Improving option price forecasts with neural networks and support vector regressions

Neurocomputing

Volumn 72, Issue 13-15, 2009, Pages 3055-3065

  Liang, Xun ^a   Zhang, Haisheng ^a   Xiao, Jianguo ^a   Chen, Ying ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Decision making; Forecasting; Hong Kong option market; Neural networks; Option prices; Support vector regressions

Indexed keywords

COMMERCE; DECISION MAKING; ECONOMICS; ELECTRONIC TRADING; FINANCIAL MARKETS; FORECASTING; INVESTMENTS; NEURAL NETWORKS; REGRESSION ANALYSIS;

CONVENTIONAL METHODS; FINANCIAL DERIVATIVES; NEURAL NETWORKS (NNS); NONPARAMETRIC METHODS; OPTION MARKETS; OPTION PRICE; PARAMETRIC METHOD; SUPPORT VECTOR REGRESSION (SVR);

COSTS;

ACCURACY; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; BINOMIAL DISTRIBUTION; CONTROLLED STUDY; DATA ANALYSIS SOFTWARE; DECISION MAKING; FINITE ELEMENT ANALYSIS; FORECASTING; HONG KONG; INVESTMENT; KERNEL METHOD; LINEAR SYSTEM; MARKETING; MATHEMATICAL COMPUTING; MONTE CARLO METHOD; NONLINEAR SYSTEM; NONPARAMETRIC TEST; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

EID: 77953106067     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2009.03.015     Document Type: Article

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