Non-nested Monte Carlo dual bounds for multi-exercisable options

Xiang Cheng, Zhuo Jin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We study the optimal marginal value of discrete-time optimal multiple stopping problems and find that it can be formulated as a single optimal stopping optimization as well. Based on this result propose a marginal-value-based lower bound method to achieve a small bound on the iterative error. We further introduce a non-nested upper bound method. The convergence of both methods is analysed. The implementation details and enhancement techniques are discussed as well. Overall, our methods make a good trade-off between the time-efficiency and the tightness in dual bounds.

Original languageEnglish
Article number2
Pages (from-to)269-292
Number of pages24
JournalCommunications on Stochastic Analysis
Issue number3
Publication statusPublished - 2019
Externally publishedYes


  • Duality
  • Multi-exercisable option
  • Optimal stopping


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