A test for a parametric form of the volatility in second-order diffusion models

Tianshun Yan () and Changlin Mei ()
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Tianshun Yan: Xi’an Jiaotong University
Changlin Mei: Xi’an Jiaotong University

Computational Statistics, 2017, vol. 32, issue 4, No 17, 1583-1596

Abstract: Abstract Second-order diffusion models have been found to be promising in analyzing financial market data. Based on nonparametric fitting, Nicolau (Stat Probabil Lett 78(16):2700–2704, 2008) suggested that the quadratic function may be an appropriate specification of the volatility when a second-order diffusion model is used to analyze some European and American financial market data sets, which motivates us to develop a formal statistical test for this finding. To achieve the task, a generalized likelihood ratio test is proposed in this paper and a residual-based bootstrap is suggested to compute the p value of the test. The analysis of many real-world financial market data sets demonstrates that the quadratic specification of the volatility function is in general reasonable.

Keywords: Second-order diffusion models; Generalized likelihood ratio test; Local-linear fitting; Bootstrap (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s00180-016-0685-z

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