IDEAS home Printed from https://ideas.repec.org/p/sce/scecf5/234.html
   My bibliography  Save this paper

Study of Nonlinearities in the Dynamics of Exchange Rates: Is There Any Evidence of Chaos?

Author

Listed:
  • Vitaliy Vandrovych

    (International Business School Brandeis University)

Abstract

This paper studies the dynamics of six major exchange rates, and runs formal tests to distinguish among different types of nonlinearities. In particular we study exchange rate returns, normalized exchange rates and exchange rate volatilities, classifying these series using BDS test, correlation dimensions and maximum Liapunov exponents. Estimates of dimension indicate high complexity in all series, suggesting that the series are either stochastic processes or high dimensional deterministic processes. Though we obtain a number of positive estimates of Liapunov exponent, they are quite small and it seems more appropriate to interpret them as indicating stochastic origin of the series.

Suggested Citation

  • Vitaliy Vandrovych, 2005. "Study of Nonlinearities in the Dynamics of Exchange Rates: Is There Any Evidence of Chaos?," Computing in Economics and Finance 2005 234, Society for Computational Economics.
    • Handle: RePEc:sce:scecf5:234
    as

    Download full text from publisher

    File URL: http://people.brandeis.edu/~vivandr/CCE2005%20paper.pdf
    File Function: main text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shintani, Mototsugu & Linton, Oliver, 2004. "Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos," Journal of Econometrics, Elsevier, vol. 120(1), pages 1-33, May.
    2. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
    3. Barnett, William A. & Serletis, Apostolos, 2000. "Martingales, nonlinearity, and chaos," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 703-724, June.
    4. Gilmore, Claire G., 2001. "An examination of nonlinear dependence in exchange rates, using recent methods from chaos theory," Global Finance Journal, Elsevier, vol. 12(1), pages 139-151.
    5. Bask, Mikael, 2000. "A Positive Lyapunov Exponent in Swedish Exchange Rates?," Umeå Economic Studies 528, Umeå University, Department of Economics.
    6. Hsieh, David A, 1989. "Testing for Nonlinear Dependence in Daily Foreign Exchange Rates," The Journal of Business, University of Chicago Press, vol. 62(3), pages 339-368, July.
    7. Brzozowska-Rup, Katarzyna & Orłowski, Arkadiusz, 2004. "Application of bootstrap to detecting chaos in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 317-321.
    8. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    9. Blake LeBaron, 1994. "Chaos and Nonlinear Forecastability in Economics and Finance," Finance 9411001, University Library of Munich, Germany.
    10. Mototsugu Shintani & Oliver Linton, 2003. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(1), pages 331-357, February.
    Full references (including those not matched with items on IDEAS)

    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. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    2. Marisa Faggini & Bruna Bruno & Anna Parziale, 2019. "Does Chaos Matter in Financial Time Series Analysis?," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 18-24.
    3. Hommes, C.H. & Manzan, S., 2005. "Testing for Nonlinear Structure and Chaos in Economic Time Series: A Comment," CeNDEF Working Papers 05-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    4. Olmedo,E. & Velasco, F. & Valderas, J.M., 2007. "Caracterización no lineal y predicción no paramétrica en el IBEX35/Nonlinear Characterization and Predictions of IBEX 35," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 25, pages 815-842, Diciembre.
    5. Cars Hommes & Sebastiano Manzan, 2006. "Testing for Nonlinear Structure and Chaos in Economic Time. A Comment," Tinbergen Institute Discussion Papers 06-030/1, Tinbergen Institute.
    6. Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.
    7. Graham Newell & Maurice Peat & Max Stevenson, 1997. "Testing for Evidence of Nonlinear Structure in Daily and Weekly United Kingdom Stock and Property Market Indicies," Working Paper Series 73, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    8. Czamanski, Daniel & Dormaar, Paul & Hinich, Melvin J. & Serletis, Apostolos, 2007. "Episodic nonlinearity and nonstationarity in Alberta's power and natural gas markets," Energy Economics, Elsevier, vol. 29(1), pages 94-104, January.
    9. Serletis, Apostolos & Uritskaya, Olga Y., 2007. "Detecting signatures of stochastic self-organization in US money and velocity measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 281-291.
    10. Venus Khim-Sen Liew, 2003. "The Validity of PPP Revisited: An Application of Non-linear Unit Root Test," International Finance 0308001, University Library of Munich, Germany.
    11. Amilon, Henrik & Byström, Hans, 1998. "The Search for Chaos and Nonlinearities in Swedish Stock Index Returns," Working Papers 1998:6, Lund University, Department of Economics.
    12. Bajo-Rubio, Oscar & Sosvilla-Rivero, Simon & Fernandez-Rodriguez, Fernando, 2001. "Asymmetry in the EMS: New evidence based on non-linear forecasts," European Economic Review, Elsevier, vol. 45(3), pages 451-473, March.
    13. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    14. Daniela Federici & Giancarlo Gandolfo, 2011. "The Euro/Dollar Exchange Rate: Chaotic or Non-Chaotic?," CESifo Working Paper Series 3420, CESifo.
    15. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
    16. Madhavan, Vinodh, 2013. "Nonlinearity in investment grade Credit Default Swap (CDS) Indices of US and Europe: Evidence from BDS and close-returns tests," Global Finance Journal, Elsevier, vol. 24(3), pages 266-279.
    17. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero & Maria Dolores Garcia-Artiles, 1997. "Using nearest neighbour predictors to forecast the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 21(1), pages 75-91, January.
    18. Elena Olmedo & Ricardo Gimeno & Lorenzo Escot & Ruth Mateos, 2007. "Convergencia y Estabilidad de los Tipos de Cambio Europeos: Una Aplicación de Exponentes de Lyapunov," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 44(129), pages 91-108.
    19. Graham Newell & Maurice Peat & Max Stevenson, 1996. "Testing for Evidence of Nonlinear Structure in Australian Real Estate Market Returns," Working Paper Series 61, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    20. Marco Pangallo, 2023. "Synchronization of endogenous business cycles," LEM Papers Series 2023/01, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

    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:sce:scecf5:234. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.