Support Vector Machine as an Efficient Framework for Stock Market Volatility Forecasting

Author： Gavrishchaka Valeriy   Banerjee Supriya  

Publisher： Springer Publishing Company

ISSN： 1619-697X

Source： Computational Management Science, Vol.3, Iss.2, 2006-04, pp. : 147-160

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Related content

Short term forecasting with support vector machines and application to stock price prediction

By Ince Huseyin  

International Journal of General Systems, Vol. 37, Iss. 6, 2008-12 ,pp. : 677-687

Taylor & Francis Ltd

Access to resources Recommend Favorite

A Support Vector Machine Based Approach for Forecasting of Network Weather Services

By Prem Hema   Raghavan N.  

Journal of Grid Computing, Vol. 4, Iss. 1, 2006-03 ,pp. : 89-114

Springer Publishing Company

Access to resources Recommend Favorite

Modeling Shanghai stock market volatility

By Xu J.  

Annals of Operations Research, Vol. 87, Iss. 1, 1999-01 ,pp. : 141-152

Springer Publishing Company

Access to resources Recommend Favorite

Multiclass Lagrangian support vector machine

By Hwang Jae  

Neural Computing & Applications, Vol. 22, Iss. 3-4, 2013-03 ,pp. : 703-710

Springer Publishing Company

Access to resources Recommend Favorite

Projection Support Vector Machine Generators

By González-Castaño Francisco J.  

Machine Learning, Vol. 54, Iss. 1, 2004-01 ,pp. : 33-44

Springer Publishing Company

Access to resources Recommend Favorite