@inproceedings{650cabc9af404be591a691111bd18afa,
title = "Combining Monte Carlo filters with support vector machines for option price forecasting",
abstract = "This study proposes a hybrid model for online forecasting of option prices. The hybrid predictor combines a Monte Carlo filter with a support vector machine. The Monte Carlo filter (MCF) is used to infer the latent volatility and discount rate of the Black-Scholes model, and makes a subsequent prediction. The support vector machine is employed to capture the nonlinear residuals between the actual option prices and the MCF predictions. Taking the option transaction data on the Taiwan composite stock index, this study examined the forecasting accuracy of the proposed model. The performance of the hybrid model is superior to traditional extended Kalman filter models and pure SVM forecasts. The results can help investors to control and hedge their risks.",
author = "Huang, {Shian Chang} and Wu, {Tung Kuang}",
year = "2006",
month = jan,
day = "1",
doi = "10.1007/11908029_63",
language = "English",
isbn = "3540476938",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "607--616",
booktitle = "Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings",
address = "Germany",
note = "5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006 ; Conference date: 06-11-2006 Through 08-11-2006",
}