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Citations for "Tests for Skewness, Kurtosis, and Normality for Time Series Data"

by Jushan Bai & Serena Ng

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  1. Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona Graduate School of Economics.
  2. Lee, Sangyeol & Ng, Chi Tim, 2011. "Normality test for multivariate conditional heteroskedastic dynamic regression models," Economics Letters, Elsevier, vol. 111(1), pages 75-77, April.
  3. Araújo, Tanya & Dias, João & Eleutério, Samuel & Louçã, Francisco, 2013. "A measure of multivariate kurtosis for the identification of the dynamics of a N-dimensional market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3708-3714.
  4. Francisco Penaranda, 2007. "Portfolio choice beyond the traditional approach," LSE Research Online Documents on Economics 24481, London School of Economics and Political Science, LSE Library.
  5. Chen, Yi-Ting & Ho, Keng-Yu & Tzeng, Larry Y., 2014. "Riskiness-minimizing spot-futures hedge ratio," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 154-164.
  6. Jordà, Òscar & Knüppel, Malte & Marcellino, Massimiliano, 2013. "Empirical simultaneous prediction regions for path-forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 456-468.
  7. Tanya Ara\'ujo & Jo\~ao Dias & Samuel Eleut\'erio & Francisco Lou\c{c}\~a, 2012. "How Fama Went Wrong: Measures of Multivariate Kurtosis for the Identification of the Dynamics of a N-Dimensional Market," Papers 1207.1202, arXiv.org.
  8. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
  9. Enrique Sentana, 2008. "The Econometrics Of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.
  10. Bontemps, Christian, 2013. "Moment-Based Tests for Discrete Distributions," IDEI Working Papers 772, Institut d'Économie Industrielle (IDEI), Toulouse.
  11. Christoph Gortz & John D. Tsoukalas, 2013. "Learning, Capital Embodied Technology and Aggregate Fluctuations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(4), pages 708-723, October.
  12. McKay, Alisdair & Reis, Ricardo, 2008. "The brevity and violence of contractions and expansions," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 738-751, May.
  13. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO.
  14. Marian Vavra, 2013. "Testing for marginal asymmetry of weakly dependent processes," Working and Discussion Papers WP 1/2013, Research Department, National Bank of Slovakia.
  15. Makram El-Shagi & Sebastian Giesen, 2010. "Testing for Structural Breaks at Unknown Time: A Steeplechase," IWH Discussion Papers 19, Halle Institute for Economic Research.
  16. Galvao, Antonio F. & Montes-Rojas, Gabriel & Sosa-Escudero, Walter & Wang, Liang, 2013. "Tests for skewness and kurtosis in the one-way error component model," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 35-52.
  17. Ippei Fujiwara & Lena Mareen Körber & Daisuke Nagakura, 2011. "How much asymmetry is there in bond returns and exchange rates?," Globalization and Monetary Policy Institute Working Paper 93, Federal Reserve Bank of Dallas.
  18. Abbritti, Mirko & Fahr, Stephan, 2013. "Downward wage rigidity and business cycle asymmetries," Journal of Monetary Economics, Elsevier, vol. 60(7), pages 871-886.
  19. Thanasis Stengos & Ximing Wu†, 2007. "We derive general distribution tests based on the method of Maximum Entropy density," Working Paper Series 24-07, The Rimini Centre for Economic Analysis, revised Jul 2007.
  20. Esfandiar Maasoumi & Jeffrey Racine, 2009. "A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 246-261.
  21. Òscar Jordà & Malte Knüppel & Massimiliano Marcellino, 2010. "Empirical Simultaneous Confidence Regions for Path-Forecasts," Economics Working Papers ECO2010/18, European University Institute.
  22. Karanasos, M. & Kartsaklas, A., 2009. "Dual long-memory, structural breaks and the link between turnover and the range-based volatility," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 838-851, December.
  23. El-Shagi, M. & Knedlik, T. & von Schweinitz, G., 2013. "Predicting financial crises: The (statistical) significance of the signals approach," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 76-103.
  24. Syed Abul, Basher & Salem, Nechi & Hui, Zhu, 2014. "Dependence patterns across Gulf Arab stock markets: a copula approach," MPRA Paper 56566, University Library of Munich, Germany.
  25. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods and Applications, Springer, vol. 20(4), pages 487-506, November.
  26. Giet, Ludovic & Lubrano, Michel, 2008. "A minimum Hellinger distance estimator for stochastic differential equations: An application to statistical inference for continuous time interest rate models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2945-2965, February.
  27. Tanya Araujo & João Dias & Samuel Eleutério & Francisco Louçã, 2012. "How Fama Went Wrong: Measures of Multivariate Kurtosis for the Identification of the Dynamics of a N-Dimensional Market," Working Papers Department of Economics 2012/21, ISEG - School of Economics and Management, Department of Economics, University of Lisbon.
  28. Homm, Ulrich & Pigorsch, Christian, 2012. "Beyond the Sharpe ratio: An application of the Aumann–Serrano index to performance measurement," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2274-2284.
  29. Panagiotelis, Anastasios & Smith, Michael, 2010. "Bayesian skew selection for multivariate models," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1824-1839, July.
  30. Richard Gerlach & Zudi Lu & Hai Huang, 2013. "Exponentially Smoothing the Skewed Laplace Distribution for Value‐at‐Risk Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 534-550, 09.