The benefits of improved covariance estimation
H.J. Turtle and
Journal of Empirical Finance, 2016, vol. 37, issue C, pages 233-246
Recent advances in covariance estimation can improve portfolio formation strategies aimed at avoiding high risk market environments. We consider a covariance specification with information variables that include both historical firm specific variables and an ex ante measure of macro volatility (CBOE VIX). We compare the in-sample and predictive out-of-sample performance of the information instrument model relative to three alternative approaches. Out-of-sample, a risk-on, risk-off strategy that optimally weights the global minimum variance (GMV) portfolio and a riskless asset shows the information instrument model provides effective exit signals during the financial crisis and other high risk environments.
Keywords: Conditional covariances; Information instruments; Portfolio performance; Mean–variance analysis (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: http://EconPapers.repec.org/RePEc:eee:empfin:v:37:y:2016:i:c:p:233-246
Access Statistics for this article
Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff
More articles in Journal of Empirical Finance from Elsevier
Series data maintained by Dana Niculescu ().