Optimal search for parameters in Monte Carlo simulation for derivative pricing

Chuan Ju Wang*, Ming-Yang Kao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper provides a novel and general framework for the problem of searching parameter space in Monte Carlo simulations. We propose a deterministic online algorithm and a randomized online algorithm to search for suitable parameter values for derivative pricing which are needed to achieve desired precisions. We also give the competitive ratios of the two algorithms and prove the optimality of the algorithms. Experimental results on the performance of the algorithms are presented and analyzed as well.

Original languageEnglish (US)
Pages (from-to)683-690
Number of pages8
JournalEuropean Journal of Operational Research
Issue number2
StatePublished - Mar 1 2016


  • Competitive ratio
  • Deterministic online algorithm
  • Finance
  • Monte Carlo simulation
  • Randomized online algorithm

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Fingerprint Dive into the research topics of 'Optimal search for parameters in Monte Carlo simulation for derivative pricing'. Together they form a unique fingerprint.

Cite this