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Unformatted text preview: ECON 2P91: Business Econometrics with Applications Winter 2011 Lab2 (Week of February 14 th ): SOLUTIONS The objective of this weeks labs is to demonstrate the use of GRETL to transform variables and use the transformed variables to estimate the parameters of a simple linear regression model and test the appropriate hypotheses (using both the significance approach and p-value approach) and interpret the results of these hypotheses tests. The Capital Asset Pricing Model (CAPM) suggests that there should be a linear relationship between the risk premium of stock j (i.e. the difference between stock js return and the risk free market rate), and the overall market risk premium (i.e. the difference between the overall market rate of return and the risk free market rate). This relationship could be specified as t t t t t u RFREE RMARKET RFREE RJ +- + =- ) ( ) ( 1 where t RJ is the return of the j-th firm at time t, t RFREE is the risk free return at time t, and t RMARKET is the market rate of return at time t. One of the main objectives of CAPM is to obtain estimates of a measure of risk for an asset. On the basis of finance theory underlying CAPM, we would expect estimates of the intercept parameter to be (close to) zero. The slope parameter 1 is referred to as the beta coefficient of stock j. If 1 1 = , the movement of asset prices of the j-th firm is the same as that of the market as a whole. What is the beta coefficient for IBM stocks? If 1 1 , then adding IBM stocks to a portfolio would increase the portfolios risk (i.e., IBM is more risky than the market); If 1 1 < , then adding IBM stocks to a portfolio would decrease the portfolios risk (i.e., IBM is less risky than the market). Consider the Excel data file capm.xls . For this data set, that covers the period from January 1978 to December 1987, RJ is the return of IBM stocks; RFREE is the risk-free return; and RMARKET is the return for the market portfolio (S&P500)....
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