 1 y = -0.1517x + 94.083
R² = 0.481
$80
$81
$81
$82
$82
$83
$85
$90
$95
$100
$105
$110
$115
Predicted price
Actual price
Scatterplot Actual/Predicted
Walt Disney
4 The correlation or R square between the share price and time (day and month) is weak and is only 0.55 (table 1). According to the figure 2, a linear dynamic in the direction of decrease in the value of shares over time. The stock value has been gradually decreasing since the beginning of 2023, but from the 7
th
of November the stock values increased. This upward spike in value was not included by linear regression in the accounting, continuing the downward trend line to lower value (figure 2). Figure 2 Figure 3
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270
360
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ut of
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Return on equity in percent
Salary
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(324) (0.033)
(0.0129)
(0.00026)
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Question 9
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O Increase by 2Q units
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18
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B
1 SUMMARY OUTPUT
2
3.
Regression Statistics
4 Multiple R
5 R Square
6 Adjusted R Square
7 Standard Error
0.4924
0.2425
0.2019
40.24
8 Observations
60
9.
10 ANOVA
Significance F
5.97
11
df
S
MS
9676.6
0.0013
12 Regression
13 Residual
3
29,030
90,694
56
1619.5
14 Total
59
119,724
15
16
Coefficients Standard Error
t Stat
P-value
0.0331
0.2156
17 Intercept
51.39
23.52
2.19
18 Lot size
0.700
0.559
1.25
19 Trees
0.679
0.229
2.96
0.0045
20 Distance
-0.378
0.195
-1.94
0.0577
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0.34 (0.18)
Entitlement/
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0.19 (0.26)
exploitativeness
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Primary
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.16 (-1.07)
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-.20 (-2.63**)
67.40 (14.54)
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75.16 (16.57)
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2003
2138
103.9
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2005
2600
78.1
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SE Coef
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F-RATIO
P-VALUE ON F
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0.85121212
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30
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5
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2
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2,000
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80
Hiking Trips
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8
6
2
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