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 parameterestimatesofhestonstochasticvolatilitymodelwithmleandconsistentekfalgorithm Wang Ximei1; He Xingkang1; Bao Ying2; Zhao Yanlong1 2018 Source Publication sciencechinainformationscience ISSN 1674-733X Volume 61Issue:4Pages:17 Abstract Heston model is the most famous stochastic volatility model in finance. This paper considers the parameter estimation problem of Heston model with both known and unknown volatilities. First, parameters in equity process and volatility process of Heston model are estimated separately since there is no explicit solution for the likelihood function with all parameters. Second, the normal maximum likelihood estimation(NMLE) algorithm is proposed based on the Ito transformation of Heston model. The algorithm can reduce the estimate error compared with existing pseudo maximum likelihood estimation. Third, the NMLE algorithm and consistent extended Kalman filter(CEKF) algorithm are combined in the case of unknown volatilities. As an advantage, CEKF algorithm can apply an upper bound of the error covariance matrix to ensure the volatilities estimation errors to be well evaluated. Numerical simulations illustrate that the proposed NMLE algorithm works more efficiently than the existing pseudo MLE algorithm with known and unknown volatilities. Therefore, the upper bound of the error covariance is illustrated. Additionally, the proposed estimation method is applied to American stock market index S&P 500, and the result shows the utility and effectiveness of the NMLE-CEKF algorithm. Language 英语 Document Type 期刊论文 Identifier http://ir.amss.ac.cn/handle/2S8OKBNM/49724 Collection 系统科学研究所 Affiliation 1.中国科学院数学与系统科学研究院2.Risk Management Department, Industrial and Commercial Bank of China Recommended CitationGB/T 7714 Wang Ximei,He Xingkang,Bao Ying,et al. parameterestimatesofhestonstochasticvolatilitymodelwithmleandconsistentekfalgorithm[J]. sciencechinainformationscience,2018,61(4):17. APA Wang Ximei,He Xingkang,Bao Ying,&Zhao Yanlong.(2018).parameterestimatesofhestonstochasticvolatilitymodelwithmleandconsistentekfalgorithm.sciencechinainformationscience,61(4),17. MLA Wang Ximei,et al."parameterestimatesofhestonstochasticvolatilitymodelwithmleandconsistentekfalgorithm".sciencechinainformationscience 61.4(2018):17.
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