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A strong law of large numbers for sub-linear expectation under a general moment condition

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  • Hu, Cheng

Abstract

In this paper, we derive a strong law of large numbers for sub-linear expectation under a general moment condition. The result can be reduced to the classical strong law of large numbers when the sub-linear expectation coincides with the classical linear expectation. Moreover, we illustrate that this moment condition for strong law of large numbers in sub-linear situation is the weakest.

Suggested Citation

  • Hu, Cheng, 2016. "A strong law of large numbers for sub-linear expectation under a general moment condition," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 248-258.
    • Handle: RePEc:eee:stapro:v:119:y:2016:i:c:p:248-258
    DOI: 10.1016/j.spl.2016.08.015
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    References listed on IDEAS

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    1. Zengjing Chen & Larry Epstein, 2002. "Ambiguity, Risk, and Asset Returns in Continuous Time," Econometrica, Econometric Society, vol. 70(4), pages 1403-1443, July.
    2. Korchevsky, Valery, 2015. "A generalization of the Petrov strong law of large numbers," Statistics & Probability Letters, Elsevier, vol. 104(C), pages 102-108.
    3. Marinacci, Massimo, 1999. "Limit Laws for Non-additive Probabilities and Their Frequentist Interpretation," Journal of Economic Theory, Elsevier, vol. 84(2), pages 145-195, February.
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    Cited by:

    1. Shuxia Guo & Zhe Meng, 2023. "The Marcinkiewicz–Zygmund-Type Strong Law of Large Numbers with General Normalizing Sequences under Sublinear Expectation," Mathematics, MDPI, vol. 11(23), pages 1-21, November.
    2. Xiang Zeng, 2025. "Laws of the k -Iterated Logarithm of Weighted Sums in a Sub-Linear Expected Space," Mathematics, MDPI, vol. 13(18), pages 1-16, September.

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