A Finite Mixture Modelling Perspective for Combining Experts’ Opinions with an Application to Quantile-Based Risk Measures

Despoina Makariou, Pauline Barrieu and George Tzougas
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Despoina Makariou: Department of Statistics, London School of Economics and Political Science, London WC2A 2AE, UK
Pauline Barrieu: Department of Statistics, London School of Economics and Political Science, London WC2A 2AE, UK
George Tzougas: Department of Statistics, London School of Economics and Political Science, London WC2A 2AE, UK

Risks, 2021, vol. 9, issue 6, 1-25

Abstract: The key purpose of this paper is to present an alternative viewpoint for combining expert opinions based on finite mixture models. Moreover, we consider that the components of the mixture are not necessarily assumed to be from the same parametric family. This approach can enable the agent to make informed decisions about the uncertain quantity of interest in a flexible manner that accounts for multiple sources of heterogeneity involved in the opinions expressed by the experts in terms of the parametric family, the parameters of each component density, and also the mixing weights. Finally, the proposed models are employed for numerically computing quantile-based risk measures in a collective decision-making context.

Keywords: opinion pooling; finite mixture models; expectation maximization algorithm; quantile-based risk measures (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:9:y:2021:i:6:p:115-:d:572157

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