Financial time series forecasting with machine learning techniques: A survey
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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 the machine learning technique used, the forecasting timeframe, 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. Artificial Neural Networks (ANNs) are identified to be the dominant machine learning technique in this area. We conclude with possible future research directions.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN 2010) |
| Pages | 25-30 |
| Number of pages | 6 |
| Publication status | Published - 2010 |
| Externally published | Yes |