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    題名: The Role of Additional Information in Option Pricing: Estimation Issues for the State Space Model
    作者: Wang, Ren-Her;Aston, J. A. D.;Fuh, Cheng-Der
    貢獻者: 淡江大學財務金融學系
    關鍵詞: Kalman filter;Particle filter;Stochastic volatility model;Volatility forecasting
    日期: 2010-12
    上傳時間: 2011-10-05 20:56:36 (UTC+8)
    出版者: New York: Springer New York LLC
    摘要: We consider two competing financial state space models and investigate whether additional information in the form of option price data is helpful to the estimation of either the unobservable state variable (volatility) or the unknown parameters in the model. The complete discussion of the estimation problem in the presence of additional information involves decisions about filtering methods, the quality of the new information, the correlation between state variables and out-of-sample forecast performance. It is found that the state variable estimation is more sensitive than the parameter estimation to the correlation, information quality and the assumed linearity or non-linearity of the underlying model. As a result of the investigation of these factors, the particle filter is shown to be an attractive method for computing posterior
    distributions for these models.
    關聯: Computational Economics 36(4), pp.283-307
    DOI: 10.1007/s10614-010-9240-0
    顯示於類別:[財務金融學系暨研究所] 期刊論文


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