TITLE

Forecasting Stock Index Movement using Support Vector Machines and Random Forest Method

AUTHOR(S)
Kumar, Manish; Thenmozhi, M.
PUB. DATE
March 2009
SOURCE
IIMB Management Review (Indian Institute of Management Bangalore;Mar2009, Vol. 21 Issue 1, p41
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
The authors predict the direction of movement of the S&P CNX NIFTY Market Index using Support Vector Machines (SVM) and Random Forest Method (RFM). The performance of these techniques is benchmarked against the neural network, logit and discriminant models. The experimental analysis suggests that SVM outperforms RFM, which in turn outperforms neural network, discriminant analysis and logit. SVM models will be useful in evolving successful investment strategies while operating in the stock market.
ACCESSION #
38213392

 

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