MAXIMUM NON-EXTENSIVE ENTROPY BLOCK BOOTSTRAP FOR NON-STATIONARY PROCESSES

Michele Bergamelli (), Jan Novotný () and Giovanni Urga
Additional contact information
Michele Bergamelli: Cass Business School - City University London
Jan Novotný: Cass Business School - City University London

L'Actualité Economique, 2015, vol. 91, issue 1-2, 115-139

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 López-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.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://id.erudit.org/iderudit/1036916ar Full text (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:actuec:0115

Access Statistics for this article

L'Actualité Economique is currently edited by Benoit Dostie

More articles in L'Actualité Economique from Société Canadienne de Science Economique Contact information at EDIRC.
Bibliographic data for series maintained by Benoit Dostie ( this e-mail address is bad, please contact ).