IDEAS home Printed from https://ideas.repec.org/p/arx/papers/cond-mat-0103033.html
   My bibliography  Save this paper

False EUR exchange rates vs. DKK, CHF, JPY and USD. What is a strong currency?

Author

Listed:
  • K. Ivanova
  • M. Ausloos

Abstract

The Euro (EUR) has been a currency introduced by the European Community on Jan. 01, 1999. This implies eleven countries of the European Union which have been found to meet the five requirements of the Maastricht convergence criteria. In order to test EUR behavior and understand various features, we have extrapolated the EUR backwards and therefore have obtained a {\it false euro} (FEUR) dating back to 1993. We have derived the exchange rates of the FEUR with respect to several currencies of interest not belonging to the EUR, i.e., Danish Kroner (DKK), Swiss Franc (CHF), Japanese Yen (JPY) and U.S. Dollar (USD). We have first observed the distribution of fluctuations of the exchange rates. Within the {\it Detrended Fluctuation Analysis} (DFA) statistical method, we have calculated the power law behavior describing the root-mean-square deviation of these exchange rate fluctuations as a function of time, displaying in particular the JPY exchange rate case. In order to estimate the role of each currency making the EUR and therefore in view of identifying whether some of them mostly influences its behavior, we have compared the time-dependent exponent of the exchange rate fluctuations for EUR with that for the currencies that form the EUR. We have found that the German Mark (DEM) has been leading the fluctuations of EUR/JPY exchange rates, and Portuguese Escudo (PTE) is the farthest away currency from this point of view.

Suggested Citation

  • K. Ivanova & M. Ausloos, 2001. "False EUR exchange rates vs. DKK, CHF, JPY and USD. What is a strong currency?," Papers cond-mat/0103033, arXiv.org.
    • Handle: RePEc:arx:papers:cond-mat/0103033
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/cond-mat/0103033
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M. Ausloos & K. Ivanova, 2001. "False Euro (FEUR) exchange rate correlated behaviors and investment strategy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 20(4), pages 537-541, April.
    2. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Scaling properties of foreign exchange volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 249-266.
    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. T. Di Matteo & T. Aste & M. M. Dacorogna, 2003. "Using the Scaling Analysis to Characterize Financial Markets," Papers cond-mat/0302434, arXiv.org.
    2. Wang, Dong-Hua & Yu, Xiao-Wen & Suo, Yuan-Yuan, 2012. "Statistical properties of the yuan exchange rate index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3503-3512.
    3. Wang, Gang-Jin & Xie, Chi, 2013. "Cross-correlations between Renminbi and four major currencies in the Renminbi currency basket," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1418-1428.
    4. Raul Matsushita & Andre Santos & Iram Gleria & Annibal Figueiredo & Sergio Da Silva, 2005. "Are Pound and Euro the Same Currency?," International Finance 0505002, University Library of Munich, Germany.
    5. Matsushita, Raul & Gleria, Iram & Figueiredo, Annibal & Da Silva, Sergio, 2007. "Are Pound and Euro the Same Currency? - Updated," MPRA Paper 1981, University Library of Munich, Germany.
    6. Marcel Ausloos, 2012. "Econophysics in Belgium. The first (?) 15 years," Papers 1212.1946, arXiv.org.
    7. Sitabhra Sinha & Uday Kovur, 2013. "Uncovering the network structure of the world currency market: Cross-correlations in the fluctuations of daily exchange rates," Papers 1305.0239, arXiv.org.
    8. Celeste, Valerio & Corbet, Shaen & Gurdgiev, Constantin, 2020. "Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 310-324.
    9. Boilard, J.-F. & Kanazawa, K. & Takayasu, H. & Takayasu, M., 2018. "Empirical scaling relations of market event rates in foreign currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1152-1161.
    10. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(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. T. Di Matteo & T. Aste & M. M. Dacorogna, 2003. "Using the Scaling Analysis to Characterize Financial Markets," Papers cond-mat/0302434, arXiv.org.
    2. Matsushita, Raul & Gleria, Iram & Figueiredo, Annibal & Rathie, Pushpa & Da Silva, Sergio, 2004. "Exponentially damped Lévy flights, multiscaling, and exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 353-369.
    3. Wang, Dong-Hua & Yu, Xiao-Wen & Suo, Yuan-Yuan, 2012. "Statistical properties of the yuan exchange rate index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3503-3512.
    4. Muniandy, Sithi V. & Uning, Rosemary, 2006. "Characterization of exchange rate regimes based on scaling and correlation properties of volatility for ASEAN-5 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 585-598.
    5. In, Francis & Kim, Sangbae & Gençay, Ramazan, 2011. "Investment horizon effect on asset allocation between value and growth strategies," Economic Modelling, Elsevier, vol. 28(4), pages 1489-1497, July.
    6. Neeraj, & Panigrahi, Prasanta K., 2017. "Causality and correlations between BSE and NYSE indexes: A Janus faced relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 284-313.
    7. Muhammad Azmat Hayat & Huma Ghulam & Maryam Batool & Muhammad Zahid Naeem & Abdullah Ejaz & Cristi Spulbar & Ramona Birau, 2021. "Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    8. Chang, Lo-Bin & Geman, Stuart, 2013. "Empirical scaling laws and the aggregation of non-stationary data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5046-5052.
    9. Abid, Fathi & Kaffel, Bilel, 2018. "Time–frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1028-1045.
    10. Ftiti, Zied & Guesmi, Khaled & Abid, Ilyes, 2016. "Oil price and stock market co-movement: What can we learn from time-scale approaches?," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 266-280.
    11. Xu, Zhaoxia & Gençay, Ramazan, 2003. "Scaling, self-similarity and multifractality in FX markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 578-590.
    12. Sergio Da Silva, 2004. "International Finance, Levy Distributions, and the Econophysics of Exchange Rates," International Finance 0405018, University Library of Munich, Germany.
    13. Charalampos Basdekis & Apostolos Christopoulos & Ioannis Katsampoxakis & Vasileios Nastas, 2022. "The Impact of the Ukrainian War on Stock and Energy Markets: A Wavelet Coherence Analysis," Energies, MDPI, vol. 15(21), pages 1-15, November.
    14. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    15. Saumya Ranjan Dash & Debasish Maitra & Byomakesh Debata & Jitendra Mahakud, 2021. "Economic policy uncertainty and stock market liquidity: Evidence from G7 countries," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 611-626, June.
    16. Dewandaru, Ginanjar & Bacha, Obiyathulla Ismath & Masih, A. Mansur M. & Masih, Rumi, 2015. "Risk-return characteristics of Islamic equity indices: Multi-timescales analysis," Journal of Multinational Financial Management, Elsevier, vol. 29(C), pages 115-138.
    17. Joscha Beckmann & Theo Berger & Robert Czudaj, 2019. "Gold price dynamics and the role of uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 19(4), pages 663-681, April.
    18. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
    19. Gordon V. Chavez, 2019. "Dynamic tail inference with log-Laplace volatility," Papers 1901.02419, arXiv.org, revised Jul 2019.
    20. Souhir, Ben Amor & Heni, Boubaker & Lotfi, Belkacem, 2019. "Price risk and hedging strategies in Nord Pool electricity market evidence with sector indexes," Energy Economics, Elsevier, vol. 80(C), pages 635-655.

    More about this item

    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:arx:papers:cond-mat/0103033. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.