Case Study
39352BM has substantial operations in many countries, including the United States, Canada, and Germany. Go to finance.yahoo.com/q?s=ibm.
Click on Historical Prices. (Or apply this exercise to a different MNC.) Set the date range so that you can obtain quarterly values of the U.S. stock index for the last 20 quarters. Insert the quarterly data on a spreadsheet. Compute the percentage change in IBM’s stock price for each quarter. Next go to finance.yahoo.com/stock-center/ and click (under U.S.) on S&P Composite 1500 Index, which represents the U.S. stock market index, so that you can derive the quarterly percentage change in the U.S. stock index over the last 20 quarters. Then run a regression analysis with IBM’s quarterly return (percentage change in stock price) as the dependent variable and the quarterly percentage change in the U.S. stock market’s value as the independent variable. (Appendix C explains how Excel can be used to run regression analysis.) The slope coefficient serves as an estimate of the sensitivity of IBM’s value to the U.S. market returns. Also, check the fit of the relationship based on the R-squared statistic.
Go to finance.yahoo.com/stock-center/ and click (under “Europe”) on DAX, which represents the German stock market index. Repeat the process described in exercise 1 so that you can assess IBM’s sensitivity to the German stock market. Compare the slope coefficient between the two analyses. Is IBM’s value more sensitive to the U.S. market or the German market? Does the U.S. market or the German market explain a higher proportion of the variation in IBM’s returns (check the R-squared statistic)? Offer an explanation of your results.
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