GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts
David Ardia and
Lennart F. Hoogerheide
Economics Letters, 2014, vol. 123, issue 2, 187-190
Abstract:
We analyze the impact of the estimation frequency–updating parameter estimates on a daily, weekly, monthly or quarterly basis–for commonly used GARCH models in a large-scale study, using more than twelve years (2000–2012) of daily returns for constituents of the S&P 500 index. We assess the implication for one-day ahead 95% and 99% Value-at-Risk (VaR) forecasts with the test for correct conditional coverage of Christoffersen (1998) and for Expected Shortfall (ES) forecasts with the block-bootstrap test of ES violations of Jalal and Rockinger (2008). Using the false discovery rate methodology of Storey (2002) to estimate the percentage of stocks for which the model yields correct VaR and ES forecasts, we conclude that there is no difference in performance between updating the parameter estimates of the GARCH equation at a daily or weekly frequency, whereas monthly or even quarterly updates are only marginally outperformed.
Keywords: GARCH; Value-at-Risk; Expected Shortfall; Equity; Frequency; False discovery rate (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176514000640
Full text for ScienceDirect subscribers only
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:eee:ecolet:v:123:y:2014:i:2:p:187-190
DOI: 10.1016/j.econlet.2014.02.008
Access Statistics for this article
Economics Letters is currently edited by Economics Letters Editorial Office
More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().