Biography
학력
- Ph.D. in Statistics, University of Wisconsin-Madison, USA
주요경력
- 09/2021-present Associate Professor, College of Business, KAIST
03/2020-present Ewon Assistant Professor, KAIST
08/2016-08/2017 Postdoctoral Fellow, Department of Operations Research & Financial Engineering, Princeton University
Publications & Research
주요논문 (특허등)
- Manuscripts
Kim, D., Oh, M., and Wang, Y. (2021). Conditional Quantile Analysis for Realized GARCH Models. To be appeared in Journal of Time Series Analysis.
Chun, D. and Kim, D. (2021). State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data. To be appeared in Journal of Time Series Analysis.
Kim, D. and Shin, M. (2021). High-Dimensional High-Frequency Regression. Submitted.
Kim, D., Oh, M., Song, X., and Wang, Y. (2021). Multivariate Overnight GARCH-Ito Model with Applications in Large Volatility Matrix Estimation and Prediction. Submitted.
Oh, M. and Kim, D. (2021). Effect of the U.S.?China Trade War on Stock Markets: A Financial Contagion Perspective. Submitted.
Shin, M., Kim, D., Wang, Y., and Fan, J. (2021). Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data. Submitted.
Kim, D. and Shin, M. (2021). Volatility Models for Stylized Facts of High-Frequency Financial Data. Submitted.
Han, S., Kim, D., and Kim, H. (2021). Adaptive Thresholding for Iterative Matrix Completion with Heterogeneous Missing Probability: H-AdaptiveImpute. Submitted.
Song, M., Kim, D., and Wang, Y. (2021). Dynamic Realized Beta Models. Submitted.
Kim, D. (2021). Exponential GARCH-Ito Volatility Models. Submitted.
Shin, M., Kim, D., and Fan, J. (2020). Adaptive Robust Large Volatility Matrix Estimation Based on High-Frequency Financial Data. Submitted.
Kim, D. and Wang, Y. (2021). Overnight GARCH-Ito Volatility Models. Submitted.
Kim, D. and Yu, S. (2020). Incorporating Financial Big Data in Small Portfolio Risk Analysis: Market Risk Management Approach. Submitted.
Kim, D., Song, X., and Wang, Y. (2020). Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency. Submitted.
Published Papers
2021
Song, X., Kim, D., Yuan, H., and Wang, Y., Zhou, Y., and Cui, X. (2021). Volatility Analysis with Realized GARCH-Ito Models. Journal of Econometrics, 222, 393-410.
Cai, T, Kim, D., Song, X., and Wang, Y. (2021). Optimal sparse eigenspace and low-rank density matrix estimation for quantum systems. Journal of Statistical Planning and Inference, 213, 50-71.
2019
Cho. J., Kim, D., and Rohe, K. (2019). Intelligent Initialization and Adaptive Thresholding for Iterative Matrix Completion; Some Statistical and Algorithmic Theory for Adaptive-Impute. Journal of Computational and Graphical Statistics, 28, 323-333.
Fan, J. and Kim, D. (2019). Structured Volatility Matrix Estimation for Non-synchronized High-frequency Financial Data. Journal of Econometrics, 209, 61-78.
Kim, D. and Fan, J. (2019). Factor GARCH-Ito Models for High-frequency Data with Application to Large Volatility Matrix Prediction. Journal of Econometrics, 208, 395-417.
2018
Kim, D., Kong, X., Li, C., and Wang, Y. (2018). Adaptive Thresholding for Large Volatility Matrix Estimation Based on High-Frequency Financial Data. Journal of Econometrics, 203, 69-79.
Kim, D., Liu, Y. and Wang, Y. (2018). Large Volatility Matrix Estimation with Factor-Based Diffusion Model for High-Frequency Financial data. Bernoulli, 24, 3657-3682.
Fan, J. and Kim, D. (2018). Robust high-dimensional volatility matrix estimation for high-frequency factor model. Journal of the American Statistical Association, 113, 1268-1283.
2017
Kim, D., and Wang, Y. (2017). Hypothesis Tests of Large Density Matrices of Quantum Systems Based on Pauli Measurements. Physica A, 469, 31-51.
Cho, J., Kim, D., and Rohe, K. (2017). Asymptotic Theory for Estimating the Singular Vectors and Values of a Partially-observed Low Rank Matrix with Noise. Statistica Sinica, 27, 1921-1948. pdf.
2016
Cai, T., Kim, D., Yuan, M., Wang, Y. and Zhou, H. (2016). Optimal Large-Scale Quantum State Tomography with Pauli Measurements. The Annals of Statistics, 44, 682-712.
Kim, D. and Wang, Y. (2016). Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data. Journal of Econometrics,194, 220-230.
Kim, D. and Wang, Y. (2016). Sparse PCA Based on High-Dimensional It\^o processes with Measurement Errors. Journal of Multivariate Analysis, 152, 172-189. Supplement Document.
Kim, D., Wang, Y. and Zou, J. (2016). Asymptotic Theory for Large Volatility Matrix Estimation Based on High-Frequency Financial Data. Stochastic Processes and Their Applications, 126, 3527?3577.
Kim, D. (2016). Statistical inference for unified GARCH-Ito models with high-frequency financial data. Journal of Time Series Analysis, 37, 513-532.
Zhang, X., Kim, D., and Wang, Y. (2016). Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets. Econometrics, 4(3), 34.
2014
Kim, D. and Zhang, C. (2014). Adaptive Linear Step-up Multiple Testing Procedure with the Bias-Reduced Estimator. Statistics and Probability Letters, 87, 31-39.
연구분야
- Financial econometrics
Risk Management
Ultra-high dimensional statistical inference
Machine Learning
Recommendation System
Quantum State Tomography
