Non-linear dynamics apply to volatile or inconsistent change and are, thus, seem by some as the best means of analysing market behaviour and predicting price volatility. Critics of neural network theory claim that it is the ultimate curve-fitting exercise. The term 'curve-fitting' means that traders add rules to their system until it achieves a perfect hypothetical performance based on historical results. As history never repeats, curve-fitted systems generally fail when applied to real trading. Knowledge-based systems and 'fuzzy logic' also fall into the same realm, with the latter becoming increasingly popular among traders.
Genetic algorithms are an offshoot of artificial intelligence technology.
In Australia, professional users of neural networks, at least in financial markets, seem to lie low. One funds management organisation in Melbourne uses a neural network to trade the Share Price Index. Despite the ongoing development of the industry, neural nets remain the most well-known application of artificial intelligence to financial markets. This is probably because traders have been seduced by the concept of 'smart systems' with the ability to 'learn', an attribute more commonly applied to neural nets than the other forms of the technology. But neural networks can't think on behalf of a trader.