IBM has substantial operations in many countries, including the United States, Canada, and Germany. Go to finance.yahoo.com and search for IBM. Alternatively, apply this exercise to a different MNC of your choice.

1. Click on Historical Data. Set the date range so that you can obtain quarterly values of the U.S. stock index for the last 20 quarters. Enter the quarterly data on a spreadsheet. Compute the percentage change in IBMs stock price for each quarter. Next, click on S&P Composite 1500, 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 IBMs quarterly return (percentage change in stock price) as the dependent variable and the quarterly percentage change in the U.S. stock markets value as the independent variable. (Appendix C explains how you can use Excel to run regression analysis.) The slope coefficient serves as an estimate of the sensitivity of IBMs value to the U.S. market returns. Also, check the fit of the relationship based on the R-squared statistic.

2. Go to finance.yahoo.com and search for DAX Performance-Index, which represents the German stock market index. Repeat the process described in exercise 1 so that you can assess IBMs sensitivity to the German stock market. Compare the slope coef-ficient between the two analyses. Is IBMs 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 IBMs returns (check the R-squared statistic)? Offer an explanation of your results.