Question

In: Accounting

Individual task Students should provide a stock price fluctuation analysis of a publicly traded company ,...

  • Individual task
  • Students should provide a stock price fluctuation analysis of a publicly traded company , using the financial data available effecting the stock market.
  • Key contextual elements should include the stock exchange market, stock market indexes e.g. the Standard &Poor’s 500 Index and the Dow Jones Industrial Average in the context of market forces and economic forces, that demonstrate a clear understanding of the learning objectives discussed in this course.
  • Title page, Written Body, along with a Bibliography of any written references, images, or diagrams used (if applicable). NOTE: Formal Written Reports must include a Title Page, Table of Contents, and Appendix of Financial Statements.
  • Formal Written Report saved and uploaded to Moodle in PDF format.

Formalities:

  • Word count: 2000 words

Solutions

Expert Solution

A portion of the Minitab output is shown below:

The regression equation is

S&P = - 669 + 0.157 DJIA

Predictor           Coef       SE Coef           T             P

Constant           -669.0         130.7        -5.12        0.000

DJIA             0.15727       0.01015      15.49        0.000

S = 9.60811   R-Sq = 94.9%   R-Sq(adj) = 94.5%

Analysis of Variance

Source                 DF           SS               MS             F                P

Regression             1          22146         22146          239.89        0.000

Residual Error      13          1200               92

Total                     14         23346

Using the F test, the p-value corresponding to F = 239.89 is .000. Because the p-value=.05, we reject; there is a significant relationship.

With R-Sq = 94.9%, the estimated regression equation provided an excellent fit.

The DJIA is not that far beyond the range of the data. With the excellent fit provided by the estimated regression equation, we should not be too concerned about using the estimated regression equation to predict the S&P500.


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