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Understanding Exchange Rates Dynamics

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Abstract

With the emergence of the chaos theory and the method of surrogates data, nonlinear approaches employed in analysing time series typically suffer from high computational complexity and lack of straightforward explanation. Therefore, the need for methods capable of characterizing time series in terms of their linear, nonlinear, deterministic and stochastic nature are preferable. In this paper, we provide a signal modality analysis on a variety of exchange rates. The analysis is achieved by using the recently proposed "delay vector variance" (DVV) method, which examines local predictability of a signal in the phase space to detect the presence of determinism and nonlinearity in a time series. Optimal embedding parameters used in the DVV analysis are obtain via differential entropy based method using wavelet-based surrogates. A comprehensive analysis of the feasibility of this approach is provided. The empirical results show that the DVV method can be opted as an alternative way to understanding exchange rates dynamics.

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File URL: ftp://mse.univ-paris1.fr/pub/mse/CES2013/13023.pdf
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Bibliographic 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 13023.

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Length: 15 pages
Date of creation: Mar 2013
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Handle: RePEc:mse:cesdoc:13023

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Keywords: Nonlinearity analysis; exchange rates; surrogates; Delay vector variance (DVV)method; wavelets.;

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  1. Buncic, Daniel, 2009. "Understanding forecast failure of ESTAR models of real exchange rates," MPRA Paper 16526, University Library of Munich, Germany.
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Cited by:
  1. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Turning point chronology for the Euro-Zone: A Distance Plot Approach," Documents de travail du Centre d'Economie de la Sorbonne 13025r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Oct 2013.
  2. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Nonlinear Dynamics and Recurrence Plots for Detecting Financial Crisis," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00803450, HAL.
  3. Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Studies in Nonlinear Dynamics and Wavelets for Business Cycle Analysis," Documents de travail du Centre d'Economie de la Sorbonne 12023r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Nov 2013.

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