IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v379y2007i1p188-198.html
   My bibliography  Save this article

Self-similar characteristics of the currency exchange rate in an economy in transition

Author

Listed:
  • Scarlat, E.I.
  • Stan, Cristina
  • Cristescu, C.P.

Abstract

In this paper, we present an analysis of the self-similar characteristics of the temporal series describing the daily exchange rate of the Romanian currency unit “Leu” (ROL) with respect to the US Dollar (USD). The relevance of this investigation consists in the exchange rate being a proper indicator for the dynamics of an economy in transition from a command-type structure towards an open market one. The time series is exhibiting self-similar cells of dimensions obeying a definite power law scaling rule that is related to different categories of economic agents. By using a crossing-type analysis based on the Hurst exponent and the frequency spectrum, five categories were detected. A simple model based on active filters with prevailing feedforward loops working close to the unstable regime, each one describing an economic agent under the stress of a hostile economic environment, is proposed for the dynamics of the fragmentation–defragmentation process. The model qualitatively reproduces the self-similarity characteristics of the currency exchange rate of an economy in transition, subjected to deep structural changes. We observe that the “in-phase evolution” of the economic agents causes the statistical self-similarity to resemble a theoretical self-similarity.

Suggested Citation

  • Scarlat, E.I. & Stan, Cristina & Cristescu, C.P., 2007. "Self-similar characteristics of the currency exchange rate in an economy in transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 188-198.
    • Handle: RePEc:eee:phsmap:v:379:y:2007:i:1:p:188-198
    DOI: 10.1016/j.physa.2006.12.040
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437107000246
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2006.12.040?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Litvin, Vladimir A., 2004. "Multiscaling behavior in transition economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 178-183.
    2. Benhabib, Jess & Schmitt-Grohe, Stephanie & Uribe, Martin, 2001. "The Perils of Taylor Rules," Journal of Economic Theory, Elsevier, vol. 96(1-2), pages 40-69, January.
    3. Fu, Dongfeng & Pammolli, Fabio & Buldyrev, Sergey V. & Riccaboni, Massimo & Matia, Kaushik & Yamasaki, Kazuko & Stanley, H. Eugene, 2005. "The Growth of Business Firms: Theoretical Framework and Empirical Evidence," MPRA Paper 15905, University Library of Munich, Germany.
    4. Stanley, H.E. & Amaral, L.A.N. & Gabaix, X. & Gopikrishnan, P. & Plerou, V., 2001. "Similarities and differences between physics and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 1-15.
    5. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    6. Scafetta, N & Griffin, L & West, B.J, 2003. "Hölder exponent spectra for human gait," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 328(3), pages 561-583.
    7. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.
    8. Adlai Fisher & Laurent Calvet & Benoit Mandelbrot, 1997. "Multifractality of Deutschemark/US Dollar Exchange Rates," Cowles Foundation Discussion Papers 1166, Cowles Foundation for Research in Economics, Yale University.
    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. Cristescu, C.P. & Stan, C. & Scarlat, E.I., 2009. "The dynamics of exchange rate time series and the chaos game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4845-4855.
    2. Benbachir, Saâd & El Alaoui, Marwane, 2011. "A Multifractal Detrended Fluctuation Analysis of the Moroccan Stock Exchange," MPRA Paper 49003, University Library of Munich, Germany.
    3. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    4. Cezar Scarlat & Eugen I. Scarlat, 2007. "Theoretical Aspects of the Economic Transition: The Case of Romania," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 5(4), pages 307-331.
    5. Trenca Ioan & Plesoianu Anita & Capusan Razvan, 2012. "Multifractal Structure Of Central And Eastern European Foreign Exchange Markets," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 784-790, July.
    6. Cristescu, Constantin P. & Stan, Cristina & Scarlat, Eugen I. & Minea, Teofil & Cristescu, Cristina M., 2012. "Parameter motivated mutual correlation analysis: Application to the study of currency exchange rates based on intermittency parameter and Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2623-2635.
    7. Stan, Cristina & Marmureanu, Luminita & Marin, Cristina & Cristescu, Constantin P., 2020. "Investigation of multifractal cross-correlation surfaces of Hurst exponents for some atmospheric pollutants," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

    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. Todd Zorick & Mark A Mandelkern, 2013. "Multifractal Detrended Fluctuation Analysis of Human EEG: Preliminary Investigation and Comparison with the Wavelet Transform Modulus Maxima Technique," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
    2. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    3. Hallam, Mark & Olmo, Jose, 2014. "Forecasting daily return densities from intraday data: A multifractal approach," International Journal of Forecasting, Elsevier, vol. 30(4), pages 863-881.
    4. Zunino, Luciano & Figliola, Alejandra & Tabak, Benjamin M. & Pérez, Darío G. & Garavaglia, Mario & Rosso, Osvaldo A., 2009. "Multifractal structure in Latin-American market indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2331-2340.
    5. Mulligan, Robert F., 2004. "Fractal analysis of highly volatile markets: an application to technology equities," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(1), pages 155-179, February.
    6. Aslam, Faheem & Aziz, Saqib & Nguyen, Duc Khuong & Mughal, Khurrum S. & Khan, Maaz, 2020. "On the efficiency of foreign exchange markets in times of the COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    7. Thomas Lux, 2004. "Detecting Multifractal Properties In Asset Returns: The Failure Of The "Scaling Estimator"," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 481-491.
    8. Onali, Enrico & Goddard, John, 2011. "Are European equity markets efficient? New evidence from fractal analysis," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 59-67, April.
    9. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
    10. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    11. Makowiec, Danuta & Dudkowska, Aleksandra & Gała̧ska, Rafał & Rynkiewicz, Andrzej, 2009. "Multifractal estimates of monofractality in RR-heart series in power spectrum ranges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3486-3502.
    12. Lee, Hojin & Chang, Woojin, 2015. "Multifractal regime detecting method for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 117-129.
    13. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    14. Brandi, Giuseppe & Di Matteo, T., 2022. "Multiscaling and rough volatility: An empirical investigation," International Review of Financial Analysis, Elsevier, vol. 84(C).
    15. Suárez-García, Pablo & Gómez-Ullate, David, 2014. "Multifractality and long memory of a financial index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 226-234.
    16. Bhardwaj, Shivam & Chandrasekhar, E. & Seemala, Gopi K. & Gadre, Vikram M., 2020. "Characterization of ionospheric total electron content data using wavelet-based multifractal formalism," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    17. Eisler, Z. & Kertész, J., 2004. "Multifractal model of asset returns with leverage effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 603-622.
    18. Arshad, Shaista & Rizvi, Syed Aun R. & Haroon, Omair, 2020. "Impact of Brexit vote on the London stock exchange: A sectorial analysis of its volatility and efficiency," Finance Research Letters, Elsevier, vol. 34(C).
    19. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Casado Belmonte, M.P. & Trinidad Segovia, J.E., 2020. "A note on power-law cross-correlated processes," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    20. Segnon Mawuli & Wilfling Bernd & Lau Chi Keung & Gupta Rangan, 2022. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 73-98, February.

    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:eee:phsmap:v:379:y:2007:i:1:p:188-198. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.