we developed trading software for a customer that implemented an extremely simple algorithm to decide between buying/selling stocks. Each calculation took less than a millisecond.

Of course this wasn't very impressive. Something that calculates so fast can't be worth anything.

So about half of the project's development time was spent on creating a realistic (that is: unpredictable, jerky) progress bar that created the illusion of a complex analysis taking 30 seconds or so. :-)

This is an interesting proposal. We are using something similar at my company, which offers one of the most detailed databases for retail structured products.

What some people posting here misunderstand is that the proposal isn't about making available magic formulas or explaining, why a call option retails at $12,34 at a given moment. It is simply about calculating the resulting cash flow that the buyer receives from a product in a given scenario. So it let's you try out, what you receive when you assume that at maturity the underlying stock is at $15.

It does not automatically tell you if the option should be worth $12,34 or $2,34 right now. The current fair value is part of the magic sauce: It can only be calculated with the right assumptions, eg. the assumed volatility, the current interest rate structure, ... Different market participants will usually make different assumptions here, but with these assumptions plus a numerical pricing model plus the program supplied to you under this scheme you can also calculate your fair value for the product.

In my opinion a general purpose language like Python is not a good fit for this use. In any case, very strict interfaces would need to be defined. If there were multiple ways to input the assumed stock price (which is just one of a very large number of parameters), then this would not be much more useful, than the current written documentation of the products. With a general purpose language there might also be hundreds of possibilities to program even simple structured products, which makes reading/debugging these programs needlessly hard.

We have developed a special purpose language internally, that can be used to easily program variable cash flows that depend on other market data. The good thing about such a special purpose language is that most standard product have a generic representation, that is short enough to be easily read, understand and (if needed) debugged. We supply "code" for the more than 400.000 active retail structured products in our database to our customers and they can for example try out, which product works best for then in a given investment scenario.

You might have a similar effect by using a generic language + strict interface definition + enforced use of a standard library. But a compiler/interpreter for a simple special purpose language can easily be implemented in most environments while many possible users of this project might not like adding a full python-interpreter to their system.

bye, Paul.

That's not a wind turbine, but a joke. That thing hardly produces as much energy as a hamster running around in his little wheel.