Uses and computation of imprecise probabilities from statistical data and expert arguments

• Published in: International journal of approximate reasoning Vol. 81; pp. 63 - 86
• Main Author: Matt, Paul-Amaury
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.02.2017
• Subjects: Abstract argumentation; Added value; Coherence; Coherent previsions; Coherent risk measures; Computation; Decision making under uncertainty; Imprecise probabilities; Mathematical models; Optimization; Raw materials; Risk analysis; Statistical inference; Coherent risk measures; Abstract argumentation; Imprecise probabilities; Statistical inference; Coherent previsions; Decision making under uncertainty
• ISSN: 0888-613X; 1873-4731
• DOI: 10.1016/j.ijar.2016.11.003

Imprecise probabilities and the theory of coherent previsions offer a rigorous and powerful framework for modelling subjective uncertainty and solving problems of statistical inference, decision making or risk analysis. The paper introduces formulas for computing imprecise probabilities when statistical data and expert arguments are available to a subject. We then show how to use these imprecise probabilities (dialectical probabilities) for comparing the likelihood of events, conditioning on events, comparing decisions, computing optimal decisions or assessing financial risk. We apply the method to stock trading and show in this experiment the added value both of imprecision and of expert arguments derived from Technical Analysis. •Formulas for computing imprecise probabilities based on statistical data and expert arguments.•Formulas/algorithms for statistical inference, decision making and risk analysis.•Detailed application to stock trading.