Nonparametric specification tests for stochastic volatility models based on volatility density
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DOI: 10.1016/j.jeconom.2015.02.045
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Citations
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- Christensen, Kim & Thyrsgaard, Martin & Veliyev, Bezirgen, 2019.
"The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing,"
Journal of Econometrics, Elsevier, vol. 212(2), pages 556-583.
- Kim Christensen & Martin Thyrsgaard & Bezirgen Veliyev, 2018. "The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing," CREATES Research Papers 2018-19, Department of Economics and Business Economics, Aarhus University.
- Yinfen Tang & Tao Su & Zhiyuan Zhang, 2022. "Distribution-free specification test for volatility function based on high-frequency data with microstructure noise," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(8), pages 977-1022, November.
- Zu, Yang & Boswijk, H. Peter, 2017. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 53-75.
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More about this item
Keywords
Nonparametric tests; Kernel deconvolution estimator; Stochastic volatility model;All these keywords.
JEL classification:
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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