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Incorporating the RMB internationalization effect into its exchange rate volatility forecasting

Author

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  • Ding, Shusheng
  • Cui, Tianxiang
  • Zhang, Yongmin

Abstract

Recently, the Chinese government has launched the renminbi (RMB) internationalization policy as an impetus to foster China’s global economic integration. The RMB internationalization effect on China’s economy and the RMB exchange rate has attracted massive attention in recent financial research. In this paper, we adopt a genetic programming (GP) method to generate new RMB exchange rate volatility forecasting models incorporating the RMB internationalization effect. Our models are proved to have significant accuracy improvement in predicting both RMB/US dollar and RMB/euro exchange rate volatilities, compared with standard GARCH volatility models, which are incapable of capturing the RMB internationalization effect. Furthermore, our models display salient practical implications for policy makers to formulate monetary policies and currency traders to design effective trading strategies.

Suggested Citation

  • Ding, Shusheng & Cui, Tianxiang & Zhang, Yongmin, 2020. "Incorporating the RMB internationalization effect into its exchange rate volatility forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
  • Handle: RePEc:eee:ecofin:v:54:y:2020:i:c:s1062940819302840
    DOI: 10.1016/j.najef.2019.101103
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    1. Cong Wang & Xue Wang, 2018. "The Macroeconomic Effects of RMB Internationalization: The Perspective of Overseas Circulation," International Symposia in Economic Theory and Econometrics, in: Banking and Finance Issues in Emerging Markets, volume 25, pages 31-50, Emerald Group Publishing Limited.
    2. Frenkel, Jacob A, 1976. " A Monetary Approach to the Exchange Rate: Doctrinal Aspects and Empirical Evidence," Scandinavian Journal of Economics, Wiley Blackwell, vol. 78(2), pages 200-224.
    3. Della Corte, Pasquale & Ramadorai, Tarun & Sarno, Lucio, 2016. "Volatility risk premia and exchange rate predictability," Journal of Financial Economics, Elsevier, vol. 120(1), pages 21-40.
    4. Liu, Li-Gang & Pauwels, Laurent L., 2012. "Do external political pressures affect the Renminbi exchange rate?," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1800-1818.
    5. Jorion, Philippe, 1995. "Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-528, June.
    6. Du, Julan & Zhang, Yifei, 2018. "Does One Belt One Road initiative promote Chinese overseas direct investment?," China Economic Review, Elsevier, vol. 47(C), pages 189-205.
    7. Jorion, Philippe, 1991. "The Pricing of Exchange Rate Risk in the Stock Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 26(3), pages 363-376, September.
    8. Paul R. Krugman, 1991. "Target Zones and Exchange Rate Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(3), pages 669-682.
    9. Funke, Michael & Shu, Chang & Cheng, Xiaoqiang & Eraslan, Sercan, 2015. "Assessing the CNH–CNY pricing differential: Role of fundamentals, contagion and policy," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 245-262.
    10. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    11. Bailey, Warren & Chung, Y. Peter, 1995. "Exchange Rate Fluctuations, Political Risk, and Stock Returns: Some Evidence from an Emerging Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(4), pages 541-561, December.
    12. Alan S. Blinder, 1996. "The Role of the Dollar as an International Currency," Eastern Economic Journal, Eastern Economic Association, vol. 22(2), pages 127-136, Spring.
    13. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    14. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2017. "Does news matter in China’s foreign exchange market? Chinese RMB volatility and public information arrivals," International Review of Economics & Finance, Elsevier, vol. 52(C), pages 302-321.
    15. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    16. Yinghua Ren & Lin Chen & Ye Liu, 2018. "The Onshore–Offshore Exchange Rate Differential, Interest Rate Spreads, and Internationalization: Evidence from the Hong Kong Offshore Renminbi Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(13), pages 3100-3116, October.
    17. Asteriou, Dimitrios & Masatci, Kaan & Pılbeam, Keith, 2016. "Exchange rate volatility and international trade: International evidence from the MINT countries," Economic Modelling, Elsevier, vol. 58(C), pages 133-140.
    18. Yang, Lijian, 2006. "A semiparametric GARCH model for foreign exchange volatility," Journal of Econometrics, Elsevier, vol. 130(2), pages 365-384, February.
    19. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    20. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Nicola, 2015. "Exchange rate uncertainty and international portfolio flows: A multivariate GARCH-in-mean approach," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 70-92.
    21. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2018. "Public information arrival, price discovery and dynamic correlations in the Chinese renminbi markets," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 168-186.
    22. Grier, Kevin B. & Smallwood, Aaron D., 2013. "Exchange rate shocks and trade: A multivariate GARCH-M approach," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 282-305.
    23. Fengming Qin & Junru Zhang & Zhaoyong Zhang, 2018. "RMB Exchange Rates and Volatility Spillover across Financial Markets in China and Japan," Risks, MDPI, vol. 6(4), pages 1-26, October.
    24. Hong, Eun Pyo, 1991. "The autocorrelation structure for the GARCH-M process," Economics Letters, Elsevier, vol. 37(2), pages 129-132, October.
    25. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
    26. Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
    27. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
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    Cited by:

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    4. Yang‐Chao Wang & Jui‐Jung Tsai & Shushu Li & Yiying Huang, 2023. "The impacts of RMB internationalization on onshore and offshore RMB markets," International Review of Finance, International Review of Finance Ltd., vol. 23(3), pages 502-523, September.
    5. Zhang, Yongmin & Wang, Ruizhi, 2022. "COVID-19 impact on commodity futures volatilities," Finance Research Letters, Elsevier, vol. 47(PA).
    6. Chunming Shen, 2022. "Digital RMB, RMB Internationalization and Sustainable Development of the International Monetary System," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    7. Anwer, Zaheer & Khan, Ashraf & Kabir Hassan, M. & Rashid, Mamunur, 2022. "Does the regional proximity lead to exchange rate spillover?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    8. Cui, Tianxiang & Ding, Shusheng & Jin, Huan & Zhang, Yongmin, 2023. "Portfolio constructions in cryptocurrency market: A CVaR-based deep reinforcement learning approach," Economic Modelling, Elsevier, vol. 119(C).

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    More about this item

    Keywords

    RMB internationalization; Exchange rate; Volatility forecasting; Genetic programming;
    All these keywords.

    JEL classification:

    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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