The Role of Additional Information in Option Pricing: Estimation Issues for the State Space Model
學年 99
學期 1
出版(發表)日期 2010-12-01
作品名稱 The Role of Additional Information in Option Pricing: Estimation Issues for the State Space Model
作品名稱(其他語言)
著者 Wang, Ren-Her; Aston, J. A. D.; Fuh, Cheng-Der
單位 淡江大學財務金融學系
出版者 New York: Springer New York LLC
著錄名稱、卷期、頁數 Computational Economics 36(4), pp.283-307
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.
關鍵字 Kalman filter; Particle filter; Stochastic volatility model; Volatility forecasting
語言 en
ISSN 0927-7099; 1572-9974
期刊性質 國外
收錄於 SCI SSCI
產學合作
通訊作者 Wang, Ren-Her
審稿制度
國別 USA
公開徵稿
出版型式 紙本
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