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Time Series Simulation With Quasi-Monte Carlo Methods

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  • Peter Winker

    (University of Manheim)

  • Jenny Li

    (The Pennsylvania State University)

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.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 151.

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Date of creation: 05 Jul 2000
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Handle: RePEc:sce:scecf0:151

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  1. Franz, Wolfgang & Göggelmann, Klaus & Schellhorn, Martin & Winker, Peter, 1998. "Quasi - Monte Carlo Methods in Stochastic Simulations," ZEW Discussion Papers 98-03, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  2. Neil R. Ericsson & Jaime Marquez, 1998. "A framework for economic forecasting," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C228-C266.
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Cited by:
  1. Johannes Paha, 2010. "Simulation and Prosecution of a Cartel with Endogenous Cartel Formation," MAGKS Papers on Economics 201007, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  2. Okten, Giray & Eastman, Warren, 2004. "Randomized quasi-Monte Carlo methods in pricing securities," Journal of Economic Dynamics and Control, Elsevier, vol. 28(12), pages 2399-2426, December.
  3. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Society for Computational Economics, vol. 31(1), pages 21-43, February.

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