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Bootstrapping the economy -- a non-parametric method of generating consistent future scenarios


  • Müller, Ulrich A
  • Bürgi, Roland
  • Dacorogna, Michel M


The fortune and the risk of a business venture depends on the future course of the economy. There is a strong demand for economic forecasts and scenarios that can be applied to planning and modeling. While there is an ongoing debate on modeling economic scenarios, the bootstrapping (or resampling) approach presented here has several advantages. As a non-parametric method, it directly relies on past market behaviors rather than debatable assumptions on models and parameters. Simultaneous dependencies between economic variables are automatically captured. Some aspects of the bootstrapping method require additional modeling: choice and ransformation of the economic variables, arbitrage-free consistency, heavy tails of distributions, serial dependence, trends and mean reversion. Results of a complete economic scenario generator are presented, tested and discussed.

Suggested Citation

  • Müller, Ulrich A & Bürgi, Roland & Dacorogna, Michel M, 2004. "Bootstrapping the economy -- a non-parametric method of generating consistent future scenarios," MPRA Paper 17755, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:17755

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    References listed on IDEAS

    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Ballocchi, Giuseppe & Dacorogna, Michel M. & Hopman, Carl M. & Muller, Ulrich A. & Olsen, Richard B., 1999. "The intraday multivariate structure of the Eurofutures markets," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 479-513, December.
    3. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    4. Giovanni Barone-Adesi & Kostas Giannopoulos & Les Vosper, 2002. "Backtesting Derivative Portfolios with Filtered Historical Simulation (FHS)," European Financial Management, European Financial Management Association, vol. 8(1), pages 31-58.
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    More about this item


    economic scenario generator (ESG); asset-liability management (ALM); bootstrapping; resampling; simulation; Monte-Carlo simulation; non-parametric model; yield curve model;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics


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