Flexible time series models for subjective distribution estimation with monetary policy in view
AbstractIn 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.
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Date of creation: Oct 2007
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Subjective distribution; autoregressive conditional density; generalized hyperbolic distribution; Fed Funds futures contracts.;
Other versions of this item:
- Dominique Guégan & Florian Ielpo, 2008. "Flexible time series models for subjective distribution estimation with monetary policy in view," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 51(1), pages 79-103.
- Dominique Guégan & Florian Ielpo, 2007. "Flexible time series models for subjective distribution estimation with monetary policy in view," Documents de travail du Centre d'Economie de la Sorbonne b07056, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- Dominique Guegan & Florian Ielpo, 2008. "Flexible time series models for subjective distribution estimation with monetary policy in view," UniversitÃ© Paris1 PanthÃ©on-Sorbonne (Post-Print and Working Papers) halshs-00368356, HAL.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
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