Maximum non-extensive entropy block bootstrap for non-stationary processes

0455411 - NHU-C 2016 RIV CA eng J - Článek v odborném periodiku
Bergamelli, M. - Novotný, Jan - Urga, G.
Maximum non-extensive entropy block bootstrap for non-stationary processes.
Actualite Economique. Roč. 91, 1/2 (2015), s. 115-139. ISSN 0001-771X
Institucionální podpora: PRVOUK-P23
Klíčová slova: maximum entropy * bootstrap * Monte Carlo simulations
Kód oboru RIV: AH - Ekonomie

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.
Trvalý link: http://hdl.handle.net/11104/0256027