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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

Suggested Citation

  • Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Understanding Exchange Rates Dynamics," Documents de travail du Centre d'Economie de la Sorbonne 13023, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    • Handle: RePEc:mse:cesdoc:13023
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    References listed on IDEAS

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    1. Daniel Buncic, 2012. "Understanding forecast failure of ESTAR models of real exchange rates," Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
    2. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
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    1. Addo, Peter Martey & Billio, Monica & Guégan, Dominique, 2013. "Nonlinear dynamics and recurrence plots for detecting financial crisis," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 416-435.
    2. Peter Martey Addo & Philippe De Peretti & Hayette Gatfaoui & Jakob Runge, 2014. "The kiss of information theory that captures systemic risk," Documents de travail du Centre d'Economie de la Sorbonne 14069r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Mar 2015.
    3. Petre CARAIANI, 2015. "Testing For Nonlinearity In Unemployment Rates Via Delay Vector Variance," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 81-92, March.
    4. 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 13025, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    5. Emmanuel Numapau Gyamfi & Kwabena A. Kyei, 2016. "Modeling Stock Market Returns under Self-exciting Threshold Autoregressive Model: Evidence from West Africa," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1194-1199.
    6. Peter Martey Addo & Philippe De Peretti, 2014. "Detection and quantification of causal dependencies in multivariate time series: a novel information theoretic approach to understanding systemic risk," Documents de travail du Centre d'Economie de la Sorbonne 14069, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    7. 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.
    8. Jaksic, Vesna & Mandic, Danilo P. & Karoumi, Raid & Basu, Bidroha & Pakrashi, Vikram, 2016. "Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 100-120.

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    More about this item

    Keywords

    Nonlinearity analysis; exchange rates; surrogates; Delay vector variance (DVV)method; wavelets;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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