IBM vs the Fama French Market Factor

I'm more interested in economic factor models (EFM) than fundamental factor models. Since the heart of building an EFM is estimating the exposures (betas) of stocks to economic time series with regressions, I'm going to start with that. This is pretty basic, but I have an additional challenge in that I've decided to do everything with Mathematica (M-). It's extremely powerful, but has a steep learning curve. Starting with something basic will make it easier for me to learn about M-.

Finding sources for data and making sure it's good data is another challenge, and not a trivial one. MM helps me out a bit because version 6 comes with built in access to a financial database, but it's not perfect either. The Mathematic financial data function ( FinancialData ["IBM", "Returns", {to,from,period}] ) comes back with price returns. The financial database at Wolfram Research is a new thing for them, so they still have a few bugs to work out. I'll solve total return problem later.

My first exercise is simple. I want to calculate IBM's exposure to the Fama French market factor (this is basically IBM's market beta). This regression is based on approximately 36 years of monthly returns. The IBM's returns are price instead of instead of total returns, and not excess returns either, but I'm anxious to get started! Look how little M- code it took to load the data, do the regression and make two plots. The regression returns a beta of 1.30 with an r-squared of 34%. Not a bad r-squared! Click the image below for a better view.