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20182021
most citedUnified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency

3 citations · 4 across the 5 of their papers we have counts for

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stat.ME2020★ 3 cited

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…

stat.ME2019

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…