5 papers
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…
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,…
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…
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…