02030101 TMBA TMBA #tm_1th_2 > li:nth-child(3) > ul > li.toy_0 > a 02030101 TMBA TMBA #mprovide > div > div > div.box.box1 > ul > li:nth-child(1) > a 02030201 IMBA IMBA #tm_1th_2 > li:nth-child(3) > ul > li.toy_1 > a 02030201 IMBA IMBA #mprovide > div > div > div.box.box1 > ul > li:nth-child(2) > a 02030301 EMBA EMBA #tm_1th_2 > li:nth-child(3) > ul > li.toy_2 > a 02030301 EMBA EMBA #mprovide > div > div > div.box.box1 > ul > li:nth-child(4) > a 02030401 PMBA PMBA #tm_1th_2 > li:nth-child(3) > ul > li.last.toy_3 > a 02030401 PMBA PMBA #mprovide > div > div > div.box.box1 > ul > li:nth-child(3) > a 02040101 FMBA FMBA #tm_1th_2 > li:nth-child(4) > ul > li.toy_0 > a 02040101 FMBA FMBA #mprovide > div > div > div.box.box3 > ul > li:nth-child(1) > a 02040201 MFE MFE #tm_1th_2 > li:nth-child(4) > ul > li.toy_1 > a 02040201 MFE MFE #mprovide > div > div > div.box.box3 > ul > li:nth-child(3) > a 02040401 IMMBA IMMBA #tm_1th_2 > li:nth-child(4) > ul > li.toy_2 > a 02040401 IMMBA IMMBA #mprovide > div > div > div.box.box3 > ul > li:nth-child(2) > a 02040501 IMMS IMMS #tm_1th_2 > li:nth-child(4) > ul > li.toy_3 > a 02040501 IMMS IMMS #mprovide > div > div > div.box.box3 > ul > li:nth-child(4) > a 02040601 SEMBA SEMBA #tm_1th_2 > li:nth-child(4) > ul > li.toy_4 > a 02040601 SEMBA SEMBA #mprovide > div > div > div.box.box3 > ul > li:nth-child(6) > a 02040701 GP GP #tm_1th_2 > li:nth-child(4) > ul > li.last.toy_5 > a 02040701 GP GP #mprovide > div > div > div.box.box3 > ul > li:nth-child(7) > a 02040701 admission admission #txt > div.sub0303.mt_20 > div.btn_wrap > a 02040701 GP GP #mprovide > div > div > div.box.box3 > ul > li:nth-child(7) > a
본문 바로가기 사이트 메뉴 바로가기 주메뉴 바로가기

Volatility analysis with realized GARCH-Ito models

JOURNAL OF ECONOMETRICS2021-05

Song, Xinyu | Kim, Donggyu | Yuan, Huiling | Cui, Xiangyu | Lu, Zhiping | Zhou, Yong | Wang, Yazhen

This paper introduces a unified approach for modeling high-frequency financial data that can accommodate both the continuous-time jump?diffusion and discrete-time realized GARCH model by embedding the discrete realized GARCH structure in the continuous instantaneous volatility process. The key feature of the proposed model is that the corresponding conditional daily integrated volatility adopts an autoregressive structure, where both integrated volatility and jump variation serve as innovations. We name it as the realized GARCH-Ito model. Given the autoregressive structure in the conditional daily integrated volatility, we propose a quasi-likelihood function for parameter estimation and establish its asymptotic properties. To improve the parameter estimation, we propose a joint quasi-likelihood function that is built on the marriage of daily integrated volatility estimated by high-frequency data and nonparametric volatility estimator obtained from option data. We conduct a simulation study to check the finite sample performance of the proposed methodologies and an empirical study with the S&P500 stock index and option data.

Publisher
ELSEVIER SCIENCE SA
Issue Date
2021-05
Article Type
Article; Proceedings Paper
Citation
JOURNAL OF ECONOMETRICS, Vol.222, No.1, pp.393 - 410
ISSN
0304-4076
DOI
10.1016/j.jeconom.2020.07.007
만족도조사

이 페이지에서 제공하는 정보에 대하여 만족하십니까?

콘텐츠담당자 : 주선희 연락처 : 02-958-3602

교수 & 연구

관심자등록

KCB ISSUE