Sparse vector heterogeneous autoregressive modeling for realized volatility
DOI10.1007/s42952-020-00090-5zbMath1485.62143OpenAlexW3092474152MaRDI QIDQ2132003
Publication date: 27 April 2022
Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s42952-020-00090-5
realized volatilityheterogeneous autoregressive (HAR) modelsparse vector heterogeneous autoregressive modelstock market linkage
Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Economic time series analysis (91B84)
Cites Work
- Unnamed Item
- Unnamed Item
- Regularized estimation in sparse high-dimensional time series models
- The Adaptive Lasso and Its Oracle Properties
- Sparse seasonal and periodic vector autoregressive modeling
- Periodic dynamic factor models: estimation approaches and applications
- Detecting structural breaks in realized volatility
- On distinguishing multiple changes in mean and long-range dependence using local Whittle estimation
- Extended Bayesian information criteria for model selection with large model spaces
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
- Tests for Volatility Shifts in Garch Against Long‐Range Dependence
- Modeling and Forecasting Realized Volatility
This page was built for publication: Sparse vector heterogeneous autoregressive modeling for realized volatility