Goldman and the future of Investment Banking

Some of the dealing on Wall Street falls under the category of being legal but unscrupulous.   That said, it is little different from the buying and selling that a used car dealer does.   The dealers products have to be approached with a buyer-beware mentality for better or worse.

The dealer is looking to buy cheap, repackage or create, and sell at a higher price.   Necessarily the dealer cannot reveal what she perceives to be the real value in buying merchandise and likewise will sell the merchandise for the highest price possible.

Goldman fell a bit over 12% after the news of the SEC civil case, removing about 9B$ in market value.   My view is this reaction is much overdone (hence I am long at the -12% level).   Beyond the civil case there are concerns about possible regulations such as:

• disallowing retail banks to deal in derivatives (more or less)
  The details of how this would be applied are not clear.  But firms that choose to deal in the restricted products will not have access to depositors insurance and fed funds apparently.
• rules about leverage (i.e. capital requirements)
  Nothing clear here, but surely would expect that there will be regulation here and/or unwillingness on the part of gov lenders to provide capital for over-leveraged firms.
• move many OTC derivatives to exchanges
  This will introduce more transparency to the derivatives market.   At the same time, margins for these trades will drop significantly.    It will, however, open up new algo markets.

With the exception of reduced leverage, I expect the above, in whatever form they appear will disadvantage retail banks and less sophisticated players, and hand more of the market to investment banks such as Goldman.   It will take a long time to play out, but I see Goldman winning here.

Personally I welcome the new algo opportunities!

Distribution Estimation

I’ve been travelling for the last 3 weeks so have not had much time to post.   During the trip, I’ve been thinking further about the following problem:

1. We are interested in determining a representative distribution for some financial factor
2. suppose we start with start with a “universal” high-dimensional joint distribution of all random variables that might possibly have relevance to the probability of some financial factor
3. suppose that the number of variables in the universal joint distribution is high enough that the distribution is sparse relative to the sampled data.  We need to reduce the number of degrees of freedom.
4. Is there a smaller marginal distribution (a subset of variables) that provides representative modes and distribution shape?
5. How do we determine it?

Some observations:

1. We should expect clustering around 1 or more modes
2. Variables with little impact will not introduce new modes or substantially alter the shape of the distribution
3. Adding a new low-impact variable (dimension) should just stretch the existing modes uniformly along the new dimension

This brings to mind a brute-force approach that would involve:

1. observing all possible marginal distributions
2. applying a measure to each, determining the degree of information within, select one that maximizes information and penalizes for number of variables

The first step can possibly be shortcut by reducing incrementally, but may not find the global optimum.   The notion of “information” also needs to be defined.   I’ll post more later on this.

Another approach would be to formulate as an expectation maximisation problem, but I have not worked out how this would be done.