Using artificial neural networks

Using artificial neural networks

18 July 2014, 14:12
Sergey Golubev
1
466

Artificial neural networks are sophisticated computer systems that mimic the working of the human brain. Often referred to as ‘artificial intelligence’, neural networks can perform various functions of the human brain and have cognitive abilities—that is, the ability to learn, which most computer programs do not. Deep Blue, the famous IBM computer that played chess against Garry Kasparov, and Deep Insight, an expert system that can recognise profitable trading patterns in the stock market, are examples of neural network systems that can perform functions and also learn as they go along.

Neural networks can be trained to perform such functions as speech and handwriting recognition, credit card fraud protection, establishing credit risk limits, loan application processing, and analysis of market research data. Neural networks are also employed in monitoring power plant systems, automatic language translation, text-to-speech conversion, bomb detection, prediction of traffic accidents, medical diagnostics and aircraft radars. In fact, neural networks and Kalman filters are used wherever an unknown state of a dynamic system, which is obscured by randomness or noise, has to be estimated.

The application of artificial neural networks to trading the financial markets is an interesting practical use of this technology. Just as traders are able to recognise patterns of arbitrage opportunities based on their trading experience, artificial neural networks can be trained to identify profitable trading opportunities. This technology has a distinctive edge over traders in that they are able to completely isolate human emotions such as greed and fear from the decision-making process.

An experienced trader can easily identify whether a particular market is ‘bid’ or ‘offered’ by looking at a computer screen blinking with price updates. However, traders need coffee breaks to escape from the stress of such highly focused work. Artificial neural networks can perform the same task 24/7, and free of emotions, too. One of the commandments of trading is that, “If you have a position, forget your emotion”. This is easy to remember, but in practice most traders develop emotional attachment to their positions or their models, even after the markets have proven them wrong.

The saying, “The markets may not be smart, but they are always right”, is another principle taught to all traders. In the book, When Genius Failed: The Rise and Fall of Long Term Capital Management, there is an anecdote about Lawrence Hillibrand, who insisted that his trading models were right even after he had raked up trading

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