@article{5443f6c0efd14a6ab87c71520ec6fd13,
title = "Goodness-of-fit test for the SVM based on noisy observations",
abstract = "In financial high frequency data analysis, the efficient price of an asset is commonly assumed to follow a continuous-time stochastic volatility model, contaminated with a microstructure noise. In this study, we consider a goodness-of-fit test problem for the efficient price models based on discretely observed samples and employ a goodness-of-fit test based on the empirical characteristic function. We show that the proposed test is asymptotically a weighted sum of products of centered normal random variables. To evaluate the proposed test, we conducted a simulation study using a bootstrap method. A data analysis is provided for illustration.",
author = "Lin, {Liang Ching} and Sangyeol Lee and Meihui Guo",
note = "Funding Information: The first and third authors acknowledge that this work was supported in part by the National Science Council, Taiwan, under grant NSC 100-2118-M-110-003 and NSC 103-2118-M-110-003. The first author acknowledges that this work was supported by Ministry of Science and Technology, Taiwan, under grant MOST 104-2118-M-006-001. The second author acknowledges that this work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No. 2015R1A2A2A010003894). This work is partially supported by the National Center for Theoretical Sciences (South), Tainan, Taiwan",
year = "2016",
month = jul,
doi = "10.5705/ss.202015.0215",
language = "English",
volume = "26",
pages = "1305--1329",
journal = "Statistica Sinica",
issn = "1017-0405",
publisher = "Institute of Statistical Science",
number = "3",
}