Eric Hoyle, CFA, is a Duke University graduate and a Yale MBA who remembers his Yale professors "sneering" at the very mention of technical analysis. (We can just imagine their faces if someone mentioned neural networks!) He also remembers a paper he wrote at Yale in which he argued that, on a risk-adjusted basis, the returns achieved by hedge fund managers were not worth the costs. However, now Eric has done so well with the models he has created with the NeuroShell DayTrader Professional, he is starting a hedge fund using it as one of his major tools.

Eric's change in attitude was brought about by his experience after business school. Eric explains that "in business school we were taught that everyone used fundamentally the same tools and had the same information, therefore, no analyst could consistently outperform. However, I see the NeuroShell Trader as a new tool. It helps to model relationships traditional analysts would miss, or not discover until it was too late to trade on them." He feels as a hedge fund manager, he adds value because "the key is selecting the right inputs, which requires an understanding of the markets. The number of indicators and relationships a trader could attempt to model are limitless; it is a full time job. I hope to provide an opportunity for investors to take advantage of my knowledge of the markets and the power of this program."

Prior to starting the hedge fund, Eric worked as a fixed income analyst for the mutual fund subsidiary of Raymond James Financial, and before that, on the trading desk of Ferris, Baker Watts. It is very clear that Eric knows what he is doing when it comes to trading.

Before purchasing the NeuroShell Trader Professional, he experimented with a competitor's neural network program and found it interesting, but frustrating to use. "The amount of time required to create a basic model was formidable. Creating a complex trading strategy would have been out of the question." Later, when he saw an ad for the debut of the NeuroShell Trader program, he decided to try it. Contrary to his prior experience, he found that the NeuroShell Trader was "user friendly and had the ability to easily create complex trading strategies." His results, he says, "have been phenomenal. I've done very well."

Like so many of the successful NeuroShell users we talk to, Eric says he does not use rocket science in what he puts into the Trader. He builds trading strategies and optimizes them to maximize return. Then he "eye balls" the out of sample trading to be sure he wants to go forward and trade the system, comparing it to a buy and hold strategy. "It's important to feel like the system has learned some relationships between the variables I've selected and not just made a few great trades."

Eric models U.S. Equities and tries to diversify his trading across markets and industries as a risk control measure. Typically, his models employ just one neural net in the trading strategy. The inputs to his nets are simple technical indicators from our price momentum category, often applied on an inter-market basis - to other issues and indices. He does not have a favorite or consistently good indicator. He has found that simple is better: simple indicators, and no more than 5 or 6 of them to assure generalization. When Eric optimizes, he just uses the parameter search function.

We asked Eric about how much data he uses for modeling. "In the beginning, I was probably using too much data for my models," he explained. "I wanted lots of out of sample results to be confident that my models would work well going forward. However, market relationships are dynamic, and as the relationships change your models need to change. I found that models that tested well over a long period actually had less chance of continuing to be profitable in the future. My best results were achieved with nets using roughly 9 months of data, and perhaps 2 or 3 walk forward tests of just 1 to 3 months each."

"That was BEFORE the NeuroShell DayTrader," he went on. "The DayTrader is great because it allows you to use a lot more data over shorter time periods. Shorter periods are particularly advantageous when the markets are rapidly changing. I now train my nets on only a month or two of data, using 10-minute bar increments. I may not technically be 'day trading,' however, day trading is not necessarily my goal. My trades typically last two or three days and I will have exposure to both the long side and the short side of the market. I am careful not to be too heavy on either side and I diversify as much as possible. I'm not concerned about being absolutely market neutral."

We asked Eric if he had any advice for other NeuroShell users. "In addition to keeping the number of inputs to your nets low," he suggested, "use a small number of hidden neurons in your neural network models. This helped me create much better trading systems. At first, I felt I was making my system less robust, however, I think using less neurons forces the model to generalize better. There is a lot of noise in the market, and you do not want your system to trade based on noise. Let your system learn the basic relationships and trade on them." (Editors note: adjusting the number of hidden neurons is a feature only found in the NeuroShell Trader Professional and NeuroShell DayTrader Professional.)

At the time of this interview, Eric's company had yet to be named, but we will add that information here when we have it, and keep you updated on his progress. We do know that it will be based in Eric's hometown of Philadelphia.

Update 9/28/00

Eric's new company got off and running in August. Here is the contact information:

Eric L. Hoyle, CFA
Oval Oak Capital Management
ehoyle@oval-oak.com
(215) 985-4911