Exchange Rate Synchronization for a Set of Currencies from Different Monetary Areas
DOI:
https://doi.org/10.47743/saeb-2022-0013Keywords:
Exchange rate, co-movements, Hodrick-Prescott filter, wavelets, synchronizationAbstract
The degree of co-movement between currencies remains an important subject for international trade and monetary integration across countries. However, the economic literature has given limited answers about the directional relationships among currencies, and whether they have a leader or a driver. Using the Hodrick-Prescott filter and the wavelet methodology, this paper analyzes exchange rate synchronization for a set of twelve currencies belonging to different monetary areas covering the period between January 1980 and July 2020. The empirical results reveal that: i) the U.S. dollar still plays an essential role as a foreign exchange anchor; ii) the euro shows an out-of-phase relationship with the vast majority of currencies, including with the other European currencies; iii) the British pound seems to have departed significantly from the European single currency; iv) the Brazilian real leads the Chinese yuan for most of the sample, and both currencies record great dissimilarities with the other currencies; v) in the absence of short-term foreign exchange market frictions, average bilateral distances between currencies are smaller, and vi) during the international financial crisis, exchange rates became more synchronized.
References
Aguiar-Conraria, L., Azevedo, N., & Soares, M. J. (2008). Using wavelets to decompose the time-frequency effects of monetary policy. Physica A, 387(12), 2863-2878. http://dx.doi.org/10.1016/j.physa.2008.01.063
Aguiar-Conraria, L., Martins, M. M., & Soares, M. J. (2013). Synchronization of Economic Sentiment Cycles in the Euro Area: A time-frequency analysis. Journal of Common Market Studies, 51(3), 377-398. http://dx.doi.org/10.1111/j.1468-5965.2012.02315.x
Aguiar-Conraria, L., Martins, M. M., & Soares, M. J. (2018). Estimating the Taylor rule in the time-frequency domain. Journal of Macroeconomics, 57, 122-137. http://dx.doi.org/10.1016/j.jmacro.2018.05.008
Aguiar-Conraria, L., & Soares, M. J. (2011). Business cycle synchronization and the Euro: A wavelet analysis. Journal of Macroeconomics, 33(3), 477-489. http://dx.doi.org/10.1016/j.jmacro.2011.02.005
Aguiar-Conraria, L., & Soares, M. J. (2014). The continuous wavelet transform: Moving beyond uni- and bivariate analysis. Journal of Economic Surveys, 28(2), 344-375. http://dx.doi.org/10.1111/joes.12012
Aloui, C., Hkiri, B., & Nguyen, D. K. (2016). Real growth co-movements and business cycle synchronization in the GCC countries: Evidence from time-frequency analysis. Economic Modelling, 52, 322-331. http://dx.doi.org/10.1016/j.econmod.2015.09.009
Andries, A. M., Ihnatov, I., & Tiwari, A. K. (2014). Analyzing time-frequency relationship between interest rate, stock price and exchange rate through continuous wavelet. Economic Modelling, 41, 227-238. http://dx.doi.org/10.1016/j.econmod.2014.05.013
Antonakakis, N. (2012). Exchange return co-movements and volatility spillovers before and after the introduction of euro. Journal of International Financial Markets, Institutions and Money, 22(5), 1091-1109. http://dx.doi.org/10.1016/j.intfin.2012.05.009
Bento, J. A., & Duarte, A. P. (2020). Brexit: An Exploratory Analysis of the Macroeconomic Effects on the British Economy. Scientific Annals of Economics and Business, 67(Special Issue), 69-85. http://dx.doi.org/10.47743/saeb-2020-0027
BIS. (2019). Triennial Central Bank Survey: Foreign Exchange Turnover in April 2019. Monetary and Economic Department.
