Stock Index Prediction Based on the Analytical Center of Version Space

摘要

This paper presents a novel method for predicting the stock index based on the multiclass classification. The strategy firstly discretizes the stock index to different interval and assigns a class label to each interval, which yields a multiclass classification problem. After briefly reviewing multiclass classification algorithm, a multiclass classifier based on analytical center of version space is proposed and applied to stock index prediction. Experiments on shanghai stock index demonstrates that the strategy of stock index prediction proposed is validated and of practical value.