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A new unique information share measure with applications on cross-listed Chinese banks

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  • Li, Hong
  • Shi, Yanlin

Abstract

We propose a unique measure of information share based on the factor modeling of the price innovations, which we refer to as the Factor Information Share (FIS). We show that the proposed FIS is improved over two widely used measures by providing meaningful rationale and unique identifiability. Our simulation study suggests that FIS also leads to more accurate estimates of the market-specific contribution in the process of price discovery. The empirical results include both static and dynamic FIS of cross-listed Chinese banks traded on A-shares and H-shares. By incorporating the news sentiment, we find that positive news has a larger influence on A-shares’ FIS than negative news.

Suggested Citation

  • Li, Hong & Shi, Yanlin, 2021. "A new unique information share measure with applications on cross-listed Chinese banks," Journal of Banking & Finance, Elsevier, vol. 128(C).
    • Handle: RePEc:eee:jbfina:v:128:y:2021:i:c:s0378426621000996
    DOI: 10.1016/j.jbankfin.2021.106141
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    as
    1. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    2. Bird, Ron & Yeung, Danny, 2012. "How do investors react under uncertainty?," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 310-327.
    3. Henderson, Daniel J. & Kumbhakar, Subal C. & Li, Qi & Parmeter, Christopher F., 2015. "Smooth coefficient estimation of a seemingly unrelated regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 148-162.
    4. Lin, Wensheng, 2017. "Modeling volatility linkages between Shanghai and Hong Kong stock markets before and after the connect program," Economic Modelling, Elsevier, vol. 67(C), pages 346-354.
    5. Marc K. Chan & Simon S. Kwok, 2016. "Capital account liberalization and dynamic price discovery: evidence from Chinese cross-listed stocks," Applied Economics, Taylor & Francis Journals, vol. 48(6), pages 517-535, February.
    6. de Jong, Frank, 2002. "Measures of contributions to price discovery: a comparison," Journal of Financial Markets, Elsevier, vol. 5(3), pages 323-327, July.
    7. Laakkonen Helinä & Lanne Markku, 2009. "Asymmetric News Effects on Exchange Rate Volatility: Good vs. Bad News in Good vs. Bad Times," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-38, December.
    8. 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.
    9. Ozturk, Sait R. & van der Wel, Michel & van Dijk, Dick, 2017. "Intraday price discovery in fragmented markets," Journal of Financial Markets, Elsevier, vol. 32(C), pages 28-48.
    10. Lettau, Martin & Pelger, Markus, 2020. "Estimating latent asset-pricing factors," Journal of Econometrics, Elsevier, vol. 218(1), pages 1-31.
    11. Donald Lien & Zijun Wang, 2016. "Estimation of Market Information Shares: A Comparison," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(11), pages 1108-1124, November.
    12. Thomas A. Lubik & Christian Matthes, 2015. "Time-Varying Parameter Vector Autoregressions: Specification, Estimation, and an Application," Economic Quarterly, Federal Reserve Bank of Richmond, issue 4Q, pages 323-352.
    13. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    14. Philipp Adämmer & Martin T. Bohl & Christian Gross, 2016. "Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(9), pages 851-869, September.
    15. Eric C. Chang & Joseph W. Cheng & Yinghui Yu, 2007. "Short‐Sales Constraints and Price Discovery: Evidence from the Hong Kong Market," Journal of Finance, American Finance Association, vol. 62(5), pages 2097-2121, October.
    16. Putniņš, Tālis J., 2013. "What do price discovery metrics really measure?," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 68-83.
    17. Avino, Davide & Lazar, Emese & Varotto, Simone, 2015. "Time varying price discovery," Economics Letters, Elsevier, vol. 126(C), pages 18-21.
    18. Burdekin, Richard C.K. & Siklos, Pierre L., 2018. "Quantifying the impact of the November 2014 Shanghai-Hong Kong Stock Connect," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 156-163.
    19. Yeh, Yin-Hua & Lee, Tsun-Siou, 2000. "The interaction and volatility asymmetry of unexpected returns in the greater China stock markets," Global Finance Journal, Elsevier, vol. 11(1-2), pages 129-149.
    20. Yan, Bingcheng & Zivot, Eric, 2010. "A structural analysis of price discovery measures," Journal of Financial Markets, Elsevier, vol. 13(1), pages 1-19, February.
    21. Donald Lien & Keshab Shrestha, 2014. "Price Discovery in Interrelated Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(3), pages 203-219, March.
