I've recently neglected the Compact Model Portfolio, on this blog. This is probably due to my interest in the Dynamic Trading Risk Factor — which is work I've done more recently.

The history of the composition of this index, and it's daily return relative to the benchmark, have been available on the blog side panel for a while now.

This index has been short financials via a long position in SKF, which has reversed some of the exposure due to a long position in Bank of America (BAC). Today, this changed — as the SKF position was replaced with one in Wells Fargo.

In the previous post we exhibited regressions of the returns of various banking companies onto the dynamic trading risk factor. Two distinct regression periods we used, and we made general comments about how the parameter estimates had changed.

In this post we're going to try to delve a little more into those changes. We're going to assume that the changes represent an actual change of behaviour on behalf of the institution concerned rather than that they represent statistical fluctuations about a common "true" value. With such a small sample, and such large errors relative to the estimates, this is a dubious exercise, but we will press on as it is entertaining.

These changes are represented by the vector flows on the "tadpole" chart below. The vector is from the "thin end" to the "head" (and is represented as such because Excel can't draw arrows).

So, overinterpreting to the best of our abilities, we see that: MS and GS have moved towards eachother - adopting similar behavioural profiles; JPM has essentially abandoned its hedge fund like trading business; MER (which were "rescued" by BAC), BAC, and C have started winding down their trading businesses at considerable expense; and LEH and BSC traded more desperately as they failed.

The above is, of course, entirely unrigourous and barely supported by the data. Don't place too much faith in it.

The table below shows the estimated parameters, alpha and beta, for a linear regression of the monthly adjusted returns of the common stock of a well known group of companies onto the dynamic trading risk factor series. These regressions are done separately for the pro articulus (01/2001 until 12/2006) and per articulus (01/2007 to date) periods. If the company still exists as an independent entity, a forecast is given for the return for 02/2009 (i.e. this month) based on a "whole dataset" regression (01/2001 to date). The companies studied are: Goldman Sachs; Morgan Stanley; Citigroup; Bank of America; Merrill Lynch; Lehman Brothers; JP Morgan; and, Bear Stearns. (Of course MER, LEH, and BSC terminated at some point within the latter period. For these companies, the regression used data upto the "end" of the company and not for the later trading of "stub" equity in the remnants of the company, if any.)

What is there to conclude from this? Starting with the innocent days of the pro articulus period, we see that all of these firms, with the exception of BAC, have an alpha estimated to be of order -1%/month to -2%/month and a beta of approximately 3 to 4 onto the risk factor. An plausible explanation is that, with the exeption of BAC, these firms all were in the business of trading and the negative alpha represents the high costs of financing this activity. Interestingly, the damage done due to the fiscal crisis, at least as far as the parameter estimates for the per articulus period go, was done idiosyncratically (i.e. it is expressed through the alpha) and not as a result of highly leveraged exposure to dynamic trading.