A Reexamination of Diffusion Estimators With Applications to Financial Model Validation

By Jianqing Fan, Chunming Zhang. 2003

176 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/a56e15f8d4db37280d9a5be520fd893d266788ab

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Citations in the corpus

Nonparametric inference with generalized likelihood ratio tests (2007, background): “Therefore, it should not be surprised that the test in Fan and Zhang (2003) based on alternative models (1.6) is more powerful than the test constructed based only on the stationary Markovian assumption (Hong and Li, 2005; A˜‡t-Sahalia, Fan and Peng, 2005), when the data are indeed generated from ”
Exact and computationally efficient likelihood‐based estimation for discretely observed diffusion processes (with discussion) (2006, methodology): “This question is really of much broader intent, pertaining also to nonparametric methods of inference for discretely observed diffusions, such as those proposed by Aït-Sahalia (1996), Jiang and Knight (1997), Stanton (1997) and more recently by Fan and Zhang (2003) and Bandi and Phillips (2003).”
Sharp adaptive estimation of the drift function for ergodic diffusions (2005, methodology): “In the problem of estimation and validation of the model with discretely sampled high frequency observations, which is frequently used in mathematical finance, recent progress has been achieved by Fan and Zhang [15] and Aït-Sahalia and Mykland [2].”
Inference of trends in time series (2007, background): “For related discussions see Fan and Gijbels (1996, Sec 3.3) and Fan and Zhang (2003) .”
Nonparametric estimation of scalar diffusions based on low frequency data (2002, methodology): “Methods of this kind have been successfully applied to financial data [Aït-Sahalia (1996), Stanton (1997), Chapman and Pearson (2000) and Fan and Zhang (2003)].”
Statistical Methods with Varying Coefficient Models. (2008, background): “2) was studied by Rice and Silverman (1991) and Hart and Wehrly (1993) for functional data.”
Nonparametric Transition-Based Tests for Jump Diffusions (2009, unknown): “Fan and Zhang (2003) restricted the alternative models to the class of nonparametric univariate pure diffusion models (1.3) and tested the drift and diffusion functions separately.”
An updated review of Goodness-of-Fit tests for regression models (2013, methodology): “GLRT methodology has been also adapted to diffusion process by Fan and Zhang (2003) and Fan et al. (2003).”
Tilted Nonparametric Estimation of Volatility Functions With Empirical Applications (2010, unknown): “For the pure diffusion models (where σ 2z = 0), the asymptotic theories for these two methods have been studied by Moloche (2001), Fan and Zhang (2003), and Xu (2010).”