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- W2000923870 abstract "This study combines a modified Kalman filter (MKF) and support vector machines (SVMs, a type of kernel machines) to implement a fast online predictor for option prices. The latent variables in Black-Scholes formula are estimated by the MKF. The residuals in MKF predictions are handled by an SVM. Using option data of Taiwan Futures Exchange, the proposed model is compared with traditional predictors. Empirical results confirmed that the new model is superior to traditional neural network models, which remarkably reduce the root-mean-squared forecasting errors." @default.
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- W2000923870 date "2013-03-01" @default.
- W2000923870 modified "2023-09-23" @default.
- W2000923870 title "Financial Forecasting by Modified Kalman Filters and Kernel Machines" @default.
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- W2000923870 doi "https://doi.org/10.1080/09720510.2013.777575" @default.
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