Convergence rates in the law of large numbers under sublinear expectations

2019/03/14 by Ze-Chun Hu, Hu, Ze-Chun, Ning-Hua Liu +3
Decision Sciences · Economics, Econometrics and Finance · Social Sciences · #FOS: Mathematics #Insurance, Mortality, Demography, Risk Management #Probability (math.PR) #Probability and Risk Models #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1903.05806

openalex publication_date 2019/03/14 · openalex created_date 2019/03/22 · openalex updated_date 2026/07/28

Abstract

In this note, we study convergence rates in the law of large numbers for independent and identically distributed random variables under sublinear expectations. We obtain a strong L^p-convergence version and a strongly quasi sure convergence version of the law of large numbers.

Citations

• A strong law of large numbers for non-additive probabilities

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