Adaptive Models and Heavy Tails

62 Pages Posted: 12 May 2016

See all articles by Davide Delle Monache

Davide Delle Monache

Bank of Italy

Ivan Petrella

University of Warwick; University of Warwick - Finance Group; University of Warwick - Warwick Business School; Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 2 versions of this paper

Date Written: February 25, 2016

Abstract

This paper introduces an adaptive algorithm for time-varying autoregressive models in the presence of heavy tails. The evolution of the parameters is determined by the score of the conditional distribution. The resulting model is observation-driven and is estimated by classical methods. Meaningful restrictions are imposed on the model parameters so as to attain local stationarity and bounded mean values. In particular, we consider time variation in both coefficients and volatility, emphasizing how the two interact. Moreover, we show how the proposed approach generalizes the various adaptive algorithms used in the literature. The model is applied to the analysis of inflation dynamics. Allowing for heavy tails leads to significant improvements in terms of fit and forecast. The adoption of the Student's-t distribution proves to be crucial in order to obtain well-calibrated density forecasts. These results are obtained using the US CPI inflation rate and are confirmed by other inflation indicators as well as the CPI of the other G7 countries.

Keywords: adaptive algorithms, inflation, score driven models, student-t, time-varying parameters

JEL Classification: C22, C51, C53, E31

Suggested Citation

Delle Monache, Davide and Petrella, Ivan and Petrella, Ivan and Petrella, Ivan, Adaptive Models and Heavy Tails (February 25, 2016). Bank of Italy Temi di Discussione (Working Paper) No. 1052, Available at SSRN: https://ssrn.com/abstract=2777989 or http://dx.doi.org/10.2139/ssrn.2777989

Davide Delle Monache (Contact Author)

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

Ivan Petrella

University of Warwick ( email )

Gibbet Hill Rd.
Coventry, West Midlands CV4 8UW
United Kingdom

University of Warwick - Warwick Business School ( email )

Coventry CV4 7AL
United Kingdom

University of Warwick - Finance Group ( email )

Gibbet Hill Rd
Coventry, CV4 7AL
Great Britain

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

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