Boero, G., Silvapulle, P., & Tursunalieva, A. (2011). Modelling the bivariate dependence structure of exchange rates before and after the introduction of the Euro: A semi-parametric approach. International Journal of Finance & Economics, 16(4), 357-374. http://dx.doi.org/10.1002/ijfe.434
Canova, F. (1998). Detrending and business cycle facts: A user’s guide. Journal of Monetary Economics, 41(3), 533-540. http://dx.doi.org/10.1016/S0304-3932(98)00008-7
Chen, M. P., Chen, W. Y., & Tseng, T. C. (2017). Co-movements of returns in the health care sectors from the US, UK, and Germany stock markets: Evidence from the continuous wavelet analyses. International Review of Economics & Finance, 49, 484-498. http://dx.doi.org/10.1016/j.iref.2017.02.009
Chitu, L., Eichengreen, B., & Mehl, A. (2014). When did the dollar overtake sterling as the leading international currency? Evidence from the bond markets. Journal of Development Economics, 111(C), 225-245. http://dx.doi.org/10.1016/j.jdeveco.2013.09.008
da Silva, K. L., & Fernandes, M. (2018). Estratégias de Momento no Mercado Cambial. Revista Brasileira de Finanças, 16(1), 39-80.
Dabrowski, M. (2020). Can the Euro Dethrone the US Dollar as the Dominant Global Currency? Not so Soon, if Ever. Monetary Dialogue Papers, European Parliament.
Dickey, D., & Fuller, W. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427-431. http://dx.doi.org/10.2307/2286348
Duarte, A. P. (2015). O Sistema Monetário Internacional: Uma Perspetiva Histórico-Económica: Conjuntura Actual Editora.
Duarte, A. P., & Silva, N. B. (2020). Sincronização dos ciclos económicos em alguns países da União Europeia: Uma análise de onduletas. In A. P. Duarte, M. Simões, P. Bação, & R. Martins (Eds.), Estudos de Homenagem a João Sousa Andrade (pp. 149-172): Almedina.
Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339-350. http://dx.doi.org/10.1198/073500102288618487
Feng, X., Hu, H., & Wang, X. (2010). The evolutionary synchronization of the exchange rate system in ASEAN+6. Physica A, 389(24), 5785-5793. http://dx.doi.org/10.1016/j.physa.2010.09.011
Goldberg, L. S., & Tille, C. (2006). The Internationalization of the Dollar and Trade Balance Adjustment. Occasional Paper, 71.
Goupillaud, P., Grossmann, A., & Morlet, J. (1984). Cycle-octave and related transforms in seismic signal analysis. Geoexploration, 23, 85-102. http://dx.doi.org/10.1016/0016-7142(84)90025-5
Grossmann, A., & Morlet, J. (1984). Decomposition of Hardy Functions into Square Integrable Wavelets of Constant Shape. SIAM Journal on Mathematical Analysis, 15, 723-736. http://dx.doi.org/10.1137/0515056
Hodrick, R., & Prescott, E. (1997). Postwar U. S. Business Cycles: An Empirical Investigation. Journal of Money, Credit and Banking, 29(1), 1-16. http://dx.doi.org/10.2307/2953682
Horobet, A., & Ilie, L. (2009). On the Exchange Rate Risk Contribution To the Performance of International Investments: The Case of Romania. Review of Economic and Business Studies, 3(SI), 57-83.
Inagaki, K. (2007). Testing for volatility spillover between the British pound and the euro. Research in International Business and Finance, 21(2), 161-174. http://dx.doi.org/10.1016/j.ribaf.2006.03.006
Jammazi, R. (2012). Cross dynamics of oil-stock interactions: A redundant wavelet analysis. Energy, 44(1), 750-777. http://dx.doi.org/10.1016/j.energy.2012.05.017
Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1-3), 159-178. http://dx.doi.org/10.1016/0304-4076(92)90104-Y
Maravall, A., & del Río, A. (2001). Time Aggregation and the Hodrick-Prescott Filter. Banco de España. Banco de España. Documento de Trabajo, 0108, 1-44.
