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Forecasting Chinese industry return volatilities with RMB/USD exchange rate

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  • Dai, Zhifeng
  • Zhu, Huan
  • Dong, Xiaodi

Abstract

The purpose of this paper is to analyze whether the fluctuations of RMB/USD exchange rate can predict the Chinese industry return volatilities during post-financial crisis period. Our in-sample results show there is significant Granger causality from RMB/USD exchange rate fluctuations to China’s industry return volatilities. The out-of-sample results also indicate the RMB/USD exchange rate fluctuations extracts significantly useful information from the predictors. Further analysis about the energy industry shows that simple linear regression is sufficient for capturing predictive relationships between RMB/USD exchange rate fluctuations and energy industry volatility.

Suggested Citation

  • Dai, Zhifeng & Zhu, Huan & Dong, Xiaodi, 2020. "Forecasting Chinese industry return volatilities with RMB/USD exchange rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    • Handle: RePEc:eee:phsmap:v:539:y:2020:i:c:s0378437119316929
    DOI: 10.1016/j.physa.2019.122994
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    as
    1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    2. Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
    3. 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.
    4. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    5. Fenghua Wen & Jihong Xiao & Chuangxia Huang & Xiaohua Xia, 2018. "Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 319-334, January.
    6. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    7. Weixian Cai & Jian Chen & Jimin Hong & Fuwei Jiang, 2017. "Forecasting Chinese Stock Market Volatility With Economic Variables," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(3), pages 521-533, March.
    8. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
    9. Granger, Clive W. J. & Huangb, Bwo-Nung & Yang, Chin-Wei, 2000. "A bivariate causality between stock prices and exchange rates: evidence from recent Asianflu," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(3), pages 337-354.
    10. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    11. Yaojie Zhang & Feng Ma & Tianyi Wang & Li Liu, 2019. "Out‐of‐sample volatility prediction: A new mixed‐frequency approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(7), pages 669-680, November.
    12. Roll, Richard, 1992. "Industrial Structure and the Comparative Behavior of International Stock Market Indices," Journal of Finance, American Finance Association, vol. 47(1), pages 3-41, March.
    13. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    14. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    15. Grobys, Klaus, 2015. "Are volatility spillovers between currency and equity market driven by economic states? Evidence from the US economy," Economics Letters, Elsevier, vol. 127(C), pages 72-75.
    16. Yu, Honghai & Fang, Libing & Sun, Wencong, 2018. "Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 931-940.
    17. Nieh, Chien-Chung & Lee, Cheng-Few, 2001. "Dynamic relationship between stock prices and exchange rates for G-7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 41(4), pages 477-490.
    18. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    19. Walid, Chkili & Chaker, Aloui & Masood, Omar & Fry, John, 2011. "Stock market volatility and exchange rates in emerging countries: A Markov-state switching approach," Emerging Markets Review, Elsevier, vol. 12(3), pages 272-292, September.
    20. Caporale, Guglielmo Maria & Hunter, John & Menla Ali, Faek, 2014. "On the linkages between stock prices and exchange rates: Evidence from the banking crisis of 2007–2010," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 87-103.
    21. Fang, Libing & Qian, Yichuo & Chen, Ying & Yu, Honghai, 2018. "How does stock market volatility react to NVIX? Evidence from developed countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 490-499.
    22. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    23. Antonakakis, Nikolaos, 2012. "Exchange return co-movements and volatility spillovers before and after the introduction of euro," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1091-1109.
    24. Moore, Tomoe & Wang, Ping, 2014. "Dynamic linkage between real exchange rates and stock prices: Evidence from developed and emerging Asian markets," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 1-11.
    25. Fenghua Wen & Jihong Xiao & Xiaohua Xia & Bin Chen & Zhengyan Xiao & Jinyi Li, 2019. "Oil Prices and Chinese Stock Market: Nonlinear Causality and Volatility Persistence," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(6), pages 1247-1263, May.
    26. Gong, Xu & Lin, Boqiang, 2017. "Forecasting the good and bad uncertainties of crude oil prices using a HAR framework," Energy Economics, Elsevier, vol. 67(C), pages 315-327.
    27. Dai, Zhifeng & Wen, Fenghua, 2018. "Some improved sparse and stable portfolio optimization problems," Finance Research Letters, Elsevier, vol. 27(C), pages 46-52.
    28. Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, vol. 106(3), pages 527-546.
    29. Qiao, Zhuo & Li, Yuming & Wong, Wing-Keung, 2008. "Policy change and lead-lag relations among China's segmented stock markets," Journal of Multinational Financial Management, Elsevier, vol. 18(3), pages 276-289, July.
    30. Zhifang He & Linjie He & Fenghua Wen, 2019. "Risk Compensation and Market Returns: The Role of Investor Sentiment in the Stock Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(3), pages 704-718, February.
    31. Girardin, Eric & Joyeux, Roselyne, 2013. "Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach," Economic Modelling, Elsevier, vol. 34(C), pages 59-68.
    32. Zhao, Hua, 2010. "Dynamic relationship between exchange rate and stock price: Evidence from China," Research in International Business and Finance, Elsevier, vol. 24(2), pages 103-112, June.
    33. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
    34. Liu, Jian & Cheng, Cheng & Yang, Xianglin & Yan, Lizhao & Lai, Yongzeng, 2019. "Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    35. Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
    36. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    37. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    38. Pan, Ming-Shiun & Fok, Robert Chi-Wing & Liu, Y. Angela, 2007. "Dynamic linkages between exchange rates and stock prices: Evidence from East Asian markets," International Review of Economics & Finance, Elsevier, vol. 16(4), pages 503-520.
    39. Liu, Li & Wan, Jieqiu, 2012. "The relationships between Shanghai stock market and CNY/USD exchange rate: New evidence based on cross-correlation analysis, structural cointegration and nonlinear causality test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6051-6059.
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    More about this item

    Keywords

    Industry return volatility; RMB/USD exchange rate fluctuation; Prediction ability; Forecasting;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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