Many variables influence the price of a company’s common stock, including company-specific internal variables such as product quality and financial performance, and external market variables such as interest rates, exchange rates and stock market performance. The attached table contains quarterly data on three such external variables (x1, x2, and x3) and the price y of Ford Motor Company’s common stock (adjusted for stock splits). The Japanese yen exchange rate, x1, measures the strength of the yen versus the US dollar. The higher the rate, the cheaper are Japanese imports – such as the automobiles of Toyota, Nissan, Honda, and Subaru – to US consumers. Similarly, the higher the deutsche mark exchange rate, x2, the less expensive are BMW’s and Mercedes Benz’s to US consumers. Finally, the S&P 500 Index, x3, is a general measure of the performance of the market for stocks in US firms. Answer the questions below using the critical value approach and/or the p-value approach Date Ford stock Price y Japanese Yen x1 Deutsche Mark x2 S&P500 x3 1992.1 38.3 133.2 1.64 407.36 1992.2 45.2 125.5 1.53 408.21 1992.3 39.4 119.2 1.41 418.48 1992.4 42.7 124.7 1.61 435.64 1993.1 52.3 121.3 1.61 450.16 1993.2 55.3 110.1 1.69 447.29 1993.3 64.7 105.2 1.62 459.24 1993.4 58.1 111.3 1.73 465.34 1994.1 59.9 103.4 1.76 463.21 1994.2 27.6 99.5 1.6 454.83 1994.3 27.5 98.5 1.55 466.96 1994.4 26.3 99.6 1.38 455.19 1995.1 29.5 89.4 1.39 493.15 1995.2 31.2 84.6 1.42 539.23 1995.3 28.7 98.2 1.43 578.32 1995.4 28.9 102.4 1.48 614.57 1996.1 34.8 106.3 1.52 647.05 1996.2 36.2 109.8 1.58 668.53 1996.3 32.1 110.5 1.61 672.92 1996.4 33.9 112.8 1.69 689.35 5) Do the data provide sufficient evidence that the price of Ford stock respond to general stock market conditions? Reach your conclusion using a= 0.05
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Many variables influence the price of a company’s common stock, including company-specific internal variables such as product quality and financial performance, and external market variables such as interest rates, exchange rates and stock market performance.
The attached table contains quarterly data on three such external variables (x1, x2, and x3) and the price y of Ford Motor Company’s common stock (adjusted for stock splits). The Japanese yen exchange rate, x1, measures the strength of the yen versus the US dollar. The higher the rate, the cheaper are Japanese imports – such as the automobiles of Toyota, Nissan, Honda, and Subaru – to US consumers.
Similarly, the higher the deutsche mark exchange rate, x2, the less expensive are BMW’s and Mercedes Benz’s to US consumers. Finally, the S&P 500 Index, x3, is a general measure of the performance of the market for stocks in US firms. Answer the questions below using the critical value approach and/or the p-value approach
|
Date |
Ford stock Price y |
Japanese Yen x1 |
Deutsche Mark x2 |
S&P500 x3 |
|
1992.1 |
38.3 |
133.2 |
1.64 |
407.36 |
|
1992.2 |
45.2 |
125.5 |
1.53 |
408.21 |
|
1992.3 |
39.4 |
119.2 |
1.41 |
418.48 |
|
1992.4 |
42.7 |
124.7 |
1.61 |
435.64 |
|
1993.1 |
52.3 |
121.3 |
1.61 |
450.16 |
|
1993.2 |
55.3 |
110.1 |
1.69 |
447.29 |
|
1993.3 |
64.7 |
105.2 |
1.62 |
459.24 |
|
1993.4 |
58.1 |
111.3 |
1.73 |
465.34 |
|
1994.1 |
59.9 |
103.4 |
1.76 |
463.21 |
|
1994.2 |
27.6 |
99.5 |
1.6 |
454.83 |
|
1994.3 |
27.5 |
98.5 |
1.55 |
466.96 |
|
1994.4 |
26.3 |
99.6 |
1.38 |
455.19 |
|
1995.1 |
29.5 |
89.4 |
1.39 |
493.15 |
|
1995.2 |
31.2 |
84.6 |
1.42 |
539.23 |
|
1995.3 |
28.7 |
98.2 |
1.43 |
578.32 |
|
1995.4 |
28.9 |
102.4 |
1.48 |
614.57 |
|
1996.1 |
34.8 |
106.3 |
1.52 |
647.05 |
|
1996.2 |
36.2 |
109.8 |
1.58 |
668.53 |
|
1996.3 |
32.1 |
110.5 |
1.61 |
672.92 |
|
1996.4 |
33.9 |
112.8 |
1.69 |
689.35 |
5) Do the data provide sufficient evidence that the price of Ford stock respond to general stock market conditions? Reach your conclusion using a= 0.05
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