This paper introduces a unified factor overnight GARCH-It\^o model for large volatility matrix estimation and prediction. To account for whole-day market dynamics, the proposed model has two different instantaneous factor volatility processes for the open-to-close and close-to-open periods, while each embeds the discrete-time multivariate GARCH model structure. To estimate latent factor volatility, we assume the low rank plus sparse structure and employ nonparametric estimation procedures. Then, based on the connection between the discrete-time model structure and the continuous-time diffusion process, we propose a weighted least squares estimation procedure with the non-parametric factor volatility estimator and establish its asymptotic th...
It is increasingly important in financial economics to estimate volatilities of asset returns. Howev...
We introduce a multivariate stochastic volatility model that imposes no restrictions on the structur...
This dissertation contains four essays that all share a common purpose: developing new methodologies...
This paper introduces a unified factor overnight GARCH-It\^o model for large volatility matrix estim...
Correlation, volatility, and covariance are three important metrics of financial risk. They are key ...
Estimation of the parameters of Garch models for financial data is typically based on daily close-to...
A new approach is proposed to estimate a large class of multivariate volatility models. The method ...
We introduce and evaluate mixed-frequency multivariate GARCH models for forecasting low-frequency (w...
In this paper we decompose the realized volatility of the GARCH-RV model into continuous sample path...
We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility tha...
This paper decomposes volatility proxies according to upward and downward price movements in high-fr...
Volatilities, in high-dimensional panels of economic time series with a dynamic factor structure on ...
In large panels of financial time series with dynamic factor structure on the levels or returns, the...
Over the past decades, the worldwide financial markets have been continually evolving. Along with th...
We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility tha...
It is increasingly important in financial economics to estimate volatilities of asset returns. Howev...
We introduce a multivariate stochastic volatility model that imposes no restrictions on the structur...
This dissertation contains four essays that all share a common purpose: developing new methodologies...
This paper introduces a unified factor overnight GARCH-It\^o model for large volatility matrix estim...
Correlation, volatility, and covariance are three important metrics of financial risk. They are key ...
Estimation of the parameters of Garch models for financial data is typically based on daily close-to...
A new approach is proposed to estimate a large class of multivariate volatility models. The method ...
We introduce and evaluate mixed-frequency multivariate GARCH models for forecasting low-frequency (w...
In this paper we decompose the realized volatility of the GARCH-RV model into continuous sample path...
We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility tha...
This paper decomposes volatility proxies according to upward and downward price movements in high-fr...
Volatilities, in high-dimensional panels of economic time series with a dynamic factor structure on ...
In large panels of financial time series with dynamic factor structure on the levels or returns, the...
Over the past decades, the worldwide financial markets have been continually evolving. Along with th...
We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility tha...
It is increasingly important in financial economics to estimate volatilities of asset returns. Howev...
We introduce a multivariate stochastic volatility model that imposes no restrictions on the structur...
This dissertation contains four essays that all share a common purpose: developing new methodologies...