期刊名称：International Journal for Research in Vocational Education and Training (IJRVET)
印刷版ISSN：2197-8646
出版年度：2011
卷号：3
期号：2
出版社：European Research Network in Vocational Education and Training (VETNET), European Educational Research Association
摘要：This paper reviews the recent option pricing literature and investigates how clustering and classification can assist option pricing models. Specifically, we consider non-parametric modular neural network (MNN) models to price the S&P-500 European call options. The focus is on decomposing and classifying options data into a number of sub-models across moneyness and maturity ranges that are processed individually. The fuzzy learning vector quantization (FLVQ) algorithm we propose generates decision regions (i.e., option classes) divided by ‘intelligent’ classification boundaries. Such an approach improves generalization properties of the MNN model and thereby increases its pricing accuracy.
