Worldwide equity Risk Prediction
David Ardia and
Lennart F. Hoogerheide
Cahiers de recherche from CIRPEE
Various GARCH models are applied to daily returns of more than 1200 constituents of major stock indices worldwide. The value-at-risk forecast performance is investigated for different markets and industries, considering the test for correct conditional coverage using the false discovery rate (FDR) methodology. For most of the markets and industries we find the same two conclusions. First, an asymmetric GARCH specification is essential when forecasting the 95% value-at-risk. Second, for both the 95% and 99% value-at-risk it is crucial that the innovations’ distribution is fat-tailed (e.g., Student-t or – even better – a non-parametric kernel density estimate). Then we discuss two applications. First, we use normal Entropy Pooling to estimate a market distribution consistent with the CAPM equilibrium, which improves on the “implied returns” a-la-Black and Litterman (1990) and can be used as the starting point for portfolio construction. Second, we use normal Entropy Pooling to process ranking signals for alpha-generation.
Keywords: GARCH; value-at-risk; equity; worldwide; false discovery rate (search for similar items in EconPapers)
JEL-codes: C11 C22 C52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for and nep-rmg
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Journal Article: Worldwide equity risk prediction (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:lvl:lacicr:1312
Access Statistics for this paper
More papers in Cahiers de recherche from CIRPEE Contact information at EDIRC.
Bibliographic data for series maintained by Manuel Paradis ().