A Note on the Asymptotic Normality of the Kernel Deconvolution Density Estimator with Logarithmic Chi-Square Noise
Econometrics, 2015, vol. 3, issue 3, 1-16
This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain the pointwise asymptotic distribution of the deconvolution volatility density estimator in discrete-time stochastic volatility models.
Keywords: kernel deconvolution estimator; asymptotic normality; volatility density estimation (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:3:y:2015:i:3:p:561-576:d:52948
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