Using R in equity research

I've been doing valuation studies within industries, looking at how
some valuation measures relate to company characteristics and
external factors over time. My professor suggested using mixed
effects models for such longitudinal data studies, and I don't have
a budget for this sort of thing, so using R and the NLME package was
a natural choice. I think I'm doing some things with it I haven't
seen other analysts do.

I'm not sure I understand what you are doing, but I've often thought
about doing the following: Suppose you estimate regression models
_within_ a homogeneous industry, where you put P/E or P/B on the
l.h.s. and you use a bunch of firm characteristics as explanatory
variables. Would the outliers be places to take a good look for a
profit opportunity? (Is this what you have in mind?)

The problem with this (AFAICT) is that the cross section of accounting
ratios / data tends to be pretty nasty in terms of
distributions. You'll always have a few weird observations which drive
the result. R might be particularly good at this, by virtue of
bringing a variety of statistical and graphical tools to bear on weird
observations, non-normal distributions, etc.

All this is just guesswork, I haven't actually done it. If you have,
do show us examples?

Ajay Shah                                                   Consultant
ajayshah@mayin.org                      Department of Economic Affairs
http://www.mayin.org/ajayshah           Ministry of Finance, New Delhi