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Portfolio optimization under partial uncertainty and incomplete information: a probability multimeasure-based approach

  • Multiple Objective Optimization
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Abstract

Markowitz’s work has had a major impact on academic research and the financial industry as a whole. The main idea of his model is risk aversion of average investors and their desire to maximise the expected return with the least risk. In this paper we extend the classical Markowitz’s model by introducing a portfolio optmization model in which the underlying space of events is described in terms of a probability multimeasure. The notion of probability multimeasure allows to formalize the concept of imprecise probability measure and incomplete information.

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Acknowledgments

The second author (FM) was partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) in the form of a Discovery Grant (238549-2012).

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Correspondence to D. La Torre.

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La Torre, D., Mendivil, F. Portfolio optimization under partial uncertainty and incomplete information: a probability multimeasure-based approach. Ann Oper Res 267, 267–279 (2018). https://doi.org/10.1007/s10479-016-2298-x

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  • DOI: https://doi.org/10.1007/s10479-016-2298-x

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