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

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

研究成果: 書貢獻/報告類型會議論文篇章

摘要

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.

原文英語
主出版物標題Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
DOIs
出版狀態已發佈 - 2006
事件9th Joint Conference on Information Sciences, JCIS 2006 - Taiwan, ROC, 臺灣
持續時間: 2006 十月 82006 十月 11

出版系列

名字Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
2006

其他

其他9th Joint Conference on Information Sciences, JCIS 2006
國家/地區臺灣
城市Taiwan, ROC
期間2006/10/082006/10/11

ASJC Scopus subject areas

  • 工程 (全部)

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