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Time Series Simulation with Quasi Monte Carlo Methods

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  • Jenny X. Li
  • Peter Winker

Abstract

This paper compares quasi Monte Carlo methods, in particular so-called (t, m, s)-nets, with classical Monte Carlo approaches for simulating econometric time-series models. Quasi Monte Carlo methods have found successful application in many fields, such as physics, image processing, and the evaluation of finance derivatives. However, they are rarely used in econometrics. Here, we apply both traditional and quasi Monte Carlo simulation methods to time-series models that typically arise in macroeconometrics. The numerical experiments demonstrate that quasi Monte Carlo methods outperform traditional ones for all models we investigate.

Suggested Citation

  • Jenny X. Li & Peter Winker, 2003. "Time Series Simulation with Quasi Monte Carlo Methods," Computational Economics, Springer;Society for Computational Economics, vol. 21(1_2), pages 23-43, February.
    • Handle: RePEc:kap:compec:v:21:y:2003:i:1_2:p:23-43
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    References listed on IDEAS

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    1. Neil R. Ericsson & Jaime Marquez, 1998. "A framework for economic forecasting," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 228-266.
    2. Franz, Wolfgang & Göggelmann, Klaus & Schellhorn, Martin & Winker, Peter, 1998. "Quasi-Monte Carlo Methods in Stochastic Simulations: An Application to Fiscal Policy Simulations using an Aggregate Disequilibrium Model of the West German Economy," ZEW Discussion Papers 98-03, ZEW - Leibniz Centre for European Economic Research.
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    Citations

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    Cited by:

    1. 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.
    2. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.
    3. Yu-Ying Tzeng & Paul M. Beaumont & Giray Ökten, 2018. "Time Series Simulation with Randomized Quasi-Monte Carlo Methods: An Application to Value at Risk and Expected Shortfall," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 55-77, June.
    4. 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).

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    More about this item

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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