Quantitative Finance Stack Exchange is a question and answer site for finance professionals and academics. It only takes a minute to sign up.
Sign up to join this community
Fama-MacBeth (1973) introduce a two stage cross-sectional regression method (http://en.wikipedia.org/wiki/Fama%E2%80%93MacBeth_regression).
If I was to regress stock prices (or returns) on a conditioning set using the Fama-MacBeth regression method, what are the econometric assumptions behind this model?
Is the model still used today or is another model now preferred?
2) Alternative to Fama-MacBeth is Fama-French approach. Explanation of difference see, for example, here: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1271935 Fama-French approach was used by Carhart (introduced momentum), Pastor-Stambaugh (introduced liquidity), Fama-French themselves (used it to build 5-factor model), and many other (elsevier or google for "fama french factor model").
Fama-MacBeth approach was used in Chen, Roll, Ross, 1986, which is believed to be quite important paper for APT.
There is also PCA approach to modelling asset returns. See, e.g., Luedecke, 1984, Connor and Korajczyk, 1988.
In industry, still, scholar models are not used. Practitioners develop their own models, sometimes kept as closely held secret, sometimes - made available to public (BARRA, CSFB, Morgan Stanley, Salomon-Smith-Barney, Bloomberg). Sometimes these models are just overcomplicated versions of scholar models, built with the same approaches. Sometimes they try to use some combination, for example Bloomberg family of models combine PCA with macro- and fundamental approaches.
The key assumption is that there is no time-series correlation between the error terms. Fama-MacBeth can deal with cross-sectional correlations.
See Samuel Thompson's "Simple formulas for standard errors that cluster by both firm and time" in the Journal of Financial Economics (2011) for a treatment of different regression methods for testing equity pricing models.
