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《第36届中国控制会议论文集(B)》2017年
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Parameters Estimations for Continuous-Time Stochastic Volatility Models

Ximei Wang  Hang Zhang  Yanlong Zhao  
【摘要】:Stochastic volatility(SV) models take a very important role in financial market, while there still exist some difficulties in estimating parameters in SV models. In this paper, a unified parameter estimation algorithm is proposed to estimate continuoustime SV model. Parameters in equity prices and volatilities stochastic processes are estimated separately after orthogonalization of Brownian motion in SV models. A closed-form of Maximum Likelihood Estimation(MLE) and moment estimation results for four parameters in SV models are deducted. Five typical SV models are simulated to reveal the characteristics in empirical volatilities data. Parameter estimation results are presented to prove the convergence of estimation algorithm. We also compare our algorithm with Least Square(LS) estimations and numerical solutions of all the parameters in with MLE method, respectively.LS can only work in a specific form of SV models and the convergence speed is limited. Numerical solutions of the likelihood function with four parameters are unstable and can not converge to true values of all the parameters. Thus our algorithm works more efficiently than other methods.
【作者单位】:Academy of Mathematics and Systems Science,Chinese Academy of Sciences
【基金】:in part by supported National Key Research and Development Program of China under 2016YFB0901902 the National Natural Science Foundation of China under grant 61622309 the National Key Basic Research Program of China(973 Program) under Grant No.2014CB845301
【分类号】:F830.91
【正文快照】:
1 IntroductionIn recent years,stochastic volatility(SV)models are ap-plied to depict dynamic of equity returns by more andmore banks,financial institutions,and academic researchers.Compared with the most famous Black Scholes(BS)model([9]),where volatilit

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