TY - JOUR
T1 - Goodness-of-fit test for stochastic volatility models
AU - Lin, Liang Ching
AU - Lee, Sangyeol
AU - Guo, Meihui
N1 - Funding Information:
We are grateful to the referees for their valuable comments. The research of the first and the third author was partly supported by grant number NSC 101-2118-M-110-003 , from Taiwan’s National Science Council . The second author acknowledges that this research was supported in part by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0010936) grant number: 2011-0010936 . This work was also partially supported by the National Center for Theoretical Sciences (South), Tainan , Taiwan.
PY - 2013/4
Y1 - 2013/4
N2 - In this paper, we propose a goodness of fit test for continuous time stochastic volatility models based on discretely sampled observations. The proposed test is constructed by measuring deviations between the empirical and true characteristic functions obtained from the hypothesized stochastic volatility model. In this study, both the test statistics based on the fixed and decreasing sampling schemes are taken into consideration. It is shown that under the null, the proposed tests asymptotically follow a weighted sum of products of centered normal random variables. In order to evaluate the proposed tests, a simulation study is performed, in which a bootstrap method is also considered. Finally, a real data analysis is conducted for illustration.
AB - In this paper, we propose a goodness of fit test for continuous time stochastic volatility models based on discretely sampled observations. The proposed test is constructed by measuring deviations between the empirical and true characteristic functions obtained from the hypothesized stochastic volatility model. In this study, both the test statistics based on the fixed and decreasing sampling schemes are taken into consideration. It is shown that under the null, the proposed tests asymptotically follow a weighted sum of products of centered normal random variables. In order to evaluate the proposed tests, a simulation study is performed, in which a bootstrap method is also considered. Finally, a real data analysis is conducted for illustration.
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U2 - 10.1016/j.jmva.2013.01.006
DO - 10.1016/j.jmva.2013.01.006
M3 - Article
AN - SCOPUS:84873962050
SN - 0047-259X
VL - 116
SP - 473
EP - 498
JO - Journal of Multivariate Analysis
JF - Journal of Multivariate Analysis
ER -