Using high frequency stock market index data to calculate, model and forecast realized return variance
AbstractNo abstract is available for this item.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by European University Institute in its series Economics Working Papers with number ECO2001/06.
Date of creation: 2001
Date of revision:
Contact details of provider:
Postal: Badia Fiesolana, Via dei Roccettini, 9, 50016 San Domenico di Fiesole (FI) Italy
Web page: http://www.eui.eu/ECO/
More information through EDIRC
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Giot,Pierre & Laurent,Sebastien, 2001.
"Modelling daily value-at-risk using realized volatility and arch type models,"
014, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
- Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
- Pierre Giot & Sébastien Laurent, 2002. "Modelling Daily Value-at-Risk Using Realized Volatility and ARCH Type Models," Computing in Economics and Finance 2002 52, Society for Computational Economics.
- Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
- Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
- Roxana Halbleib & Valeri Voev, 2011.
"Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors,"
Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik),
Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 231(1), pages 134-152, February.
- Roxana Halbleib & Valerie Voev, 2010. "Forecasting Multivariate Volatility Using the VARFIMA Model on Realized Covariance Cholesky Factors," Working Papers ECARES ECARES 2010-041, ULB -- Universite Libre de Bruxelles.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marcia Gastaldo).
If references are entirely missing, you can add them using this form.