Nonparametric Methods in Continuous-Time Finance: A Selective Review

Zongwu Cai () and Yongmiao Hong

No 2003,15, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: This paper gives a selective review on the recent developments of nonparametric methods in continuous-time finance, particularly in the areas of nonparametric estimation of diffusion processes, nonparametric testing of parametric diffusion models, and nonparametric pricing of derivatives. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weakness are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

Keywords: Continuous time model; derivative pricing; jump process; kernel smoothing; nonparametric test; non-stationarity; options (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (7)

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