# 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 IBM’s stock price for each quarter. Next, click on S\&amp;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 IBM’s quarterly return (percentage change in stock price) as the dependent variable and the quarterly percentage change in the U.S. stock market**#x2019;s 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 IBM’s value to the U.S. market returns. Also, check the fit of the relationship based on the R -squared statistic.

FindFind

### International Financial Management

14th Edition
Publisher: Cengage
ISBN: 9780357130698
FindFind

### International Financial Management

14th Edition
Publisher: Cengage
ISBN: 9780357130698

#### Solutions

Chapter 13, Problem 1IEE
Textbook Problem

## 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 IBM’s 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 IBM’s quarterly return (percentage change in stock price) as the dependent variable and the quarterly percentage change in the U.S. stock market**#x2019;s 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 IBM’s value to the U.S. market returns. Also, check the fit of the relationship based on the R -squared statistic.

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