Time Series Simulation with Quasi Monte Carlo Methods

Jenny X. Li, Peter Winker

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


This paper compares quasi Monte Carlo methods, in particularso-called (t, m, s)-nets, with classical Monte Carlo approaches forsimulating econometric time-series models. Quasi Monte Carlomethods have found successful application in many fields, such asphysics, image processing, and the evaluation of financederivatives. However, they are rarely used in econometrics. Here,we apply both traditional and quasi Monte Carlo simulation methodsto time-series models that typically arise in macroeconometrics.The numerical experiments demonstrate that quasi Monte Carlomethods outperform traditional ones for all models we investigate. © 2003 Kluwer Academic Publishers.
Original languageEnglish (US)
Pages (from-to)23-43
Number of pages21
JournalComputational Economics
Issue number1-2
StatePublished - Apr 1 2003
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-23

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)
  • Computer Science Applications


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