IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v57y2019ics0927538x19301040.html
   My bibliography  Save this article

Predicting the volatility of the iShares China Large-Cap ETF: What is the role of the SSE 50 ETF?

Author

Listed:
  • Zhu, Fangfei
  • Luo, Xingguo
  • Jin, Xuejun

Abstract

This study investigates whether the volatility of the Shanghai Stock Exchange (SSE) 50 ETF contains useful information for predicting the volatility of the U.S.-traded iShares China Large-Cap ETF (FXI). We use both in-sample and out-of-sample predictive regressions to empirically show that the realized volatility of the SSE 50 ETF significantly improves the forecasts of the future FXI realized volatility. We also find that the realized volatility of the SSE 50 ETF has predictive power for the future implied volatility of the FXI, which is calculated from the U.S. options market. However, the empirical results show that both the realized volatility and implied volatility of the FXI have limited explanatory ability for the realized volatility of the SSE 50 ETF.

Suggested Citation

  • Zhu, Fangfei & Luo, Xingguo & Jin, Xuejun, 2019. "Predicting the volatility of the iShares China Large-Cap ETF: What is the role of the SSE 50 ETF?," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:pacfin:v:57:y:2019:i:c:s0927538x19301040
    DOI: 10.1016/j.pacfin.2019.101192
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X19301040
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.pacfin.2019.101192?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Westerlund, Joakim & Narayan, Paresh Kumar & Zheng, Xinwei, 2015. "Testing for stock return predictability in a large Chinese panel," Emerging Markets Review, Elsevier, vol. 24(C), pages 81-100.
    3. Kalok Chan & Albert J. Menkveld & Zhishu Yang, 2008. "Information Asymmetry and Asset Prices: Evidence from the China Foreign Share Discount," Journal of Finance, American Finance Association, vol. 63(1), pages 159-196, February.
    4. 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.
    5. Lior Menzly & Oguzhan Ozbas, 2010. "Market Segmentation and Cross‐predictability of Returns," Journal of Finance, American Finance Association, vol. 65(4), pages 1555-1580, August.
    6. Luo, Xingguo & Ye, Zinan, 2015. "Predicting volatility of the Shanghai silver futures market: What is the role of the U.S. options market?," Finance Research Letters, Elsevier, vol. 15(C), pages 68-77.
    7. Kwangwon Ahn & Yingyao Bi & Sungbin Sohn, 2019. "Price discovery among SSE 50 Index‐based spot, futures, and options markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 238-259, February.
    8. Joakim Westerlund & Paresh K Narayan & Xinwei Zheng, "undated". "Testing For Stock Return Predictability In A Large Chinese Panel," Working Papers 2015_11, Deakin University, Department of Economics.
    9. Jianhui Li & Sebastian A. Gehricke & Jin E. Zhang, 2019. "How do US options traders “smirk” on China? Evidence from FXI options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(11), pages 1450-1470, November.
    10. 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.
    11. Goh, Jeremy C. & Jiang, Fuwei & Tu, Jun & Wang, Yuchen, 2013. "Can US economic variables predict the Chinese stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 22(C), pages 69-87.
    12. Chunxin Jia & Yaping Wang & Wei Xiong, 2017. "Market Segmentation and Differential Reactions of Local and Foreign Investors to Analyst Recommendations," The Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 2972-3008.
    13. Bryan Kelly & Seth Pruitt, 2013. "Market Expectations in the Cross-Section of Present Values," Journal of Finance, American Finance Association, vol. 68(5), pages 1721-1756, October.
    14. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    15. Xiaoqing Eleanor Xu & Hung–Gay Fung, 2002. "Information Flows across Markets: Evidence from China–Backed Stocks Dual–Listed in Hong Kong and New York," The Financial Review, Eastern Finance Association, vol. 37(4), pages 563-588, November.
    16. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    17. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marszk, Adam & Lechman, Ewa, 2021. "Reshaping financial systems: The role of ICT in the diffusion of financial innovations – Recent evidence from European countries," Technological Forecasting and Social Change, Elsevier, vol. 167(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    2. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    3. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
    4. Yanying Zhang & Yiuman Tse & Gaiyan Zhang, 2022. "Return predictability between industries and the stock market in China," Pacific Economic Review, Wiley Blackwell, vol. 27(2), pages 194-220, May.
    5. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    6. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    7. Mingwei Sun & Paskalis Glabadanidis, 2022. "Can technical indicators predict the Chinese equity risk premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 114-142, March.
    8. Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
    9. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    10. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    11. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    12. Shi, Qi, 2023. "The RP-PCA factors and stock return predictability: An aligned approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    13. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    14. 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.
    15. Ruan, Qingsong & Wang, Zilin & Zhou, Yaping & Lv, Dayong, 2020. "A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China," Economic Modelling, Elsevier, vol. 88(C), pages 47-58.
    16. David G. McMillan, 2016. "Stock return predictability and market integration: The role of global and local information," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1178363-117, December.
    17. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    18. Lu, Helen & Jacobsen, Ben, 2016. "Cross-asset return predictability: Carry trades, stocks and commodities," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 62-87.
    19. Tsiakas, Ilias & Li, Jiahan & Zhang, Haibin, 2020. "Equity premium prediction and the state of the economy," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 75-95.
    20. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:pacfin:v:57:y:2019:i:c:s0927538x19301040. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/pacfin .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.