Neural Computing and Applications

, Volume 20, Issue 8, pp 1193–1203 | Cite as

Correlation-aided support vector regression for forex time series prediction

  • Shaoning PangEmail author
  • Lei Song
  • Nik Kasabov
ISNN 2010


Market is often found behaving surprisingly similar to history, which implies that correlation exists significant for market trend analysis. In the context of Forex market analysis, this paper proposes a correlation-aided support vector regression (cSVR) for time series application, where correlation data are extracted through a graphical channel correlation analysis, compensated by a parameterized Pearson’s correlation to exclude noise meanwhile minimize useful information lost. The effectiveness of cSVR against SVR is confirmed by experiments on 5 contracts (NZD/AUD, NZD/EUD, NZD/GBP, NZD/JPY, and NZD/USD) exchange rate prediction within the period from January 2007 to December 2008.


Support vector regression Graphical channel correlation Pearson’s correlation Forex time series prediction 


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Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  1. 1.Auckland University of TechnologyAucklandNew Zealand

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