Maximum Non-Extensive Entropy Block Bootstrap for Non-Stationary Processes

28 Pages Posted: 3 Apr 2015

See all articles by Michele Bergamelli

Michele Bergamelli

City University London - The Business School

Jan Novotny

Centre for Econometric Analysis, Faculty of Finance, Cass Business School, London, UK

Giovanni Urga

Centre for Econometric Analysis, Faculty of Finance, Bayes Business School (formerly Cass), London, UK

Date Written: April 1, 2015

Abstract

In this paper, we propose a novel entropy-based resampling scheme valid for non-stationary data. In particular, we identify the reason for the failure of the original entropy-based algorithm of Vinod and Lopez-de Lacalle (2009) to be the perfect rank correlation between the actual and bootstrapped time series. We propose the Maximum Entropy Block Bootstrap which preserves the rank correlation locally. Further, we also introduce the Maximum non-extensive Entropy Block Bootstrap to allow for fat tail behaviour in time series. Finally, we show the optimal finite sample properties of the proposed methods via a Monte Carlo analysis where we bootstrap the distribution of the Dickey-Fuller test.

Keywords: Maximum Entropy, Bootstrap, Monte Carlo Simulations

JEL Classification: C12, C14, C15, C46, C63

Suggested Citation

Bergamelli, Michele and Novotny, Jan and Urga, Giovanni, Maximum Non-Extensive Entropy Block Bootstrap for Non-Stationary Processes (April 1, 2015). Available at SSRN: https://ssrn.com/abstract=2588500 or http://dx.doi.org/10.2139/ssrn.2588500

Michele Bergamelli

City University London - The Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Jan Novotny (Contact Author)

Centre for Econometric Analysis, Faculty of Finance, Cass Business School, London, UK ( email )

Giovanni Urga

Centre for Econometric Analysis, Faculty of Finance, Bayes Business School (formerly Cass), London, UK ( email )

108 Bunhill Row
London, EC1Y 8TZ
United Kingdom
+44 20 7040 8698 (Phone)
+44 20 7040 8881 (Fax)

HOME PAGE: http://www.bayes.city.ac.uk/faculties-and-research/experts/giovanni-urga

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