Showing results 20 to 30 of 30
R&D employee training, the stock of technological knowledge, and R&D productivity Kim, Donggyu; Lee, Chang-Yang, R & D MANAGEMENT, v.52, no.5, pp.801 - 819, 2022-11 |
Robust High-Dimensional Volatility Matrix Estimation for High-Frequency Factor Model Fan, Jianqing; Kim, Donggyu, JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, v.113, no.523, pp.1268 - 1283, 2018-11 |
Sparse PCA-based on high-dimensional Ito processes with measurement errors Kim, Donggyu; Wang, Yazhen, JOURNAL OF MULTIVARIATE ANALYSIS, v.152, pp.172 - 189, 2016-12 |
State Heterogeneity Analysis of Financial Volatility using high-frequency Financial Data Chun, Dohyun; Kim, Donggyu, JOURNAL OF TIME SERIES ANALYSIS, v.43, no.1, pp.105 - 124, 2022-01 |
Statistical Inference for Unified Garch-Ito Models with High-Frequency Financial Data Kim, Donggyu, JOURNAL OF TIME SERIES ANALYSIS, v.37, no.4, pp.513 - 532, 2016-07 |
Structured volatility matrix estimation for non-synchronized high-frequency financial data Fan, Jianqing; Kim, Donggyu, JOURNAL OF ECONOMETRICS, v.209, no.1, pp.61 - 78, 2019-03 |
Three essays on intrafirm R&D employees and knowledge production = 기업 내 연구개발 인력과 지식 생산에 대한 세 편의 소론link Kim, Donggyu; 김동규; et al, 한국과학기술원, 2023 |
Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data Kim, Donggyu; Wang, Yazhen, JOURNAL OF ECONOMETRICS, v.194, no.2, pp.220 - 230, 2016-10 |
Unified discrete-time factor stochastic volatility and continuous-time Ito models for combining inference based on low-frequency and high-frequency Kim, Donggyu; Song, Xinyu; Wang, Yazhen, JOURNAL OF MULTIVARIATE ANALYSIS, v.192, 2022-11 |
Volatility analysis with realized GARCH-Ito models Song, Xinyu; Kim, Donggyu; Yuan, Huiling; Cui, Xiangyu; Lu, Zhiping; Zhou, Yong; Wang, Yazhen, JOURNAL OF ECONOMETRICS, v.222, no.1, pp.393 - 410, 2021-05 |
Volatility models for stylized facts of high-frequency financial data Kim, Donggyu; Shin, Minseok, JOURNAL OF TIME SERIES ANALYSIS, v.44, no.3, pp.262 - 279, 2023-05 |
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