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The benefits of improved covariance estimation

H.J. Turtle and Kainan Wang

Journal of Empirical Finance, 2016, vol. 37, issue C, 233-246

Abstract: 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)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:37:y:2016:i:c:p:233-246

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Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

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