Warrants price forecasting using kernel machine & EKF-ANN: A comparative study

Hsing Wen Wang, Jian Hong Wang, Tse Ping Dong, Sheng Hsun Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Due to the six unreasonable assumptions companioned with the Black-Scholes options pricing model (BSM), which often make the miss-pricing result because of the difference of market convention in practical. This study try to combine the BSM and extended Kalman filters-based artificial neural networks (EKF-ANN) to deal with the limitation of consideration of the influences from many unexpected real world phenomena. If we were to soundly take these phenomena into account, the pricing error could be reduced. In this paper, we try to make a comparative study with examined the forecasting accuracy between the BSM-based kernel machines (KM-BSM) and the BSM-based EKF-ANN (EKF-ANN-BSM). From the evidence of Taiwan Warrants market, we found that the performance indicates the KM is superior to the others, and the hybrid EKF-ANN-BSM framework is also better than the pure EKF-ANN. The results show that the KM-BSM and hybrid model could significantly reduce the normalized root-mean-square-errors (NRMSE) of forecasting, it helps to provide an alternative way to refine the options valuation.

Original languageEnglish
Title of host publicationProceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
DOIs
Publication statusPublished - 2006 Dec 1
Event9th Joint Conference on Information Sciences, JCIS 2006 - Taiwan, ROC, Taiwan
Duration: 2006 Oct 82006 Oct 11

Publication series

NameProceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
Volume2006

Other

Other9th Joint Conference on Information Sciences, JCIS 2006
CountryTaiwan
CityTaiwan, ROC
Period06-10-0806-10-11

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Wang, H. W., Wang, J. H., Dong, T. P., & Hsu, S. H. (2006). Warrants price forecasting using kernel machine & EKF-ANN: A comparative study. In Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006 [CIEF-235] (Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006; Vol. 2006). https://doi.org/10.2991/jcis.2006.99