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Technical Note—Bootstrap-based Budget Allocation for Nested Simulation

Author

Listed:
  • Kun Zhang

    (Institute of Statistics and Big Data, Renmin University of China, Beijing 100872, China)

  • Guangwu Liu

    (Department of Management Sciences, College of Business, City University of Hong Kong, Kowloon, Hong Kong, China)

  • Shiyu Wang

    (Department of Management Sciences, College of Business, City University of Hong Kong, Kowloon, Hong Kong, China)

Abstract

Simulation budget allocation is at the heart of a nested (also referred to as two-level) simulation approach to estimating functionals of a conditional expectation. In this paper, we propose a sample-driven budget allocation rule under a unified nested simulation framework that allows for different forms of functionals. The proposed method employs bootstrap sampling to guide an effective choice of outer- and inner-level sample sizes. Furthermore, we establish a central limit theorem for nested simulation estimators, and incorporate the sample-driven allocation rule into the construction of asymptotically valid confidence intervals (CIs). Effectiveness of the sample-driven allocation rule and validity of the constructed CIs are confirmed by numerical experiments.

Suggested Citation

  • Kun Zhang & Guangwu Liu & Shiyu Wang, 2022. "Technical Note—Bootstrap-based Budget Allocation for Nested Simulation," Operations Research, INFORMS, vol. 70(2), pages 1128-1142, March.
    • Handle: RePEc:inm:oropre:v:70:y:2022:i:2:p:1128-1142
    DOI: 10.1287/opre.2020.2071
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