5 papers
HAR-Ito models and high-dimensional HAR modeling for high-frequency data
Huiling Yuan, Kexin Lu, Yifeng Guo +1
It is an important task to model realized volatilities for high-frequency data in finance and economics and, as arguably the most popular model, the heterogeneous autoregressive (H…
High-Frequency-Based Volatility Model with Network Structure
Huiling Yuan, Guodong Li, Junhui Wang
This paper introduces one new multivariate volatility model that can accommodate an appropriately defined network structure based on low-frequency and high-frequency data. The mode…
A new volatility model: GQARCH-Itô model
Huiling Yuan, Yong Zhou, Lu Xu +2
Volatility asymmetry is a hot topic in high-frequency financial market. In this paper, we propose a new econometric model, which could describe volatility asymmetry based on high-f…
Forecasting security's volatility using low-frequency historical data, high-frequency historical data and option-implied volatility
Huiling Yuan, Yong Zhou, Zhiyuan Zhang +1
Low-frequency historical data, high-frequency historical data and option data are three major sources, which can be used to forecast the underlying security's volatility. In this p…
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…