Behaviour of skewness, kurtosis and normality tests in long memory data
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Bibliographic InfoArticle provided by Springer in its journal Statistical Methods and Applications.
Volume (Year): 19 (2010)
Issue (Month): 2 (June)
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Web page: http://link.springer.de/link/service/journals/10260/index.htm
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- Lobato, Ignacio N. & Velasco, Carlos, 2004. "A Simple Test Of Normality For Time Series," Econometric Theory, Cambridge University Press, vol. 20(04), pages 671-689, August.
- Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 5(1), pages 31-67.
- Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Society for Computational Economics, vol. 31(3), pages 243-254, April.
- Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996.
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- Tom Doan, . "RATS programs to replicate Baillie, Bollerslev, Mikkelson FIGARCH results," Statistical Software Components RTZ00009, Boston College Department of Economics.
- Mohamed Boutahar & Velayoudom Marimoutou & Leila Nouira, 2007. "Estimation Methods of the Long Memory Parameter: Monte Carlo Analysis and Application," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(3), pages 261-301.
- Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
- Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
- Hosking, Jonathan R. M., 1996. "Asymptotic distributions of the sample mean, autocovariances, and autocorrelations of long-memory time series," Journal of Econometrics, Elsevier, vol. 73(1), pages 261-284, July.
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