TY - JOUR
T1 - The Bickel-Rosenblatt test for continuous time stochastic volatility models
AU - Lin, Liang Ching
AU - Lee, Sangyeol
AU - Guo, Meihui
N1 - Funding Information:
Acknowledgments The first and third authors acknowledge that this work was supported in part by the National Science Council, Taiwan, under Grant NSC 101-2118-M-110-003. This work is partially supported by the National Center for Theoretical Sciences (South), Tainan, Taiwan. The second author acknowledges that this research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology, under Grant 2011-0010936.
PY - 2014/3
Y1 - 2014/3
N2 - In this paper, we consider the Bickel-Rosenblatt test for continuous time stochastic volatility models. The test is constructed based on discretely observed samples by measuring integrated squared deviations between the nonparametric kernel density estimate from the observations and a parametric fit of the density. It is shown that under the null, the proposed test is asymptotically normal. To evaluate the proposed test, a simulation study is performed for illustration.
AB - In this paper, we consider the Bickel-Rosenblatt test for continuous time stochastic volatility models. The test is constructed based on discretely observed samples by measuring integrated squared deviations between the nonparametric kernel density estimate from the observations and a parametric fit of the density. It is shown that under the null, the proposed test is asymptotically normal. To evaluate the proposed test, a simulation study is performed for illustration.
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U2 - 10.1007/s11749-013-0347-1
DO - 10.1007/s11749-013-0347-1
M3 - Article
AN - SCOPUS:84896391452
SN - 1133-0686
VL - 23
SP - 195
EP - 218
JO - Test
JF - Test
IS - 1
ER -