On 2009-04-22, F George McDuffee wrote:
On Tue, 07 Apr 2009 19:05:18 -0500, Ignoramus7501
wrote:

My own programming involves mathematical modeling of financial
derivatives prices, which is in many ways akin to mathematical physics
models. That's heavy duty math involving partial derivatives, and
such.

i
-------------
Any comments that you can make about why Monte Carlo simulation
is not being used for the bank "stress" tests?

It would appear that the range of outcomes and probabilities this
generates would be far more useful that the expected pass/fail
rankings.

But the distribution of such outcomes depends on assumptions of your
monte carlo simulation. And no one knows what assumptions to make
(what is the standard deviation of housing prices, etc). But
your idea is a good idea in the right direction. The simulation would
involve not only purely random variables, but rather, their likely
effect on other variables.

Example, let's say that a variable "housing default rate" would rise
to a certain amount. That would have a direct effect on the banks'
capital levels, but it would also have an effect on housing prices,
further influencing the default rate of mortgages that would be deeper
underwater.

Then it would affect how much more would be the losses of the likes of
AIG and other mortgage insurers.

In other words, any realistic simulation would go beyond "pick a
number" game and would model at least the basic dynamics of the
process.

The distributions of most of the inputs/metrics such as prime
interest rates, unemployment, money market interest rates, etc.
should be the same across all institutions.

Any thoughts on the use of Cauchy v normal distributions? Also
how do you rank the Excel add-ins for MC simulation/analysis?
Any good?

I do not use excel add-ins, personally.

i