3 citations · 4 across the 6 of their papers we have counts for
9 papers
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…
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…
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…
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…