Title :
Research on the mixed method of option price forecasting based on support vector machine
Author_Institution :
Sch. of Manage., Xiamen Univ., Xiamen, China
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;
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
DOI :
10.1109/AIMSEC.2011.6010475