McMillan, D. G., & Speight, A. E. (2010). Return and volatility spillovers in three euro exchange rates. Journal of Economics and Business, 62(2), 79-93. http://dx.doi.org/10.1016/j.jeconbus.2009.08.003
Nikkinen, J., Pynnönen, S., Ranta, M., & Vähämaa, S. (2011). Cross-dynamics of exchange rate expectations: A wavelet analysis. International Journal of Finance & Economics, 16(3), 205-217. http://dx.doi.org/10.1002/ijfe.423
Nikkinen, J., Sahlström, P., & Vähämaa, S. (2006). Implied volatility linkages among major European currencies. Journal of International Financial Markets, Institutions and Money, 16(2), 87-103. http://dx.doi.org/10.1016/j.intfin.2004.12.007
Ojo, M. O., Aguiar-Conraria, L., & Soares, M. J. (2020). A timefrequency analysis of the Canadian macroeconomy and the yield curve. Empirical Economics, 58(5), 2333-2351. http://dx.doi.org/10.1007/s00181-018-1580-y
Orlowski, L. T. (2016). Co-movements of non-Euro EU currencies with the Euro. International Review of Economics & Finance, 45, 376-383. http://dx.doi.org/10.1016/j.iref.2016.07.001
Pérez-Rodríguez, J. V. (2006). The Euro and other major currencies oating against the U.S. dollar. Atlantic Economic Journal, 34(4), 367-384. http://dx.doi.org/10.1007/s11293-006-9042-x
Rabanal, P., & Rubio-Ramírez, J. F. (2015). Can international macroeconomic models explain low-frequency movements of real exchange rates? Journal of International Economics, 96(1), 199-211. http://dx.doi.org/10.1016/j.jinteco.2015.01.009
Raihan, S., Wen, Y., & Zeng, B. (2005). Wavelet: a new tool for business cycle analysis. Federal Reserve Bank of St. Louis Working Paper, 2005-050.
Ravn, M. O., & Uhlig, H. (2002). On adjusting the Hodrick-Prescott filter for the frequency of observations. The Review of Economics and Statistics, 84(2), 371-376. http://dx.doi.org/10.1162/003465302317411604
Rua, A. (2012). Wavelets in Economics. Banco de Portugal. Boletim Económico, 6, 71-79.
Seghezza, E., & Morelli, P. (2018). Rule of law and balance of power sustain US dollar preeminence. Journal of Policy Modeling, 40(1), 16-36. http://dx.doi.org/10.1016/j.jpolmod.2017.09.004
Tamakoshi, G., & Hamori, S. (2014). Co-movements among major European exchange rates: A multivariate time-varying asymmetric approach. International Review of Economics & Finance, 31, 105-113. http://dx.doi.org/10.1016/j.iref.2014.01.016
Tiwari, A. K. (2013). Oil prices and the macroeconomy reconsideration for Germany: Using continuous wavelet. Economic Modelling, 30(1), 636-642. http://dx.doi.org/10.1016/j.econmod.2012.11.003
Tiwari, A. K., & Albulescu, C. T. (2016). Oil price and exchange rate in India: Fresh evidence from continuous wavelet approach and asymmetric, multi-horizon Granger-causality tests. Applied Energy, 179, 272-283. http://dx.doi.org/10.1016/j.apenergy.2016.06.139
Torrence, C., & Gilbert, P. C. (1998). A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society, 137(2), 87-92.
Truman, E. M. (2012). The International Monetary System of “Nonsystem”? In C. F. Bergsten & C. R. Henning (Eds.), Global Economics in Extraordinary Times: Essays in Honor of John Williamson (pp. 27-52): Peterson Institute for International Economics.
Wang, J. X., & Yang, M. (2009). Asymmetric volatility in the foreign exchange markets. Journal of International Financial Markets, Institutions and Money, 19(4), 597-615. http://dx.doi.org/10.1016/j.intfin.2008.10.001
Williamson, J. (1976). The benefits and costs of an international monetary nonsystem. In E. M. a. Bernstein (Ed.), Reflections on Jamaica (pp. 54-59): Princeton University Press.
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