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Relationship between onshore and offshore renminbi exchange markets: Evidence from multiscale cross-correlation and nonlinear causal effect analyses

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Abstract Through multifractal detrended moving-average cross-correlation analysis (MF-X-DMA) and partial moving-average cross-correlation coefficient analysis (PDMCA), this paper studies power-law cross-correlations between renminbi (RMB) onshore and offshore markets (2013–2018). The interaction… Click to show full abstract

Abstract Through multifractal detrended moving-average cross-correlation analysis (MF-X-DMA) and partial moving-average cross-correlation coefficient analysis (PDMCA), this paper studies power-law cross-correlations between renminbi (RMB) onshore and offshore markets (2013–2018). The interaction between CNY and CNH market pairs was examined with attention to how the floating exchange rate regime reform of August 11, 2015 affects their interactions. The obtained results suggest that net power-law cross-correlations exist between the CNY and CNH exchange markets (with influences of autocorrelation, interest rate difference, US Dollar, and Oil signals removed) and that the August 11, 2015 (referred to as “811”) exchange reform significantly affects the trend of multiscale cross-correlation coefficient curves. This study also verifies that the risk of offshore RMB markets in Europe and the UK is larger than in Hong Kong and the US when facing a large shock. The nonlinear causal effect analysis reveals that asymmetric bidirectional nonlinear causality exists between any market pair, and the degree of asymmetry appears to have declined after the 811 exchange rate regime reform. For the offshore RMB markets in the US, Europe, and UK, there is evidence of stronger causality running from the CNH to CNY than vice versa, which implies that the foreign impulses have had an influence on the domestic market, and the floating exchange rate reform effectively improves the RMB exchange rate formation mechanism.

Keywords: onshore offshore; exchange; rate; cross correlation

Journal Title: Physica A: Statistical Mechanics and its Applications
Year Published: 2019

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