A data analytic approach to forecasting daily stock returns in an emerging market

Forecasting stock market returns is a challenging task due to the complex nature of the data. This study develops a generic methodology to predict daily stock price movements by deploying and integrating three data analytical prediction models: adaptive neuro-fuzzy inference systems, artificial neural networks, and support vector machines. The proposed approach is tested on the Borsa Istanbul BIST 100 Index over an 8 year period from 2007 to...