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- W2596950033 abstract "This paper develops methods for combining density forecasts which accommodate stochastic dependence between different experts’ predictions. Previous work combining density forecasts, using so-called “opinion pools”, has essentially ignored dependence. The proposed basis for modelling the dependence among di.erent experts’ densities is a recalibration function, based on the probability integral transforms of the expert densities. We show that this reduces to a copula function in a special case. We explore the properties of various approximations to the recalibration function both via Monte Carlo simulations and in an application density forecasting U.K. inflation using the Bank of England’s “fan” chart. We find that the copula opinion pool can deliver more accurate densities than traditional linear and logarithmic opinion pools in many realistic situations when historical data on expert performance are available." @default.
- W2596950033 created "2017-03-23" @default.
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- W2596950033 date "2013-01-01" @default.
- W2596950033 modified "2023-09-27" @default.
- W2596950033 title "The Recalibrated and Copula Opinion Pools" @default.
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