IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v58y2023ipcs1544612323008772.html
   My bibliography  Save this article

Outward foreign direct greenfield investments and firms predicted long-term stock volatility levels and connectedness. Evidence from China

Author

Listed:
  • Vagnani, Gianluca
  • Tian, Jinhuan
  • Dong, Yan

Abstract

The paper offers an initial effort to unfold the effect of outward foreign direct greenfield investments (OFDGIs) on firms' long-term stock return volatility levels and connectedness. Within a sample of Chinese firms, in a GARCH-MIDAS model, we offer evidence that OFDGIs investments will reduce firms' long-term stock return volatility. We also introduced a measure of firms' stock return volatility connectedness and studied OFDGIs' effect on firms' dependence on other firms' risks. Implications for theory and practice are discussed.

Suggested Citation

  • Vagnani, Gianluca & Tian, Jinhuan & Dong, Yan, 2023. "Outward foreign direct greenfield investments and firms predicted long-term stock volatility levels and connectedness. Evidence from China," Finance Research Letters, Elsevier, vol. 58(PC).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323008772
    DOI: 10.1016/j.frl.2023.104505
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323008772
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2023.104505?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. Wang, Li-Hsun, 2017. "Accounting quality and information asymmetry of foreign direct investment firms," Research in International Business and Finance, Elsevier, vol. 42(C), pages 950-958.
    2. Wang, Li-Hsun & Lin, Chu-Hsiung & Fung, Hung-Gay & Kao, Tzu-Chuan, 2019. "Foreign direct investment and downside risk: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    3. Justin Paul & Gabriel R. G. Benito, 2018. "A review of research on outward foreign direct investment from emerging countries, including China: what do we know, how do we know and where should we be heading?," Asia Pacific Business Review, Taylor & Francis Journals, vol. 24(1), pages 90-115, January.
    4. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    5. Cao, Jiahui & Wen, Fenghua & Zhang, Yue & Yin, Zhujia & Zhang, Yun, 2022. "Idiosyncratic volatility and stock price crash risk: Evidence from china," Finance Research Letters, Elsevier, vol. 44(C).
    6. 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.
    7. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    8. Dong, Yan & Tian, Jinhuan & Wen, Qiang, 2022. "Environmental regulation and outward foreign direct investment: Evidence from China," China Economic Review, Elsevier, vol. 76(C).
    9. Nikolaos Demiris & Theodore Kypraios & L. Vanessa Smith, 2014. "On the epidemic of financial crises," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(3), pages 697-723, June.
    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. Ye, Wuyi & Hu, Chenglong & Guo, Ranran, 2024. "Tail risk network of Chinese green-related stocks market," Finance Research Letters, Elsevier, vol. 67(PB).
    2. Du, HouYang & Guo, Hang, 2024. "Establishment of environmental tribunals and corporate outward investment behaviour," Finance Research Letters, Elsevier, vol. 67(PA).

    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. Yang, Xiaoqi & Vagnani, Gianluca & Dong, Yan & Ji, Xu, 2024. "Short selling and firms’ long-term stock return volatility: Evidence from Chinese concept stocks in Hong Kong," Finance Research Letters, Elsevier, vol. 70(C).
    2. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    3. Yu, Xiaoling & Huang, Yirong, 2021. "The impact of economic policy uncertainty on stock volatility: Evidence from GARCH–MIDAS approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    4. Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2021. "Stock market volatility and jumps in times of uncertainty," Journal of International Money and Finance, Elsevier, vol. 113(C).
    5. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    6. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Lasisi, Lukman & Olaniran, Abeeb, 2022. "Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Chaturvedi, Priya & Kumar, Kuldeep, 2022. "Econometric modelling of exchange rate volatility using mixed-frequency data," MPRA Paper 115222, University Library of Munich, Germany.
    8. 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.
    9. Xu Gong & Mingchao Wang & Liuguo Shao, 2022. "The impact of macro economy on the oil price volatility from the perspective of mixing frequency," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4487-4514, October.
    10. Xiao, Jihong & Jiang, Jiajie & Zhang, Yaojie, 2024. "Policy uncertainty, investor sentiment, and good and bad volatilities in the stock market: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).
    11. Lu Wang & Feng Ma & Guoshan Liu & Qiaoqi Lang, 2023. "Do extreme shocks help forecast oil price volatility? The augmented GARCH‐MIDAS approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2056-2073, April.
    12. Andy Wui Wing Cheng & Iris Wing Han Yip, 2017. "China’s Macroeconomic Fundamentals on Stock Market Volatility: Evidence from Shanghai and Hong Kong," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 20(02), pages 1-57, June.
    13. Fang, Libing & Yu, Honghai & Xiao, Wen, 2018. "Forecasting gold futures market volatility using macroeconomic variables in the United States," Economic Modelling, Elsevier, vol. 72(C), pages 249-259.
    14. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    15. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    16. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    17. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    18. Crimmel, Jeremy & Elyasiani, Elyas, 2021. "The association between financial market volatility and banking market structure," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 335-349.
    19. Deng, Yongheng & Girardin, Eric & Joyeux, Roselyne, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," China Economic Review, Elsevier, vol. 48(C), pages 205-222.
    20. Emiliano Magrini & Ayca Donmez, 2013. "Agricultural Commodity Price Volatility and Its Macroeconomic Determinants: A GARCH-MIDAS Approach," JRC Research Reports JRC84138, Joint Research Centre.

    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:finlet:v:58:y:2023:i:pc:s1544612323008772. 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/frl .

    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.