May 1, 2013

Moving Averages

What if we forecasted the weather on temperature moving-averages?

It would seem silly. After all, ENIAC ran the first mathematical computations for a weather model in 1950. ENIAC is not an Icelandic singer. It’s the first true computer and was built by University of Pennsylvania professors in 1946 with funding from the United States Army.

Now, TV weather departments use models that consume data about jet streams, moisture, temperature fluctuations, topography and other factors to project outcomes. For instance, those models say it’ll snow in Denver tonight after 80-degree temperatures the past three days. Chances are they’re right. It’s a significant predictive advance over the old method, the Native American Rock model, in which a rock was hung on a string outdoors. If the rock was wet, it was raining. And so on.

Humans use mathematical models in many predictive ways today. In a subset of weather-forecasting, models anticipate the development and trajectory of hurricanes. We track seismic activity to forecast earthquakes with some measure of warning.

In one of the most interesting applications of mathematical modeling, scientists searching outer space for planets like ours have now identified at least one in a solar system beyond our own. How? With instruments so precise that they can measure differences in light as fine as turning a flashlight on and off on the moon. Slight dimming in measurable light is evidence of a shadow being cast along a path – proof of planets.

One area dominated by math today is the equity market. At Collective2.com, the community for trading systems, there are over 20,000 different models, from some 67,000 community members. There are scores of firms like Ninjatrader, DataArt, Connamara, Orbis, Etnasoft, Vankar, TradeKing and Cyborg Trading that will help brokers, traders, exchanges and institutions build sophisticated mathematical systems for trading your shares. While you watch moving averages.

Doesn’t it seem almost inconceivable in a world where we model hurricanes, climate-change, and seismic events and can identify light-variations in space equivalent to a flashlight on the moon, that issuers wouldn’t use equity-market behavioral models? What is this, the Paleolithic era?

Everybody else in the equity market including the exchanges, supposedly on your side, long ago embraced math. Just not for you. Because, what, you’re incapable of understanding markets?

I mean, really. Is the best we can do a moving average? John Bollinger invented his price bands, still a widely used technical indicator, in the 1980s. At least it’s mathematical. But it predates the Order Handling Rules, Reg ATS, decimalization, the Global Settlement, Rules 605 and 606, Reg FD, Reg SHO, Sarbanes-Oxley, Reg NMS and Dodd-Frank.

That’s why we invented statistically modeled behavioral measures like Rational Price for IROs.

In our advanced era, under rules that explicitly prohibit unfair discrimination in equity markets against issuers and information-processors, it seems right that you should know something more than your 50-day moving average.

Right?

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