Stock index forecasting is vital for making informed investment decisions. This paper surveys recent literature in the domain of machine learning techniques and artificial intelligence used to forecast stock market movements. The publications are categorised according to their research motivation, the machine learning technique used, the surveyed stock market, the forecasting time-frame, the input variables used, and the evaluation techniques employed. It is found that there is a consensus between researchers stressing the importance of stock index forecasting and that the results are promising. Artificial Neural Networks (ANNs) are identified to be the dominant machine learning technique in this area. We conclude with possible future research directions.
- stock index forecasting,
- machine learning,
- financial data mining,
- decision support
Available at: http://works.bepress.com/bjoern_krollner/1/