IDEAS home Printed from https://ideas.repec.org/p/mse/cesdoc/13023.html
   My bibliography  Save this paper

Understanding Exchange Rates Dynamics

Author

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
    as

    Download full text from publisher

    File URL: ftp://mse.univ-paris1.fr/pub/mse/CES2013/13023.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    2. Donald L. Kohn, 2008. "Lessons for central bankers from a Phillips curve framework," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    3. González-Rivera, Gloria & Sun, Yingying, 2017. "Density forecast evaluation in unstable environments," International Journal of Forecasting, Elsevier, vol. 33(2), pages 416-432.
    4. Gareis, Johannes & Mayer, Eric, 2020. "Financial shocks and the relative dynamics of tangible and intangible investment: Evidence from the euro area," Discussion Papers 39/2020, Deutsche Bundesbank.
    5. Hertrich Markus, 2019. "A Novel Housing Price Misalignment Indicator for Germany," German Economic Review, De Gruyter, vol. 20(4), pages 759-794, December.
    6. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    7. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    8. Craig S. Hakkio, 2009. "Global inflation dynamics," Research Working Paper RWP 09-01, Federal Reserve Bank of Kansas City.
    9. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    10. Verbrugge, Randal & Zaman, Saeed, 2023. "The hard road to a soft landing: Evidence from a (modestly) nonlinear structural model," Energy Economics, Elsevier, vol. 123(C).
    11. Banerjee, Anindya & Marcellino, Massimiliano, 2006. "Are there any reliable leading indicators for US inflation and GDP growth?," International Journal of Forecasting, Elsevier, vol. 22(1), pages 137-151.
    12. Camba-Mendez, Gonzalo & Rodriguez-Palenzuela, Diego, 2003. "Assessment criteria for output gap estimates," Economic Modelling, Elsevier, vol. 20(3), pages 529-562, May.
    13. Ivan, Kitov, 2006. "Exact prediction of inflation in the USA," MPRA Paper 2735, University Library of Munich, Germany.
    14. Canelli, Rosa & Fontana, Giuseppe & Realfonzo, Riccardo & Passarella, Marco Veronese, 2024. "Energy crisis, economic growth and public finance in Italy," Energy Economics, Elsevier, vol. 132(C).
    15. Adriana Cornea‐Madeira & João Madeira, 2022. "Econometric Analysis of Switching Expectations in UK Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 651-673, June.
    16. Tae-Hwan Kim & Paul Mizen & Thanaset Chevapatrakul, 2008. "Forecasting changes in UK interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 53-74.
    17. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    18. Mark J. Holmes & Arthur Grimes, 2005. "Is there long-run convergence of regional house prices in the UK?," Working Papers 05_11, Motu Economic and Public Policy Research.
    19. Lawrence Christiano & Mathias Trabandt & Karl Walentin, 2021. "Involuntary Unemployment and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 39, pages 26-54, January.
    20. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mse:cesdoc:13023. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lucie Label (email available below). General contact details of provider: https://edirc.repec.org/data/cenp1fr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.