Evaluating density forecasts from models of stock market returns
Gabriela De Raaij and
Burkhard Raunig
The European Journal of Finance, 2005, vol. 11, issue 2, 151-166
Abstract:
Density forecasts have become important in finance and play a key role in modern risk management. Using a flexible density forecast evaluation framework that extends the Berkowitz likelihood ratio test this paper evaluates in- and out-of-sample density forecasts of daily returns on the DAX, ATX and S&P 500 stock market indices from models of financial returns that are currently widely used in the financial industry. The results indicate that GARCH-t models produce good in-sample forecasts. No model considered in this study delivers fully acceptable out-of-sample forecasts. The empirical findings emphasize that proper distributional assumptions combined with an adequate specification of relevant conditional higher moments are necessary to obtain good density forecasts.
Keywords: Density forecasting; forecast evaluation; risk management; GARCH models (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/1351847042000255652 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:eurjfi:v:11:y:2005:i:2:p:151-166
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/REJF20
DOI: 10.1080/1351847042000255652
Access Statistics for this article
The European Journal of Finance is currently edited by Chris Adcock
More articles in The European Journal of Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().