Further development of semiparametric volatility models and their applications to value at risk and expected shortfall / von Xuehai Zhang, M.A. Paderborn, 2019
Content
List of Tables
List of Figures
List of Abbreviations
Introduction
Parametric and Semiparametric Models
Introduction
Overview of the volatility models
The ACD model
The semiparametric GARCH model
The semiparametric ACD model
Final remarks
SemiGARCH models based on Box-Cox transformation
Introduction
The SemiGARCH model with Box-Cox transformation
The semiparametric estimation procedure
Estimation of s(t)
Semiparametric estimation of a given model
The bandwidth estimation algorithm
The power transformation parameter estimation algorithm
A simple stationary test
Applications
Final remarks
VaR and ES under general Semiparametric GARCH models
Introduction
VaR and ES with semiparametric processes
The Backtesting of VaR and ES
The loss function
The empirical study
Final remarks
Modeling high-frequency returns using general SemiGARCH models
Semiparametric MEM with Power Transformation
Introduction
The model
The model estimation and properties
The data-driven algorithms
The empirical examples
Final remarks
Further topics
Introduction
The sampling schemes
The SemiMEM models to the high-frequency data
The empirical analysis
The data
The analysis of the intraday trading volume
The analysis of the intraday trading duration
The analysis of the intraday realized volatility
Final remarks
Concluding remarks
References
Appendices