Trading with Artificial Neural Networks on Large-, Mid- and Small-Cap Stocks : Exploring if Market Cap has an effect on portfolio performance when trading with Artificial Neural Networks trained on historical stock data

Abstract: n this report one-day ahead stock prediction using artificial neural networks (ANN) is studied on stocks belonging to different market caps. Hennes & Mauritz, EnQuest PLC and Rottneros have been selected, representing large-, mid- and small-cap companies. This report aims to investigate whether a company's market cap affects the ability to predict stock prices when ANNs are trained using historical stock data. The study was carried out using feedforward ANNs and trained using the Levenberg-Marquardt backpropogation algorithm. The results from the study show that the large-cap company H&M was easier to predict than the mid- and small-cap companies. Although the results from this study indicate that a company's market cap affects the ability to predict stock prices using ANNs, a deeper, more extensive investigation has to be carried out in order to draw any real conclusions.