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Correlations Between Reconstructed EUR Exchange Rates vs. CHF, DKK, GBP, JPY and USD

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  • M. Ausloos
  • K. Ivanova

Abstract

On Jan. 1, 1999 the European Union introduced a common currency Euro ($EUR$), to become the legal currency in all eleven countries which form the $EUR$. In order to test the $EUR$ behavior and understand various features, the $EUR$ exchange rate is artificially extrapolated back to 1993 by a linear superposition of the exchange rates of the 11 currencies composing $EUR$ with respect to several currencies not belonging to the $EUR$, i.e. Swiss Franc ($CHF$), Danish Kroner ($DKK$), British Pound ($GBP$), Japanese Yen ($JPY$) and U.S. Dollar ($USD$) of interest for reasons given in the text. The distribution of fluctuations of the exchange rates is shown to be Gaussian for the central part of the distribution, and having fat tails for the large size fluctuations. Within the {\it Detrended Fluctuation Analysis} ($DFA$) statistical method we have obtained the power law behavior describing the root-mean-square deviation of the exchange rate fluctuations as a function of time. For the period between Jan. 1995 and Jan. 1999 we have compared the time-dependent exponent of these exchange rate fluctuations for $EUR$ and that of the 11 currencies which form the $EUR$. The German Mark ($DEM$) and the French Franc ($FRF$) have been the currencies primarily leading the fluctuations of the exchange rates, while Italian Lira ($ITL$) and ($PTE$) Portuguese Escudo are the less relevant currencies from this point of view. Technical considerations for the $EUR$ implementation are given as conclusions. The cases of exchange rates with $DKK$ appear quite different from the other four major currencies.

Suggested Citation

  • M. Ausloos & K. Ivanova, 2001. "Correlations Between Reconstructed EUR Exchange Rates vs. CHF, DKK, GBP, JPY and USD," Papers cond-mat/0104260, arXiv.org.
  • Handle: RePEc:arx:papers:cond-mat/0104260
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    1. J. MUYSKENS & C. de Neubourg, 1986. "Introduction," Discussion Papers (REL - Recherches Economiques de Louvain) 1986031, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
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    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. 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.

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