Market Timing Using Artificial Neural Networks

The emergence of artificial neural networks has given us some of the most impressive technological tools. Inspired by the human brain, these networks consist of interconnected artificial neurons that can detect patterns invisible to the human eye. These qualities have caught the attention of investors seeking ways to beat the market. In this thesis, we explore how artificial neural networks can be used to construct an active trading strategy and evaluate the strategy's performance against two benchmark strategies. Two stock indices were used to train neural networks using the lagged return as input to predict the market state. By using the networks' predictions, an active trading strategy w…