A Method of Discovering Patterns to Predict Specified Events from Financial Time Series

This paper proposes a method to discover time series patterns predictive of the occurrence of specified events. The process of technique realization is mainly composed of four steps: specifying interest function and parameters; searching ODs, clustering ODs for candidate patterns and identifying patterns. A simulation study is conducted as verification. And an application study in the stock market is introduced to demonstrate its performance.