DocumentCode
3171817
Title
Research on the mixed method of option price forecasting based on support vector machine
Author
Meng, Li
Author_Institution
Sch. of Manage., Xiamen Univ., Xiamen, China
fYear
2011
fDate
8-10 Aug. 2011
Firstpage
6755
Lastpage
6758
Abstract
In this study, the authors discuss a mixed method which involves some forecasting techniques like linear technique (ARMA), BS option pricing function, and mixed BRF. These forecasting techniques are combined by support vector machine (SVM) to forecast the option price. This mixed method can avoid disadvantages which the single forecasting techniques have, and be more accurate and stable to forecast the option prices when the maturity is coming. The rationality of the method has been proved by experimental result which is based on the foreign exchange option price data.
Keywords
autoregressive moving average processes; forecasting theory; pricing; support vector machines; SVM; foreign exchange option price data; option price forecasting; option pricing function; support vector machine; Artificial neural networks; Forecasting; Linear approximation; Predictive models; Pricing; Support vector machines; Time series analysis; ARMA; BRF; BS; RMSE; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location
Deng Leng
Print_ISBN
978-1-4577-0535-9
Type
conf
DOI
10.1109/AIMSEC.2011.6010475
Filename
6010475
Link To Document