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

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Author Info
Dominique Guégan () (Centre d'Economie de la Sorbonne)
Florian Ielpo () (Centre d'Economie de la Sorbonne)

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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.

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Publisher Info
Paper provided by Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne in its series Documents de travail du Centre d'Economie de la Sorbonne with number b07056.

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Length: 27 pages
Date of creation: Oct 2007
Date of revision:
Handle: RePEc:mse:cesdoc:b07056

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Web page: http://ces.univ-paris1.fr/
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Related research
Keywords: Subjective distribution; autoregressive conditional density; generalized hyperbolic distribution; Fed Funds futures contracts.;

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Find related papers by JEL classification:
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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References listed on IDEAS
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  1. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June. [Downloadable!] (restricted)
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  2. Jackwerth, Jens Carsten, 2000. "Recovering Risk Aversion from Option Prices and Realized Returns," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 13(2), pages 433-51.
    Other versions:
  3. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-30, August. [Downloadable!] (restricted)
    Other versions:
  4. Marvin Goodfriend, 1990. "Interest rates and the conduct of monetary policy," Working Paper 90-06, Federal Reserve Bank of Richmond. [Downloadable!]
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  5. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 9-51. [Downloadable!] (restricted)
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  6. Marie Brière, 2006. "Market Reactions to Central Bank Communication Policies : Reading Interest Rate Options Smiles," Working Papers CEB 06-009.RS, Université Libre de Bruxelles, Solvay Business School, Centre Emile Bernheim (CEB). [Downloadable!]
  7. Monika Piazzesi & Eric Swanson, 2004. "Futures Prices as Risk-adjusted Forecasts of Monetary Policy," NBER Working Papers 10547, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July. [Downloadable!] (restricted)
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