ON THE AGGREGATION OF EXPERTS' INFORMATION IN BONUS–MALUS SYSTEMS
Copyright policy )ON THE AGGREGATION OF EXPERTS' INFORMATION IN BONUS–MALUS SYSTEMS
AbstractIn this paper, we propose a new family of premium calculation principles based on the use of prior information from different sources. Under this framework and based on the use of Ordered Weighted Averaging operators, we provide alternative collective and Bayes premiums and describe some approaches to efficiently compute them. Several examples are detailed to illustrate the performance of the new methods.
Applications of statistics to actuarial sciences and financial mathematics, FOS: Computer and information sciences, Bayesian inference, Bayesian statistics, Statistics - Applications, FOS: Economics and business, premium calculation principles, ordered weighted averaging, Optimization and Control (math.OC), Risk theory, insurance, non-life insurance, Risk Management (q-fin.RM), FOS: Mathematics, 97M30, 91B30, 90C90, 62C12, Applications (stat.AP), Mathematics - Optimization and Control, mathematical programming, Quantitative Finance - Risk Management
Applications of statistics to actuarial sciences and financial mathematics, FOS: Computer and information sciences, Bayesian inference, Bayesian statistics, Statistics - Applications, FOS: Economics and business, premium calculation principles, ordered weighted averaging, Optimization and Control (math.OC), Risk theory, insurance, non-life insurance, Risk Management (q-fin.RM), FOS: Mathematics, 97M30, 91B30, 90C90, 62C12, Applications (stat.AP), Mathematics - Optimization and Control, mathematical programming, Quantitative Finance - Risk Management
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