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Comparison Study on the Performances of NLL and GMM for Estimating Diffusion Processes
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 Title & Authors
Comparison Study on the Performances of NLL and GMM for Estimating Diffusion Processes
Kim, Dae-Gyun; Lee, Yoon-Dong;
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 Abstract
Since the research of Black and Scholes (1973), modeling methods using diffusion processes have performed principal roles in financial engineering. In modern financial theories, various types of diffusion processes were suggested and applied in real situations. An estimation of the model parameters is an indispensible step to analyze financial data using diffusion process models. Many estimation methods were suggested and their properties were investigated. This paper reviews the statistical properties of the, Euler approximation method, New Local Linearization(NLL) method, and Generalized Methods of Moment(GMM) that are known as the most practical methods. From the simulation study, we found the NLL and Euler methods performed better than GMM. GMM is frequently used to estimate the parameters because of its simplicity; however this paper shows the performance of GMM is poorer than the Euler approximation method or the NLL method that are even simpler than GMM. This paper shows the performance of the GMM is extremely poor especially when the parameters in diffusion coefficient are to be estimated.
 Keywords
Diffusion process;NLL;GMM;Vasicek model;GBM;
 Language
Korean
 Cited by
1.
확산모형에 대한 일반화적률추정법의 개선,최영수;이윤동;

응용통계연구, 2013. vol.26. 5, pp.767-783 crossref(new window)
1.
Improved Generalized Method of Moment Estimators to Estimate Diffusion Models, Korean Journal of Applied Statistics, 2013, 26, 5, 767  crossref(new windwow)
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