One divide in ideas on trading system development concerns the applicability of trading models to time periods and markets.

The markets consideration is easily explained: Should a model be designed for one product, such as oil, equities, currencies, etc.? That can be drilled down further: Which oil futures (months, products), which equities (sectors, size), and which currencies (USD-pairs, regional)?

The time period consideration is explained in terms of when a model should work: over all market data, a selected time period, a regime based on specified metrics, etc. (For clarity, time period does not refer to time interval, such as 5-minute, day, tick/inconsistent, etc.)

These considerations boil down to this question: Should a trading system work on all time periods and in all markets?

Some say that a truly robust system will have captured an underlying markets law, much like in physics, and will therefore work at all times in all markets. Others argue that a system will work for the regime that it is designed for, and that detecting the regime is part of the system.

I posted this question in a thread in Nuclear Phynance, so you can check there - it is actually a slight threadjack of the “trade optimization” thread in the Trading section.

But, thanks to another Nuclear Phynance member, I came across an article written by Pablo Triana that discusses Jim Simons’ (of RenTec) take on this:

But perhaps the most interesting observation came in response to a question posed by the moderator, Nobel Prize-winner Robert Engle: “Why don’t you publish your research, the theory behind your trading methods? If not while you are active in the markets, perhaps later on.”Simons’ reply – there is nothing to publish. Quantitative investment is not physics. The markets have no fundamental, set-in-stone truths, no immutable laws. Financial “truth” changes constantly, so that a new paper would be needed almost every week.

The implication is that there is no eternal theorem of finance that could serve as an infallible guide through all the ages. Indeed, there can be no Einstein or Newton of finance. Even the math genius raking in $1 billion and consistently generating 30%-plus annual returns wouldn’t qualify. The terrain is just too lawless.

While Simons has a higher level of comprehension on this subject, I would agree with his assessment. Bill Rempel suggested that in this camp, a model may be regime specific, and the system will chose to activate/deactivate the model as needed, in essence making it work across all time periods and all markets. At least, that is what I interpreted from his response at Nuclear Phynance.

I have added another model to the Models page on foquant.com. This is a variation of the original Black Scholes model, however this uses the formulas from Black’s 1976 paper, interpreted in T.W. Epps’ Pricing Derivative Securities, for pricing options on futures.

Following up on my prior post, I have uploaded another model to the Models page of foquant.com.

This model alters the prior model, as it now allows the underlying to pay a dividend. In a sense making the original model redundant, this new model will also accurately price a non-dividend-paying underlying. But, the separation of names calls attention to the differing equations.