Fractionally integrated time varying GARCH model
From MaRDI portal
Publication:257572
DOI10.1007/S10260-010-0131-2zbMath1332.62309OpenAlexW1990580781MaRDI QIDQ257572
Adnen Ben Nasr, Mohamed Boutahar, Abdelwahed Trabelsi
Publication date: 17 March 2016
Published in: Statistical Methods and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10260-010-0131-2
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Parametric hypothesis testing (62F03) Economic time series analysis (91B84)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regression
- Seasonal nonlinear long memory model for the US inflation rates
- Fractionally integrated generalized autoregressive conditional heteroskedasticity
- Testing the adequacy of smooth transition autoregressive models
- Testing the constancy of regression parameters against continuous structural change
- Autoregressive conditional heteroskedasticity and changes in regime
- The detection and estimation of long memory in stochastic volatility
- GARCH processes: structure and estimation
- Generalized autoregressive conditional heteroscedasticity
- A nonlinear long memory model, with an application to US unemployment.
- Evaluating GARCH models.
- Modeling and pricing long memory in stock market volatility
- Modelling long memory and structural breaks in conditional variances: an adaptive FIGARCH approach
- Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices
- Conditional Heteroskedasticity in Asset Returns: A New Approach
- A NOTE ON INEQUALITY CONSTRAINTS IN THE GARCH MODEL
- Modelling the persistence of conditional variances
- Testing linearity against smooth transition autoregressive models
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
- Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
- Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
- On the Autocorrelation Properties of Long‐Memory GARCH Processes
- Consistency and Asymptotic Normality of the Quasi-Maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models
- Common Persistence in Conditional Variances
- ASYMPTOTIC INFERENCE FOR NONSTATIONARY GARCH
- Maximum Likelihood Estimation of Misspecified Models
This page was built for publication: Fractionally integrated time varying GARCH model
