Flexible time series models for subjective distribution estimation with monetary policy in view
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.
|Date of creation:||Oct 2007|
|Date of revision:|
|Publication status:||Published in Documents de travail du Centre d'Economie de la Sorbonne 2007.56 - ISSN : 1955-611X. 2007|
|Note:||View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00188247|
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