Time Series Mixtures of Generalized t Experts: ML Estimation and an Application to Stock Return Density Forecasting
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
- Raffaella Giacomini & Andreas Gottschling & Christian Haefke & Halbert White, 2002.
Boston College Working Papers in Economics
584, Boston College Department of Economics.
- Raffaella Giacomini & Andreas Gottschling & Christian Haefke & Halbert White, 2002. "Hypernormal densities," Economics Working Papers 638, Department of Economics and Business, Universitat Pompeu Fabra.
- Giacomini, Raffaella & Haefke, Christian & White, Halbert & Gottschling, Andreas, 2002. "Hypernormal Densities," University of California at San Diego, Economics Working Paper Series qt9wr373nt, Department of Economics, UC San Diego.
More about this item
KeywordsConditional density forecast; Generalized t distribution; Heavy tail distributions; Maximum likelihood estimation; Mixtures-of-experts; Nonlinear time series;
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:642-687. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://www.tandfonline.com/LECR20 .