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Predicting firm stock returns with customer stock returns: Moderating effects of customer characteristics

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  • Shi, Jinyan
  • Yu, Conghui
  • Liu, Xiangkun
  • Li, Yanxi

Abstract

Based on the multiple regression model, this study examines the potential predictive effect of customer stock returns to firm stock returns and the moderating effect of diverse customer characteristics on the predictability. By using a sample of Chinese A-share manufacturing firms listed on the Shanghai stock exchange and Shenzhen stock exchange between 2009 and 2017, we find that customer stock returns positively predict firm stock returns in the subsequent month. Additional examinations reveal that the positive predictive effect of customer stock returns on firm stock returns is more intense for firm with high proportion of state-owned customers, customer stability, customer bargaining power and customer concentration than for those with low indicators. Overall, this study contributes to the growing literature on supply chain and predictability of stock returns by shedding light on the forecasting effect of customer stock returns on firm stock returns and the predictive heterogeneity owing to customer characteristics.

Suggested Citation

  • Shi, Jinyan & Yu, Conghui & Liu, Xiangkun & Li, Yanxi, 2020. "Predicting firm stock returns with customer stock returns: Moderating effects of customer characteristics," Research in International Business and Finance, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:riibaf:v:54:y:2020:i:c:s0275531920302129
    DOI: 10.1016/j.ribaf.2020.101280
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    as
    1. 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.
    2. Lee, Charles M.C. & Sun, Stephen Teng & Wang, Rongfei & Zhang, Ran, 2019. "Technological links and predictable returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 76-96.
    3. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    4. Chaoqun Ma & Shisong Xiao & Zonggang Ma, 2018. "Investor sentiment and the prediction of stock returns: a quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 50(50), pages 5401-5415, October.
    5. Boone, Audra L. & Ivanov, Vladimir I., 2012. "Bankruptcy spillover effects on strategic alliance partners," Journal of Financial Economics, Elsevier, vol. 103(3), pages 551-569.
    6. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    7. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    8. Lauren Cohen & Andrea Frazzini, 2008. "Economic Links and Predictable Returns," Journal of Finance, American Finance Association, vol. 63(4), pages 1977-2011, August.
    9. Cakici, Nusret & Fabozzi, Frank J. & Tan, Sinan, 2013. "Size, value, and momentum in emerging market stock returns," Emerging Markets Review, Elsevier, vol. 16(C), pages 46-65.
    10. 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.
    11. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    12. Sun, Licheng & Najand, Mohammad & Shen, Jiancheng, 2016. "Stock return predictability and investor sentiment: A high-frequency perspective," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 147-164.
    13. Bollerslev, Tim & Xu, Lai & Zhou, Hao, 2015. "Stock return and cash flow predictability: The role of volatility risk," Journal of Econometrics, Elsevier, vol. 187(2), pages 458-471.
    14. Chen, Long & Zhang, Gaiyan & Zhang, Weina, 2016. "Return predictability in the corporate bond market along the supply chain," Journal of Financial Markets, Elsevier, vol. 29(C), pages 66-86.
    15. Maio, Paulo & Santa-Clara, Pedro, 2015. "Dividend Yields, Dividend Growth, and Return Predictability in the Cross Section of Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(1-2), pages 33-60, April.
    16. Li, Jun & Yu, Jianfeng, 2012. "Investor attention, psychological anchors, and stock return predictability," Journal of Financial Economics, Elsevier, vol. 104(2), pages 401-419.
    17. Darwish, M.A. & Odah, O.M., 2010. "Vendor managed inventory model for single-vendor multi-retailer supply chains," European Journal of Operational Research, Elsevier, vol. 204(3), pages 473-484, August.
    18. Patelis, Alex D, 1997. "Stock Return Predictability and the Role of Monetary Policy," Journal of Finance, American Finance Association, vol. 52(5), pages 1951-1972, December.
    19. Cao, Jie & Chordia, Tarun & Lin, Chen, 2016. "Alliances and Return Predictability," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(5), pages 1689-1717, October.
    20. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    21. Matthew D. Hill & G. Wayne Kelly & Michael J. Highfield, 2010. "Net Operating Working Capital Behavior: A First Look," Financial Management, Financial Management Association International, vol. 39(2), pages 783-805, June.
    22. Dhaliwal, Dan & Judd, J. Scott & Serfling, Matthew & Shaikh, Sarah, 2016. "Customer concentration risk and the cost of equity capital," Journal of Accounting and Economics, Elsevier, vol. 61(1), pages 23-48.
    23. Zhu, Qinghua & Liu, Junjun & Lai, Kee-hung, 2016. "Corporate social responsibility practices and performance improvement among Chinese national state-owned enterprises," International Journal of Production Economics, Elsevier, vol. 171(P3), pages 417-426.
    24. Brennan, Michael J. & Chordia, Tarun & Subrahmanyam, Avanidhar, 1998. "Alternative factor specifications, security characteristics, and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 49(3), pages 345-373, September.
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    Cited by:

    1. elviona, adra, 2020. "Peran Teori Kontingen Sebagai Variabel Moderasi dan Efek Mediasi Terhadap Kinerja Perusahaan," OSF Preprints a275k, Center for Open Science.
    2. Awijen, Haithem & Ben Zaied, Younes & Ben Lahouel, Béchir & Khlifi, Foued, 2023. "Machine learning for US cross-industry return predictability under information uncertainty," Research in International Business and Finance, Elsevier, vol. 64(C).

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    More about this item

    Keywords

    Stock returns; Return predictability; Customer characteristics; Economic dependence; Bullwhip effect;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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