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Does news matter in China’s foreign exchange market? Chinese RMB volatility and public information arrivals

Author

Listed:
  • Ho, Kin-Yip
  • Shi, Yanlin
  • Zhang, Zhaoyong

Abstract

This paper examines the impact of public information flows on the volatility of the bilateral Chinese Renminbi–US dollar (RMB–USD) exchange rates in the spot, non-deliverable forward (NDF) and futures markets. By using the comprehensive RavenPack Dow Jones News Analytics database that captures Chinese and US macroeconomic news releases and their sentiment scores at high frequencies, we investigate the circumstances in which public news sentiment is related to the volatility of the above exchange rates. To account for the possibility of different volatility regimes in the RMB–USD volatility, a two-state Regime-Switching EGARCH-in-mean (RS-EGARCH-M) model that incorporates the effects of news sentiment is proposed. Our model suggests that news sentiment has a greater impact on reducing volatility persistence in the low-volatility regime (calm state) for all the NDF and futures exchange rates; in contrast, the impact is greater in the high-volatility regime (turbulent state) for the spot rate. Furthermore, depending on the news sources and sentiment, the marginal effects of news on these exchange rates can vary significantly. In particular, compared with the USD news releases, the RMB news releases have a stronger influence on the RMB–USD volatility. Moreover, the impact of negative news sentiment is greater than that of positive news sentiment. However, the effects of RMB–USD volatility on contemporaneous returns are mostly insignificant. Our RS-EGARCH-M model indicates that the estimated smoothing probability of the RMB–USD spot rate can produce consistent identification of the different economic states arising from changes in the macroeconomic and exchange rate policies of the Chinese government. These findings have important implications for China’s exchange rate regime and the process of RMB internationalization.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reveco:v:52:y:2017:i:c:p:302-321
    DOI: 10.1016/j.iref.2017.01.016
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    Cited by:

    1. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2020. "News and return volatility of Chinese bank stocks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1095-1105.
    2. Keddad, Benjamin & Sato, Kiyotaka, 2022. "The influence of the renminbi and its macroeconomic determinants: A new Chinese monetary order in Asia?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    3. Chunming Shen, 2022. "Digital RMB, RMB Internationalization and Sustainable Development of the International Monetary System," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    4. Shahzad, Syed Jawad Hussain & Kyei, Clement Kweku & Gupta, Rangan & Olson, Eric, 2021. "Investor sentiment and dollar-pound exchange rate returns: Evidence from over a century of data using a cross-quantilogram approach," Finance Research Letters, Elsevier, vol. 38(C).
    5. Tamgac, Unay, 2021. "Emerging market exchange rates during quantitative tapering: The effect of US and domestic news," Research in International Business and Finance, Elsevier, vol. 57(C).
    6. Feng, Lingbing & Fu, Tong & Shi, Yanlin, 2022. "How does news sentiment affect the states of Japanese stock return volatility?," International Review of Financial Analysis, Elsevier, vol. 84(C).
    7. Ahmad, Wasim & Prakash, Ravi & Uddin, Gazi Salah & Chahal, Rishman Jot Kaur & Rahman, Md. Lutfur & Dutta, Anupam, 2020. "On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?," Energy Economics, Elsevier, vol. 91(C).
    8. 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.
    9. Asger Lunde & Miha Torkar, 2020. "Including news data in forecasting macro economic performance of China," Computational Management Science, Springer, vol. 17(4), pages 585-611, December.
    10. Asadi, Mehrad & Roubaud, David & Tiwari, Aviral Kumar, 2022. "Volatility spillovers amid crude oil, natural gas, coal, stock, and currency markets in the US and China based on time and frequency domain connectedness," Energy Economics, Elsevier, vol. 109(C).
    11. Xiaoyi Shen & Albert K. Tsui & Zhaoyong Zhang, 2019. "Volatility Timing in CPF Investment Funds in Singapore: Do They Outperform Non-CPF Funds?," Risks, MDPI, vol. 7(4), pages 1-16, October.
    12. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    13. Junru Zhang & Hadrian Geri Djajadikerta & Zhaoyong Zhang, 2018. "Does Sustainability Engagement Affect Stock Return Volatility? Evidence from the Chinese Financial Market," Sustainability, MDPI, vol. 10(10), pages 1-21, September.
    14. Chi-Wei Su & Xu-Yu Cai & Ran Tao, 2020. "Can Stock Investor Sentiment Be Contagious in China?," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    15. Usha Rekha Chinthapalli, 2021. "A Comparative Analysis on Probability of Volatility Clusters on Cryptocurrencies, and FOREX Currencies," JRFM, MDPI, vol. 14(7), pages 1-23, July.
    16. Jin, Y. & Jin, S., 2018. "The Heterogeneous Impact of Exchange Rate Volatility on Agricultural Export: Evidence from Chinese Food Firm-level Data," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277197, International Association of Agricultural Economists.
    17. Zhou, Xinmiao & Zhang, Junru & Zhang, Zhaoyong, 2021. "How does news flow affect cross-market volatility spillovers? Evidence from China’s stock index futures and spot markets," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 196-213.
    18. 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.
    19. 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).
    20. Mingming Li & Fengming Qin & Zhaoyong Zhang, 2021. "Short-Term Capital Flows, Exchange Rate Expectation and Currency Internationalization: Evidence from China," JRFM, MDPI, vol. 14(5), pages 1-15, May.
    21. Qi, Jianhong & Liu, Hui & Zhang, Zhaoyong, 2021. "Exchange rate uncertainty and the timing of Chinese Outward Direct Investment," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1193-1204.
    22. Zhang, Junru & Zhang, Zhaoyong, 2021. "CSR, Media and Stock Illiquidity: Evidence from Chinese Listed Financial Firms," Finance Research Letters, Elsevier, vol. 41(C).

    More about this item

    Keywords

    Chinese currency; Exchange rate; News sentiment; Regime-switching;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • O24 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Trade Policy; Factor Movement; Foreign Exchange Policy
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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