Robust maximum entropy test for GARCH models based on a minimum density power divergence estimator
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DOI: 10.1016/j.econlet.2017.11.003
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References listed on IDEAS
- Kim, Byungsoo & Lee, Sangyeol, 2013. "Robust estimation for the covariance matrix of multivariate time series based on normal mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 125-140.
- Sangyeol Lee & Junmo Song, 2009. "Minimum density power divergence estimator for GARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 316-341, August.
- Jushan Bai, 2003. "Testing Parametric Conditional Distributions of Dynamic Models," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 531-549, August.
- Winfried Stute & Wenceslao Manteiga & Manuel Quindimil, 1993. "Bootstrap based goodness-of-fit-tests," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 40(1), pages 243-256, December.
- Lee, Sangyeol & Vonta, Ilia & Karagrigoriou, Alex, 2011. "A maximum entropy type test of fit," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2635-2643, September.
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More about this item
Keywords
Entropy-based goodness-of-fit test; Normality test; GARCH models; Minimum density power divergence estimator; Parametric bootstrap method;All these keywords.
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Statistics
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