Combing extended Kalman filters and support vector machines for online option price forecasting

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

Abstract

This study combines extended Kalman filters (EKFs) and support vector machines (SVMs) to implement a fast online predictor for option prices. The EKF is used to infer latent variables and makes a prediction based on the Black-Scholes formula, while the SVM is employed to capture the nonlinear residuals between the actual option prices and the EKF predictions. Taking option data traded in Taiwan Futures Exchange, this study examined the forecasting accuracy of the proposed model, and found that the hybrid model is superior to traditional feedforward neural network models, which can significantly reduce the root-mean-squared forecasting errors.

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

Fingerprint

Extended Kalman filters
Support vector machines
Feedforward neural networks

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Huang, S-C. (2006). Combing extended Kalman filters and support vector machines for online option price forecasting. In Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006 [CIEF-36] (Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006; Vol. 2006). https://doi.org/10.2991/jcis.2006.53
Huang, Shian-Chang. / Combing extended Kalman filters and support vector machines for online option price forecasting. Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006. 2006. (Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006).
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Huang, S-C 2006, Combing extended Kalman filters and support vector machines for online option price forecasting. in Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006., CIEF-36, Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006, vol. 2006, 9th Joint Conference on Information Sciences, JCIS 2006, Taiwan, ROC, Taiwan, 06-10-08. https://doi.org/10.2991/jcis.2006.53

Combing extended Kalman filters and support vector machines for online option price forecasting. / Huang, Shian-Chang.

Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006. 2006. CIEF-36 (Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006; Vol. 2006).

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

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Huang S-C. Combing extended Kalman filters and support vector machines for online option price forecasting. In Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006. 2006. CIEF-36. (Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006). https://doi.org/10.2991/jcis.2006.53