Stochastic Spanning

dc.contributor.authorArvanitis, Stelios
dc.contributor.authorHallam, Mark
dc.contributor.authorPost, Thierry
dc.contributor.authorTopaloglou, Nikolas
dc.date.accessioned2019-12-11T09:01:10Z
dc.date.available2019-12-11T09:01:10Z
dc.date.issued2018
dc.descriptionhttps://www.tandfonline.com/doi/full/10.1080/07350015.2017.1391099en_US
dc.description.abstractThis study develops and implements methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for all risk averse investors. We develop a test procedure for “stochastic spanning” for two nested portfolio sets based on subsampling and linear programming. The test is statistically consistent and asymptotically exact for a class of weakly dependent processes. A Monte Carlo simulation experiment shows good statistical size and power properties in finite samples of realistic dimensions. In an application to standard datasets of historical stock market returns, we accept market portfolio efficiency but reject two-fund separation, which suggests an important role for higher-order moment risk in portfolio theory and asset pricing. Supplementary materials for this article are available online.en_US
dc.identifier.citationArvanitis, S., Hallam, M., Post, T., & Topaloglou, N. (2018). Stochastic Spanning. Journal of Business & Economic Statistics, 37(4), 573–585. https://doi.org/10.1080/07350015.2017.1391099en_US
dc.identifier.other000489086900001
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/4378
dc.language.isoenen_US
dc.publisherAMER STATISTICAL ASSOCen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectLinear programmingen_US
dc.subjectPortfolio choiceen_US
dc.subjectSpanningen_US
dc.subjectStochastic dominanceen_US
dc.subjectSubsamplingen_US
dc.titleStochastic Spanningen_US
dc.typeArticleen_US
workflow.import.sourcescience

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