Paired Evaluators Method to Track Concept Drift: An Application in Finance

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 423)

Abstract

We consider the problem of forecasting under the environments of sudden unexpected changes. The objective of the forecasting is to detect several different types of changes and to be adaptive to these changes in the automated way. The main contribution of this paper is a development of a novel forecast method based on paired evaluators, the stable evaluator and the reactive evaluator, that are good at dealing with consecutive concept drifts. A potential application of such drifts is Finance. Our back-testing using financial data in US demonstrates that our forecasting method is effective and robust against several sudden changes in financial markets including the late-2000s recessions.

Keywords

Window Size Forecast Error Excess Return Forecast Method Concept Drift 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Computer Science DepartmentUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.SPARX Asset Management Co. Ltd., JapanGate City OhsakiJapan

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