On the threshold innovation in quasi-likelihood for conditionally heteroscedastic time series
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Publication:5082676
DOI10.1080/03610918.2019.1593453zbMath1497.62249OpenAlexW2936836716MaRDI QIDQ5082676
Publication date: 21 June 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2019.1593453
Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
Cites Work
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- Asymmetric GARCH processes featuring both threshold effect and bilinear structure
- Quasilikelihood and quasi-maximum likelihood for GARCH-type processes: estimating function approach
- Godambe estimating functions and asymptotic optimal inference
- Quasi-likelihood and its application. A general approach to optimal parameter estimation
- Estimation in conditionally heteroscedatic time series models.
- Directional dependence via Gaussian copula beta regression model with asymmetric GARCH marginals
- Handbook of Financial Time Series
- Practical Issues in the Analysis of Univariate GARCH Models
- The foundations of finite sample estimation in stochastic processes
- On Bayesian Modeling of Fat Tails and Skewness
- Optimal Predictions of Powers of Conditionally Heteroscedastic Processes
- Martingale Estimating Functions for Stochastic Processes: A Review Toward a Unifying Tool
- A profile Godambe information of power transformations for ARCH time series
- Estimating functions for nonlinear time series models
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