Maximum likelihood estimation of partially observed diffusion models

This paper develops a maximum likelihood (ML) method to estimate partially observed diffusion models based on data sampled at discrete times. The method combines two techniques recently proposed in the literature in two separate steps. In the first step, the closed form approach of Aït-Sahalia (2008...

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Main Authors: KLEPPE, Tore Selland, Jun YU, SKAUG, Hans J.
格式: text
語言:English
出版: Institutional Knowledge at Singapore Management University 2014
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在線閱讀:https://ink.library.smu.edu.sg/soe_research/1797
https://ink.library.smu.edu.sg/context/soe_research/article/2796/viewcontent/P_ID_52648_Yu_JOE_2014_MaxLikelihoodEstPartiallyObservedDiffusionModels.pdf
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機構: Singapore Management University
語言: English