Problem-
Can you predict the price of your favorite stock shares based on a market index value? For a stock that has at least five years of history, develop a regression equation to predict its value if the index of your choice goes up by and if it goes down by 15% from its value on the day you do this problem. (For example if you choose the S&P 500 as the index and the value today is 1,200 points, then predict your stock's price when the index is at 1,380 and 1,020). Use monthly closing figures for the last five years for both your stock and index choice.
HINT: You can obtain historical price information at most Web sites that provide financial information and stock quotes, for example, www.finance.yahoo.com. On the main page, you will find the Dow-Jones Industrial Average, NASDAQ Composite Index, S&P 500 Index and the 10-year bond index. Click on the name link for your choice. On the quote page's left menu, click on Historical Prices. With the date boxes choose the date period that you want and click on the radio button for Monthly. Now click on Get Prices. At the bottom of the list of prices, click on Download to Spreadsheet. This will download the data to your computer. To get the prices for your stock choice, start typing the name of the company in the Quote box and select it when it appears in the dropdown box. Then follow the same procedure as for the index to download the data. Copy and paste the close column from the stock and the index into a new workbook and conduct your analysis.
Requirements:
• Develop a prediction equation
• Comment on the usefulness of the equation to make predictions (SEE, No Image, F-test, and slope coefficient significance)
• Interpret the slope coefficient
• Make the two predictions as indicated in the problem (whether or not you conclude the equation is useful for predictions)
• Identify the 95% prediction interval
Additional information-
This problem related to Basic Statistics and it is about developing predicting an equation and to comment on the usefulness of the equation to make predictions. The solution has data predictions and interpreted made in detail.