Comovement of Exchange Rates: A Wavelet Analysis

Abstract

In this article we investigate the behavior of exchange rates in Central and Eastern European countries. The results strongly indicate that interactions between exchange rates have different characteristics at different timescales. Our results show that CEE exchange rates are nearly perfectly integrated in the short and medium run, since the returns obtained in any of the CEE foreign exchange market can almost be explained by the overall performance in the other CEE markets. The discrepancies between CEE exchange rates are small, but increase within three to six months and that means in the long run the integration of foreign exchange markets is weak.

Interest Rate and Exchange Rate Volatility Spillovers: Multiscale Perspective of Monetary Policy Transmission in Ghana

“…where, and are the constant terms of the system of equation; and denote estimated coefficients; m is the optimal lag length based on the Schwarz Information Criterion (BIC) 6 ; and represent errors terms from the VAR model.…”

“…where, m is an integer which represents the forecasting horizon. For the lag vectors and , given , we test for conditional independence using determinate number of lags, and based on a null hypothesis of: (9) Considering that the null hypothesis of Granger non-causality is a claim about the invariant distribution of -dimensional vector , where for the lead vector , the time index is dropped and simply written 6 In determining the optimal lag length, we set the lag number to 20. 7 The DP test is a modified version of the widely used HJ test of Hiemstra and Jones (1994), while the latter is also an improved version of the maiden nonparametric test by Baek and Brock (1992).…”

The Comovement of Exchange Rates and Stock Markets in Central and Eastern Europe

“…Bubák, et al [33] explore the dynamics of volatility transmission between Central European currencies and the EUR/USD and find evidence of statistically significant intra-regional volatility spillovers among the CEE foreign exchange markets, which tend to increase in periods that are characterized by market uncertainty. Andrieş, et al [34] investigate the co-movement of exchange rates in the CEE countries (Czech koruna, Hungarian forint, Lithuanian litas, Latvian lats, Polish zloty, and Romanian leu) against the euro for the 1999-2013 period, which revealed that interactions between them have different characteristics at different timescales, i.e., in the short and medium run the exchange rates are integrated, while the integration is weak in the long run. Kadlčáková and Komárek [35] examine the contagion phenomenon in the foreign exchange markets of three Central European countries (Hungary, the Czech Republic, and Poland) and the euro area, as the occurrence of extreme events taking place in different countries simultaneously.…”

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“…Figure 1 showcases the correlation coefficients among the sample indices that show high degree of relationship. Linear correlation fails to map the nonlinear dynamics in the data thus they may be interpreted cautiously (Andrieş, Ihnatov, & Tiwari, 2016). Thus, to captivate the correlation subtleties over the study period the 12-months rolling correlations are mapped in Figure 2.…”

“…1. For a detailed discussion on methodology refer (Andrieş et al, 2016;Ko & Lee, 2015;Kumar Tiwari, Billah Dar, Bhanja, & Shah, 2013;Vacha & Barunik, 2012). 2.…”