Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment

Author:

Dai Zhifeng1ORCID,Li Tingyu1,Yang Mi2

Affiliation:

1. College of Mathematics and Statistics, Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering Changsha University of Science and Technology Changsha Hunan China

2. School of Economics and Management Changsha University of Science and Technology Changsha Hunan China

Funder

Natural Science Foundation of Hunan Province

National Social Science Fund of China

National Natural Science Foundation of China

Publisher

Wiley

Subject

Management Science and Operations Research,Statistics, Probability and Uncertainty,Strategy and Management,Computer Science Applications,Modeling and Simulation

Reference54 articles.

1. Forecasting Tehran stock exchange volatility; Markov switching GARCH approach;Abounoori E.;Physica A‐Statistical Mechanics and its Applications,2016

2. Value‐at‐risk estimations of energy commodities via long‐memory, asymmetry and fat‐tailed GARCH models;Aloui C.;Energy Policy,2010

3. The distribution of realized stock return volatility;Andersen T. G.;Journal of Financial Economics,2001

4. Flexible HAR model for realized volatility;Audrino F.;Studies in Nonlinear Dynamics & Econometrics,2019

5. Lassoing the HAR model: A model selection perspective on realized volatility dynamics;Audrino F.;Econometric Reviews,2016

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