TIME SERIES SIMULATION WITH QUASI-MONTE CARLO METHODS

Peter Winker and Jenny Li
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Jenny Li: The Pennsylvania State University

No 151, Computing in Economics and Finance 2000 from Society for Computational Economics

Abstract: The purpose of this paper is to compare the use of quasi-Monte Carlo methods, in particular the so--called $(t,m,s)-nets$ technique, versus classical Monte Carlo approaches for the simulation of econometric time series models. Some theoretic results indicate the superiority of quasi-Monte Carlo methods. Successful applications already exist in image processing, physics, and the evaluation of finance derivatives. However, so far, quasi--Monte Carlo methods are rarely used in the field of econometrics. In this paper, we apply both traditional Monte Carlo and quasi--Monte Carlo simulation methods to time series models as they typically arise in macroeconometrics. The numerical evidence demonstrates that quasi--Monte Carlo methods outperform the traditional Monte Carlo for many time series models including non-linear and multivariate models.

Date: 2000-07-05
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http://fmwww.bc.edu/cef00/papers/paper151.pdf (application/pdf)

Related works:
Journal Article: Time Series Simulation with Quasi Monte Carlo Methods (2003)
Journal Article: Time Series Simulation with Quasi Monte Carlo Methods (2003)
Working Paper: Time Series Simulation With Quasi Monte Carlo Methods (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf0:151

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