Troy Buckner from NuWave Investment Corp. has fine tuned the non-conventional pattern recognition capabilities of the NeuroShell Trader to create a Pattern Recognition Program with positive returns totaling 82.6% since 1996 (including both live and simulated data; live trading began in June of 2001). The Pattern Recognition Program is one of three trading methods used in the company’s Combined Portfolio investment plan.

Buckner, a principal at NuWave, says their Pattern Recognition Program uses the NeuroShell Trader along with the General Regression Neural Nets (GRNN) or prediction nets from the Adaptive Net Indicator add-on. Buckner uses a majority decision from three different nets to cover 35 different international stocks, bonds, currency, and commodities markets.

Buckner has been researching the use of neural nets in trading since 1989. The Pattern Recognition Program is based upon the assumption that markets exhibit a degree of repetitive price action that can be identified throughout history. He believes factors responsible for such repetition include fundamental factors such as supply, demand, economic cycles, interest rates, weather, seasonality, etc., and human factors such as fear, greed and other emotions.

GRNN nets are much more adaptive than typical neural nets, because they further "evolve" or "learn" with the pattern in each new bar they see (i.e., they retrain themselves with each new bar). GRNN nets learn the relationship between a set of inputs and a predicted value such as the momentum of the close by composing a formula of this relationship based on historical patterns.

Buckner said the inputs to his models include summaries of price information that a trader would see by looking at a monthly, weekly, and daily charts such as long term trends, the slope (rate of change), the volatility of bars, and the range of bars. Buckner describes his inputs as what a trader would see overall by looking at directional and volatility price data.

Buckner extends his analysis by looking at similar variables in different time frames. His GRNN models have a 24 day average holding periods for trades.

For the most part it takes only minutes to run models because Buckner has created a batch processor of sorts for the NeuroShell Trader by using a macro program that records key strokes.

“I think the structure of the NeuroShell Trader is superior in that it offers you options that don’t - overtrain a model, unlike the old backpropagation networks,” according to Buckner. “There you had to worry about selecting training and test sets. The Adaptive Net Indicators make it easy to automate because they automatically retrain every bar according to a moving window of history . I find GRNN to be more effective than backprop nets because GRNN works with in-sample data in a more consistent fashion, that is it doesn’t depend on how your select training and test sets or how many hidden neurons you train with. All I have to be concerned with is whether my historical training window is long enough to contain up, down, and sideways price activity.”

Buckner said there are four things that are essential to a systematic trader:

1. have a consistent approach
2. don’t overfit
3. create a model structure that applies across all markets.
4. allow the history of each market to guide trading in that contract (i.e. use S&P 500 history to generate S&P 500 trading signals, T-note history to guide trading of T-note signals etc.)

He likes the GRNN adaptive nets because there are few moving parts. , “It identifies the personality of each market while maintaining consistency with the modeling approach. You can use the same structure for each market, but allow only the history of a given market to affect trading signals in that market. In other words, each market can be modeled independently of the others but with the same structure. Because I use the same inputs and a constant smoothing factor for all markets, the length of history becomes the only real variable for the model created to trade each market.” Experience has taught him that the length of the training history doesn’t matter as much as diversifying across many trading markets.

“Overall, I see that the Pattern Recognition Program gives us a consistent edge coupled with solid risk control as part of our Combined Portfolio,” according to Buckner.

The Nuwave website is www.nuwavecorp.com

Below is a picture of Troy (on right) and his Nuwave partner, John Ryan.