Econ 393 Spring 2010 Homework 2

Finance Project ECON 393 Spring 2011 Instructor: Diep duong

Problem 1 (60 points): This problem asks you to work with empirical data. I assume that you are familiar with linear regression. In particular, what you really need to know is how to run regression using Eview or other software. (If you plan to use other software, let me know).

As we have discussed, CAPM could be seen as “One Factor” model written as follows:

R A  R f  beta * Fm where R A is the expected return of asset A; R f is the risk free rate, Fm is the market factor (Market portfolio excess return or risk premium). It is crucial to estimate beta as it is a measure for systematic risk. You could estimate beta by using the following regression equation

RA  R f    beta *(Rs& p  R f )   where RA and Rs& p are return of asset A and S&P 500 respectively and  is idiosyncratic noise of A. For asset A, you will work with Microsoft and Johnson & Johnson stock (2 separate cases). You can use the risk free rate in Fama French data set and S&P 500 for Market Portfolio from Yahoo Finance.

1. Go to Yahoo finance and download daily data of Microsoft and Johnson & Johnson and S&P 500 for period from 1990 to 2010. Specifically, search for Microsoft (or Johnson &Johnson or S&P 500) in Yahoo Finance and click on “Historical Prices” and fill in necessary information for your excel file download. Calculate the daily percentage return of the assets and report the means and variances of the 2 assets and S&P 500.

2. Estimate beta and alpha of Microsoft and Johnson & Johnson. Discuss the intuition of two betas as well as link them to the portfolio choice problem (rationality, optimality….). Compare the results you find with those of Yahoo finance. (To do this problem, use the data in Yahoo finance for assets, use the excess return of S&P for Fm and you can use the risk free rate from the link in part 3, i.e. Fama French)

3. In the case of Arbitrage Pricing Model (APT) that I mentioned in class, the model by Fama-French factors could be written as

RA  R f    betam * Fm  betasmb * Fsmb  betahml Fhml  

Similar to part 2, you can estimate ,betam ,betasmb ,betahml by regressing the left hand side variable on the right hand side variables (now you have 2 more variables than previous case). The data for risk free rate, daily data of 3 factors could be downloaded at Farma French Webpage

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html (Click on Farma/Frech Factors [Daily])

Estimate the models for the two stocks Microsoft and Johnson & Johnson and report your results. Compare R square of part 2 and part 3.