From the April 2013 issue of Futures Magazine • Subscribe!
Casting neural nets into modern markets  The key to developing
intelligent trading systems is to start with a reliable rule-
based strategy. The neural network, genetic algorithm, kernel
regression or other machine-learning method should be designed
to enhance the system’s already positive performance.  However,
this core system does not have to be the Holy Grail. While this
building block may not be tradeable as a standalone system, it
should demonstrate an ability to generate a positive return over
time, even if that return is lacking in terms of its risk-reward
balance. For example, in trend-following markets, moving-
average-crossover systems perform well. Similarly, we could
employ a classic n-day breakout of highs or lows. Intermarket
divergence strategies also are viable, as are those that employ
traditional technical indicators or fundamental analysis, such
as breadth data for the S&P 500, the Volatility Index or
price/earnings ratios, to name