Abstract
The paper presents a method to estimate diffusion parameters without specifying drift functions of one dimensional stochastic differential equations. We study finite sample properties of the estimator by numerical experiments at several observation time intervals with total time interval fixed. The results show the estimator is getting efficient as observation time interval becomes smaller. By comparing with the quadratic variation method which is proven to have consistency, the proposed method produces almost the same finite sample properties as that.
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Shoji, I. (2003). Estimation of Diffusion Parameters by a Nonparametric Drift Function Model. In: Liu, J., Cheung, Ym., Yin, H. (eds) Intelligent Data Engineering and Automated Learning. IDEAL 2003. Lecture Notes in Computer Science, vol 2690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_29
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DOI: https://doi.org/10.1007/978-3-540-45080-1_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40550-4
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