28 citations · 77 across the 25 of their papers we have counts for
25 papers
Robust Reinforcement Learning under Diffusion Models for Data with Jumps
Chenyang Jiang, Donggyu Kim, Alejandra Quintos +1
Reinforcement Learning (RL) has proven effective in solving complex decision-making tasks across various domains, but challenges remain in continuous-time settings, particularly wh…
Matrix-based Prediction Approach for Intraday Instantaneous Volatility Vector
Sung Hoon Choi, Donggyu Kim
In this paper, we introduce a novel method for predicting intraday instantaneous volatility based on Ito semimartingale models using high-frequency financial data. Several studies…
Nonconvex High-Dimensional Time-Varying Coefficient Estimation for Noisy High-Frequency Observations with a Factor Structure
Minseok Shin, Donggyu Kim
In this paper, we propose a novel high-dimensional time-varying coefficient estimator for noisy high-frequency observations with a factor structure. In high-frequency finance, we o…
Dynamic Realized Minimum Variance Portfolio Models
Donggyu Kim, Minseog Oh
This paper introduces a dynamic minimum variance portfolio (MVP) model using nonlinear volatility dynamic models, based on high-frequency financial data. Specifically, we impose an…
Large Global Volatility Matrix Analysis Based on Observation Structural Information
Sung Hoon Choi, Donggyu Kim
In this paper, we develop a novel large volatility matrix estimation procedure for analyzing global financial markets. Practitioners often use lower-frequency data, such as weekly…
Robust High-Dimensional Time-Varying Coefficient Estimation
Minseok Shin, Donggyu Kim
In this paper, we develop a novel high-dimensional coefficient estimation procedure based on high-frequency data. Unlike usual high-dimensional regression procedures such as LASSO,…
Robust Realized Integrated Beta Estimator with Application to Dynamic Analysis of Integrated Beta
Minseog Oh, Donggyu Kim, Yazhen Wang
In this paper, we develop a robust non-parametric realized integrated beta estimator using high-frequency financial data contaminated by microstructure noises, which is robust to t…
Large Volatility Matrix Analysis Using Global and National Factor Models
Sung Hoon Choi, Donggyu Kim
Several large volatility matrix inference procedures have been developed, based on the latent factor model. They often assumed that there are a few of common factors, which can acc…
Volatility Models for Stylized Facts of High-Frequency Financial Data
Donggyu Kim, Minseok Shin
This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial data such as volatility clustering, intra-day U-shape, and lev…
Dynamic Realized Beta Models Using Robust Realized Integrated Beta Estimator
Donggyu Kim, Minseog Oh, Minjeong Song +1
This paper introduces a unified parametric modeling approach for time-varying market betas that can accommodate continuous-time diffusion and discrete-time series models based on a…
Factor Overnight GARCH-Itô Models
Donggyu Kim, Minseog Oh, Xinyu Song +1
This paper introduces a unified factor overnight GARCH-Itô model for large volatility matrix estimation and prediction. To account for whole-day market dynamics, the proposed model…
Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective
Minseog Oh, Donggyu Kim
In this paper, we investigate the effect of the U.S.--China trade war on stock markets from a financial contagion perspective, based on high-frequency financial data. Specifically,…
Exponential GARCH-Ito Volatility Models
Donggyu Kim
This paper introduces a novel Ito diffusion process to model high-frequency financial data, which can accommodate low-frequency volatility dynamics by embedding the discrete-time n…
Factor and Idiosyncratic VAR Volatility Matrix Models for Heavy-Tailed High-Frequency Financial Observations
Minseok Shin, Donggyu Kim, Yazhen Wang +1
This paper introduces a novel process for both factor and idiosyncratic volatility matrices whose eigenvalues follow the vector auto-regressive (VAR) model. We call it the factor a…
Conditional Quantile Analysis for Realized GARCH Models
Donggyu Kim, Minseog Oh, Yazhen Wang
This paper introduces a novel quantile approach to harness the high-frequency information and improve the daily conditional quantile estimation. Specifically, we model the conditio…
State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data
Dohyun Chun, Donggyu Kim
Recently, to account for low-frequency market dynamics, several volatility models, employing high-frequency financial data, have been developed. However, in financial markets, we o…
Overnight GARCH-Itô Volatility Models
Donggyu Kim, Minseok Shin, Yazhen Wang
Various parametric volatility models for financial data have been developed to incorporate high-frequency realized volatilities and better capture market dynamics. However, because…
Next Generation Models for Portfolio Risk Management: An Approach Using Financial Big Data
Kwangmin Jung, Donggyu Kim, Seunghyeon Yu
This paper proposes a dynamic process of portfolio risk measurement to address potential information loss. The proposed model takes advantage of financial big data to incorporate o…
Adaptive Robust Large Volatility Matrix Estimation Based on High-Frequency Financial Data
Minseok Shin, Donggyu Kim, Jianqing Fan
Several novel statistical methods have been developed to estimate large integrated volatility matrices based on high-frequency financial data. To investigate their asymptotic behav…
Statistical Analysis of Quantum Annealing
Xinyu Song, Yazhen Wang, Shang Wu +1
Quantum computers use quantum resources to carry out computational tasks and may outperform classical computers in solving certain computational problems. Special-purpose quantum c…
Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency
Donggyu Kim, Xinyu Song, Yazhen Wang
This paper introduces unified models for high-dimensional factor-based Ito process, which can accommodate both continuous-time Ito diffusion and discrete-time stochastic volatility…
Volatility Analysis with Realized GARCH-Ito Models
Xinyu Song, Donggyu Kim, Huiling Yuan +4
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 mo…
Intelligent Initialization and Adaptive Thresholding for Iterative Matrix Completion; Some Statistical and Algorithmic Theory for Adaptive-Impute
Juhee Cho, Donggyu Kim, Karl Rohe
Over the past decade, various matrix completion algorithms have been developed. Thresholded singular value decomposition (SVD) is a popular technique in implementing many of them.…
Optimal large-scale quantum state tomography with Pauli measurements
Tony Cai, Donggyu Kim, Yazhen Wang +2
Quantum state tomography aims to determine the state of a quantum system as represented by a density matrix. It is a fundamental task in modern scientific studies involving quantum…