This paper describes the profitability of technical trading rules which are enhanced by the use of neural networks on crude oil futures contracts traded on Chicago Merchantile Exchange and on Bursa Derivative Malaysia. The profitable returns on the futures contract on crude light oil futures traded from 2/1/2008 to 31/12/2014 offer a piece of evidence on the ability of technical trading rules using neural networks to outperform the threshold benchmark, buy and hold. The results here suggest that it is worthwhile to design, build and develop more robust, machine learning algorithms like neural networks enhanced moving average technical indicator to enhance portfolio returns. The conclusion drawn is that neural network can be used in technical analysis as a predictor for futures market prices.
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