A New Neural Network Framework for Profitable Long-Short Equity Trading

Neural Network methods for stock market prediction have received attention in the literature. However, the methods that form the current state of the art have generally been unable to demonstrate sustained profitability over a significant period of time. The authors of this paper show, through the application of over ten years of experience in Quantitative Modelling and Trading, a proof of concept for a new framework for profitable long-short equity trading. Testing shows that the method could have been used to beat market benchmarks over a seven year period even with the inclusion of transaction costs.