    22. Donald Lien & Keshab Shrestha, 2009. "A new information share measure," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(4), pages 377-395, April.
    23. Su, Qian & Chong, Terence Tai-Leung, 2007. "Determining the contributions to price discovery for Chinese cross-listed stocks," Pacific-Basin Finance Journal, Elsevier, vol. 15(2), pages 140-153, April.
    24. Bai, Ye & Chow, Darien Yan Pang, 2017. "Shanghai-Hong Kong Stock Connect: An analysis of Chinese partial stock market liberalization impact on the local and foreign markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 182-203.
    25. Martin Lettau & Markus Pelger & Stijn Van Nieuwerburgh, 2020. "Factors That Fit the Time Series and Cross-Section of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2274-2325.
    26. Chiang C-T. & Rice J. A & Wu C. O, 2001. "Smoothing Spline Estimation for Varying Coefficient Models With Repeatedly Measured Dependent Variables," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 605-619, June.
    27. Jianhua Z. Huang & Haipeng Shen, 2004. "Functional Coefficient Regression Models for Non‐linear Time Series: A Polynomial Spline Approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(4), pages 515-534, December.
    28. Bae, Kee-Hong & Ozoguz, Arzu & Tan, Hongping & Wirjanto, Tony S., 2012. "Do foreigners facilitate information transmission in emerging markets?," Journal of Financial Economics, Elsevier, vol. 105(1), pages 209-227.
    29. Wang, Weishen, 2020. "Shanghai-Hong Kong Stock Exchange Connect Program: A story of two markets and different groups of stocks," Journal of Multinational Financial Management, Elsevier, vol. 55(C).
    30. Donald Lien & Zijun Wang, 2019. "Quantile information share," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 38-55, January.
    31. Veronesi, Pietro, 1999. "Stock Market Overreaction to Bad News in Good Times: A Rational Expectations Equilibrium Model," Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 975-1007.
    32. Martin Lettau & Markus Pelger, 2020. "Factors That Fit the Time Series and Cross-Section of Stock Returns," Review of Finance, European Finance Association, vol. 33(5), pages 2274-2325.
    33. Joel Hasbrouck, 2003. "Intraday Price Formation in U.S. Equity Index Markets," Journal of Finance, American Finance Association, vol. 58(6), pages 2375-2400, December.
    34. Grammig, Joachim & Peter, Franziska J., 2013. "Telltale Tails: A New Approach to Estimating Unique Market Information Shares," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(2), pages 459-488, April.
    35. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    36. Bai, Min & Li, Xiao-Ming & Qin, Yafeng, 2017. "Shortability and asset pricing model: Evidence from the Hong Kong stock market," Journal of Banking & Finance, Elsevier, vol. 85(C), pages 15-29.
    37. Hasbrouck, Joel, 2002. "Stalking the "efficient price" in market microstructure specifications: an overview," Journal of Financial Markets, Elsevier, vol. 5(3), pages 329-339, July.
    38. Baillie, Richard T. & Geoffrey Booth, G. & Tse, Yiuman & Zabotina, Tatyana, 2002. "Price discovery and common factor models," Journal of Financial Markets, Elsevier, vol. 5(3), pages 309-321, July.
    39. Markus Pelger, 2020. "Understanding Systematic Risk: A High‐Frequency Approach," Journal of Finance, American Finance Association, vol. 75(4), pages 2179-2220, August.
    40. Shi, Yanlin & Liu, Wai-Man & Ho, Kin-Yip, 2016. "Public news arrival and the idiosyncratic volatility puzzle," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 159-172.
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    Cited by:

    1. Zhao, Yuyang & Xiang, Cheng & Cai, Wenwu, 2021. "Stock market liberalization and institutional herding: Evidence from the Shanghai-Hong Kong and Shenzhen-Hong Kong Stock Connects," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    2. Ziliang Yu & Jian Yang & Robert I. Webb, 2023. "Price discovery in China's crude oil futures markets: An emerging Asian benchmark?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 297-324, March.
    3. Lien, Donald, 2022. "Comparisons of Alternative Information Share Measures," Finance Research Letters, Elsevier, vol. 50(C).
    4. Hong Li & Yanlin Shi, 2022. "Robust information share measures with an application on the international crude oil markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 555-579, April.
    5. Donald Lien & Pi-Hsia Hung, 2023. "Whose trades contribute more to price discovery? Evidence from the Taiwan stock exchange," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 213-263, July.

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    More about this item

    Keywords

    Price discovery; Information share; Factor model; Cross-market analysis;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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