FIRST-ORDER ASYMPTOTIC THEORY FOR PARAMETRIC MISSPECIFICATION TESTS OF GARCH MODELS
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Publication:3632429
DOI10.1017/S0266466608090129zbMath1279.62184WikidataQ57947626 ScholiaQ57947626MaRDI QIDQ3632429
Andreea G. Halunga, Chris D. Orme
Publication date: 11 June 2009
Published in: Econometric Theory (Search for Journal in Brave)
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15)
Related Items (7)
A general approach to conditional moment specification testing with projections ⋮ Testing for misspecification in the short-run component of GARCH-type models ⋮ Goodness-of-fit tests for parametric specifications of conditionally heteroscedastic models ⋮ The long memory HEAVY process: modeling and forecasting financial volatility ⋮ STATISTICAL INFERENCE FOR MEASUREMENT EQUATION SELECTION IN THE LOG-REALGARCH MODEL ⋮ Residual-based rank specification tests for AR-GARCH type models ⋮ Robust parametric tests of constant conditional correlation in a MGARCH model
Cites Work
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- On the application of robust, regression-based diagnostics to models of conditional means and conditional variances
- Quasi-maximum likelihood estimation in GARCH processes when some coefficients are equal to zero
- Conditional Heteroskedasticity in Asset Returns: A New Approach
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- ON THE SQUARED RESIDUAL AUTOCORRELATIONS IN NON-LINEAR TIME SERIES WITH CONDITIONAL HETEROSKEDASTICITY
- On the Behavior of Conditional Moment Tests in the Presence of Unconsidered Local Alternatives
- A consistent test for conditional symmetry in time series models
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