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Tests for departure from normality in the case of linear stochastic processes

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Cited by:

  1. Tomasz Woźniak, 2018. "Granger-causal analysis of GARCH models: A Bayesian approach," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 325-346, April.
  2. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
  3. Lakshman A. Alles & John L. Kling, 1994. "Regularities In The Variation Of Skewness In Asset Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 17(3), pages 427-438, September.
  4. Weiss, Andrew A., 1986. "Asymptotic Theory for ARCH Models: Estimation and Testing," Econometric Theory, Cambridge University Press, vol. 2(1), pages 107-131, April.
  5. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
  6. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
  7. Ewa Ratuszny, 2015. "Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 129-156.
  8. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, September.
  9. Gilles R. Ducharme & Pierre Lafaye de Micheaux, 2004. "Goodness‐of‐fit tests of normality for the innovations in ARMA models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(3), pages 373-395, May.
  10. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, September.
  11. Francesco Lisi, 2007. "Testing asymmetry in financial time series," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 687-696.
  12. C. Granger, 1976. "Tendency towards normality of linear combinations of random variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 23(1), pages 237-248, December.
  13. John McDonald, 1979. "A time series approach to forecasting Australian total live-births," Demography, Springer;Population Association of America (PAA), vol. 16(4), pages 575-601, November.
  14. Craig, Lee A. & Holt, Matthew T., 2008. "Mechanical refrigeration, seasonality, and the hog-corn cycle in the United States: 1870-1940," Explorations in Economic History, Elsevier, vol. 45(1), pages 30-50, January.
  15. O. Anderson, 1977. "An appraisal of the Box-Jenkins approach to univariate time series analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 24(1), pages 187-194, December.
  16. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
  17. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
  18. Balagtas, Joseph Valdes & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  19. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
  20. Nektarios Aslanidis, 2002. "Smooth Transition Regression Models in UK Stock Returns," Working Papers 0201, University of Crete, Department of Economics.
  21. Tincho Almuzara & Dante Amengual & Enrique Sentana, 2017. "Normality Tests for Latent Variables," Working Papers wp2018_1708, CEMFI.
  22. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
  23. Heuts, R.M.J., 1982. "The use of non-linear transformations in ARIMA-models when the data are non-Gaussian distributed," Other publications TiSEM f4ccef9b-24f6-4179-883c-9, Tilburg University, School of Economics and Management.
  24. Claudio Lupi & Patrizia Ordine, 2001. "Testing for asymmetry in economic time series using bootstrap methods," Economics Bulletin, AccessEcon, vol. 3(8), pages 1-12.
  25. David E. A. Giles, 1997. "Testing for Asymmetry in the Measured and Underground Business Cycles in New Zealand," The Economic Record, The Economic Society of Australia, vol. 73(222), pages 225-232, September.
  26. Martín Almuzara & Dante Amengual & Enrique Sentana, 2019. "Normality tests for latent variables," Quantitative Economics, Econometric Society, vol. 10(3), pages 981-1017, July.
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