Portfolio selection under supply chain predictability

Thomas Trier Bjerring*, Kourosh Marjani Rasmussen, Alex Weissensteiner

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

We investigate whether the returns of some industry portfolios predict the returns of other industry portfolios. We find a strong lead-lag structure which is statistically and economically significant. These findings suggest that information diffuses only gradually across industries. Moreover, we show that this predictability can be exploited in a mean-variance optimization framework. The calculated out-of-sample portfolio returns are attractive under different return-risk measures, and they show positive risk-adjusted excess returns which are not explained by classical risk factors.
Original languageEnglish
JournalComputational Management Science
Volume15
Issue number2
Pages (from-to)139–159
ISSN1619-697X
DOIs
Publication statusPublished - 2018

Cite this

Bjerring, Thomas Trier ; Rasmussen, Kourosh Marjani ; Weissensteiner, Alex. / Portfolio selection under supply chain predictability. In: Computational Management Science. 2018 ; Vol. 15, No. 2. pp. 139–159.
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Portfolio selection under supply chain predictability. / Bjerring, Thomas Trier; Rasmussen, Kourosh Marjani; Weissensteiner, Alex.

In: Computational Management Science, Vol. 15, No. 2, 2018, p. 139–159.

Research output: Contribution to journalJournal articleResearchpeer-review

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AB - We investigate whether the returns of some industry portfolios predict the returns of other industry portfolios. We find a strong lead-lag structure which is statistically and economically significant. These findings suggest that information diffuses only gradually across industries. Moreover, we show that this predictability can be exploited in a mean-variance optimization framework. The calculated out-of-sample portfolio returns are attractive under different return-risk measures, and they show positive risk-adjusted excess returns which are not explained by classical risk factors.

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