Abstract
For evaluating the influence of the Chinese renminbi (RMB) joining in the special drawing right (SDR) basket on RMB’s internationalization, the authors systemically study the risk spillover networks and examine the dynamic relationship of exchange rates among the SDR currencies including the US dollar (USD), European Union euro (EUR), Japanese yen (JPY) and British pound (GBP). The empirical results demonstrate that the USD takes a dominant position and holds the biggest risk spillover to other currencies, and the RMB’s inclusion to the SDR basket makes the risk spillover to get average, giving rise to the SDR currency system more stable to a certain degree. The inclusion of the RMB in the SDR not only can reduce the systematic risk of the SDR, but also has a certain impact on the international exchange rate markets. Nowadays, in front of the growing trade friction, more such researches could help to effectively deal with the currency disputes.
Similar content being viewed by others
References
Peter H and Steven W K, The effect of exchange rate uncertainty on the prices and volume of international trade, Journal of International Economics, 1978, 8(4): 483–511.
Abdur R C, Does exchange rate volatility depress trade flows? Evidence from error-correction models, The Review of Economics and Statistics, 1993, 75(4): 700–706.
Enrique G M, The terms of trade, the real exchange rate, and economic fluctuations, International Economic Review, 1995, 36(1): 101–137.
Eden H V, Bin L, Romyn G, et al, Natrex and determination of real exchange rate of RMB, Journal of Systems Science and Complexity, 2001, 14(4): 356–372.
Sun X, Li J, Tang L, et al., Identifying the risk-return tradeoff and exploring the dynamic risk exposure of country portfolio of the FSU’s oil economies, Economic Modelling, 2012, 29(6): 2494–2503.
Jose M C and Linda S G, Exchange rate pass-through into import prices, Review of Economics and Statistics, 2005, 87(4): 679–690.
Silvana T, On the trade impact of nominal exchange rate volatility, Journal of Development Economics, 2007, 82(2): 485–508.
Mohsen B O and Scott W H, Exchange rate volatility and trade flows: A review article, Journal of Economic Studies, 2007, 34(3): 211–255.
Jordi G and Tommaso M, Monetary policy and exchange rate volatility in a small open economy, The Review of Economic Studies, 2005, 72(3): 707–734.
Joshua A and Daniel R C, Real exchange rate and international reserves in an era of growing financial and trade integration, The Review of Economics and Statistics, 2008, 90(4): 812–815.
Gust C J, Leduc S, and Vigfusson R J, Trade integration, competition, and the decline in exchange-rate pass-through, Journal of Monetary Economics, 2010, 57(3): 309–324.
Zhang Z, Makin A J, and Bai Q, Yen internationalization and Japan’s international reserves, Economic Modelling, 2016, 52: 452–466.
Du J and Lai K K, Copula-based risk management models for multivariable RMB exchange rate in the process of RMB internationalization, Journal of Systems Science and Complexity, 2017, 30(3): 660–679.
Galagedera D U A and Kitamura Y, Effect of exchange rate return on volatility spill-over across trading regions, Japan & the World Economy, 2012, 24(4): 254–265.
Drehmann M and Tarashev N, Systemic importance: Some simple indicators, Bis Quarterly Review, 2011.
Upper C, Simulation methods to assess the danger of contagion in interbank markets, Journal of Financial Stability, 2011, 7(3): 111–125.
Lee S H, Systemic liquidity shortages and interbank network structures, Journal of Financial Stability, 2013, 9(1): 1–12.
Greenwood R, Landier A, and Thesmar D, Vulnerable banks, Journal of Financial Economics, 2015, 115(3): 471–485.
Meng Z, Jiang M, and Hu Q, Dynamic CVaR with multi-period risk problems, Journal of Systems Science and Complexity, 2011, 24(5): 907–918.
Nier E, Yang J, Yorulmazer T, et al, Network models and financial stability, Social Science Electronic Publishing, 2007, 31(6): 2033–2060.
Gai P and Kapadia S, Contagion in financial networks, Proceedings Mathematical Physical & Engineering Sciences, 2010, 466(2120): 2401–2423.
Pesaran B and Pesaran M H, Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash, Economic Modelling, 2010, 27(6): 1398–1416.
Diebold F X and Yilmaz K, Better to give than to receive: Predictive directional measurement of volatility spillovers, International Journal of Forecasting, 2012, 28(1): 57–66.
Diebold F X and Yilmaz K, On the network topology of variance decompositions: Measuring the connectedness of financial firms, Journal of Econometrics, 2011, 182(1): 119–134.
Yang Z and Zhou Y, Quantitative easing and volatility spillovers across countries and asset classes, Management Science, 2017, 63(2): 333–354.
Fan X, Fang Y, and Wang D, Systemic risk and systemically important financial institutions of China’s bank section-an analysis based on CCA and DAG, Journal of Financial Research, 2013, 11: 82–95.
Author information
Authors and Affiliations
Corresponding author
Additional information
This research was supported by the National Natural Science Foundation of China under Grant Nos. 71801213 and 71642006.
This paper was recommended for publication by Editor YANG Cuihong.
Rights and permissions
About this article
Cite this article
Zhang, B., Wang, S., Wei, Y. et al. Impact of the RMB Joining in the SDR Basket on Its Internationalization from the Perspective of Risk Spillover. J Syst Sci Complex 34, 339–350 (2021). https://doi.org/10.1007/s11424-020-9215-8
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11424-020-9215-8