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Flexible time series models for subjective distribution estimation with monetary policy in view

Author

Listed:
  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Florian Ielpo

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this paper, we introduce a new approach to estimate the subjective distribution of the future short rate from the historical dynamics of futures, based on a model generated by a Normal Inverse Gaussian distribution, with dynamical parameters. The model displays time varying conditional volatility, skewness and kurtosis and provides a flexible framework to recover the conditional distribution of the future rates. For the estimation, we use maximum likelihood method. Then, we apply the model to Fed Fund futures and discuss its performance.

Suggested Citation

  • Dominique Guegan & Florian Ielpo, 2007. "Flexible time series models for subjective distribution estimation with monetary policy in view," Post-Print halshs-00188247, HAL.
    • Handle: RePEc:hal:journl:halshs-00188247
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00188247
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    References listed on IDEAS

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