An Alternative Conditional Asymmetry Specification for Stock Returns
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Other versions of this item:
- Kurt Brannas & Niklas Nordman, 2003. "An alternative conditional asymmetry specification for stock returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 537-541.
- Brännäs, Kurt & Nordman, Niklas, 2001. "An Alternative Conditional Asymmetry Specification for Stock Returns," Umeå Economic Studies 556, Umeå University, Department of Economics.
References listed on IDEAS
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- Brännäs, Kurt & de Gooijer, Jan G., 2000. "ASYMMETRIES IN CONDITIONAL MEAN AND VARIANCE: MODELLING STOCK RETURNS BY asMA-asQGARCH," Umeå Economic Studies 535, Umeå University, Department of Economics.
- Kurt Brännäs & Jan G. de Gooijer, 2000. "Asymmetries in Conditional Mean and Variance: Modelling Stock Returns by asMA-asQGARCH," Tinbergen Institute Discussion Papers 00-049/4, Tinbergen Institute.
- Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(04), pages 465-487, December.
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Cited by:
- Brännäs, Kurt, 2003. "Temporal Aggregation of the Returns of a Stock Index Series," Umeå Economic Studies 614, Umeå University, Department of Economics.
- Kurt Brannas & Albina Soultanaeva, 2011. "Influence of news from Moscow and New York on returns and risks of Baltic States’ stock markets," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 11(1), pages 109-124, July.
- Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008.
"Parameterizing Unconditional Skewness in Models for Financial Time Series,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 6(2), pages 208-230, Spring.
- Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2005. "Parameterizing Unconditional Skewness in Models for Financial Time Series," Research Paper Series 169, Quantitative Finance Research Centre, University of Technology, Sydney.
- Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing unconditional skewness in models for financial time series," CREATES Research Papers 2008-07, Department of Economics and Business Economics, Aarhus University.
- C. James Hueng, 2006. "Short-sales constraints and stock return asymmetry: evidence from the Chinese stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 707-716.
- Kurt Brannas & Niklas Nordman, 2003.
"Conditional skewness modelling for stock returns,"
Applied Economics Letters,
Taylor & Francis Journals, vol. 10(11), pages 725-728.
- Brännäs, Kurt & Nordman, Niklas, 2001. "Conditional Skewness Modelling for Stock Returns," Umeå Economic Studies 562, Umeå University, Department of Economics.
- Brännäs, Kurt & Soultanaeva, Albina, 2006. "Influence of News in Moscow and New York on Returns and Risks on Baltic State Stock Indices," Umeå Economic Studies 696, Umeå University, Department of Economics.
- Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.
- Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.
More about this item
Keywords
Time series; finance; nonlinearity; skewness; gamma; estimation; NYSE;JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
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