Organizational Sources of Mutual Funds’ Common Top Holdings and Stock Return Comovement: Evidence from China
DOI:
https://doi.org/10.54097/knn57p02Keywords:
Common ownership, Fund families, Manager sharing, Mutual funds, Return comovementAbstract
Two stocks can share the same number of common mutual fund owners and yet differ in who those owners are. Using the holdings of actively managed equity and hybrid mutual funds in China from the fourth quarter of 2015 to the third quarter of 2024, we examine whether the organizational composition of common owners is related to subsequent stock return comovement. We classify each pair of common funds as belonging to the same fund family with a shared manager, to the same family without a shared manager, or to different families, and we measure comovement as the within-month correlation of daily residual returns after holdings are disclosed. Among stock pairs held by exactly two common funds, pairs held across families comove more strongly than pairs held within a family. Controlling for the number of common funds, the intensity of common ownership, and stock characteristics, both within-family shares are negatively associated with comovement. Stock-pair fixed effects weaken these associations: the shared-manager coefficient remains significantly negative, whereas the other becomes insignificant. In a matched sample of pairs selected through common top holdings, both negative associations hold under top-ten and full holdings, but neither is significant in a separate random sample of full-holdings pairs. Our results suggest that the organizational composition of common owners contains information about comovement beyond the number of common funds and the intensity of common ownership.
Downloads
References
[1] Antón, M., & Polk, C. (2014). Connected stocks. The Journal of Finance, 69(3), 1099–1127. DOI: https://doi.org/10.1111/jofi.12149
[2] Coval, J., & Stafford, E. (2007). Asset fire sales (and purchases) in equity markets. Journal of Financial Economics, 86(2), 479–512. DOI: https://doi.org/10.1016/j.jfineco.2006.09.007
[3] Greenwood, R., & Thesmar, D. (2011). Stock price fragility. Journal of Financial Economics, 102(3), 471–490. DOI: https://doi.org/10.1016/j.jfineco.2011.06.003
[4] Chen, X., Liu, Y., & Luo, R. (2017). Does information sharing among institutional investors lead to black swans? Fund information networks and extreme market risk. Journal of Financial Research, (7), 140–155. (In Chinese).
[5] Li, K., et al. (2019). Mutual fund manager turnover, stock connection and stock price. Journal of Financial Research, (1), 188–206. (In Chinese).
[6] Zhou, Y., Tang, C., & Xu, X. (2025). Fund common ownership network and stock price comovement. Journal of Financial Research, (11), 189–206. (In Chinese).
[7] Elton, E. J., Gruber, M. J., & Green, T. C. (2007). The impact of mutual fund family membership on investor risk. Journal of Financial and Quantitative Analysis, 42(2), 257–277. DOI: https://doi.org/10.1017/S0022109000003276
[8] Cici, G., Jaspersen, S., & Kempf, A. (2017). Speed of information diffusion within fund families. The Review of Asset Pricing Studies, 7(1), 144–170. DOI: https://doi.org/10.1093/rapstu/raw007
[9] He, X., Su, Z., & Zhang, Y. (2024). Product homogenization in fund families and fund performance. Journal of Management Science, 37(5), 146–158. (In Chinese).
[10] Hong, H., Kubik, J. D., & Stein, J. C. (2005). Thy neighbor’s portfolio: Word-of-mouth effects in the holdings and trades of money managers. The Journal of Finance, 60(6), 2801–2824. DOI: https://doi.org/10.1111/j.1540-6261.2005.00817.x
[11] Pool, V. K., Stoffman, N., & Yonker, S. E. (2015). The people in your neighborhood: Social interactions and mutual fund portfolios. The Journal of Finance, 70(6), 2679–2732. DOI: https://doi.org/10.1111/jofi.12208
[12] Luo, Y., & Lin, S. (2022). A study of fund managers’ investment behavior from the perspective of social network analysis. Modern Finance and Economics (Journal of Tianjin University of Finance and Economics), 42(4), 79–95. (In Chinese).
[13] Shen, Y., Mao, X., & Liu, Y. (2024). Alumni network, mutual fund herding and information spillover: Evidence from China. Pacific-Basin Finance Journal, 83, 102265. DOI: https://doi.org/10.1016/j.pacfin.2024.102265
[14] Genc, E., et al. (2023). Finding information in obvious places: Work connections and mutual fund investment ideas. Journal of Financial Markets, 63, 100767. DOI: https://doi.org/10.1016/j.finmar.2022.100767
[15] Cici, G., Kempf, A., & Peitzmeier, C. (2022). Knowledge spillovers in the mutual fund industry through labor mobility. Journal of Banking & Finance, 134, 106310. DOI: https://doi.org/10.1016/j.jbankfin.2021.106310
[16] Ben-David, I., et al. (2021). The granular nature of large institutional investors. Management Science, 67(11), 6629–6659. DOI: https://doi.org/10.1287/mnsc.2020.3808
[17] Barberis, N., Shleifer, A., & Wurgler, J. (2005). Comovement. Journal of Financial Economics, 75(2), 283–317. DOI: https://doi.org/10.1016/j.jfineco.2004.04.003
[18] Luo, R., Tian, Z., & Fang, H. (2020). “Harmonious but different” or “standing out from the crowd”? A perspective of fund network information use. Journal of Financial Research, (8), 188–206. (In Chinese).
[19] Peng, W., & Chen, Y. (2015). Conflicts of interest and substitution of management effort in funds: Evidence from managers running multiple funds. Review of Investment Studies, 34(4), 129–142. (In Chinese).
[20] Beggs, W., & DeVault, L. (2022). Mutual fund (sub)advisor connections and crowds. Journal of Empirical Finance, 67, 231–252. DOI: https://doi.org/10.1016/j.jempfin.2022.03.009
[21] Caglayan, M. O., Hu, Y., & Xue, W. (2021). Mutual fund herding and return comovement in Chinese equities. Pacific-Basin Finance Journal, 68, 101599. DOI: https://doi.org/10.1016/j.pacfin.2021.101599
[22] Guo, X., et al. (2024). Institutional herding and investor sentiment. Journal of Financial Markets, 68, 100891. DOI: https://doi.org/10.1016/j.finmar.2024.100891
[23] Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3–56. DOI: https://doi.org/10.1016/0304-405X(93)90023-5
[24] Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3), 607–636. DOI: https://doi.org/10.1086/260061
[25] Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708. DOI: https://doi.org/10.2307/1913610
[26] Cameron, A. C., Gelbach, J. B., & Miller, D. L. (2011). Robust inference with multiway clustering. Journal of Business & Economic Statistics, 29(2), 238–249. DOI: https://doi.org/10.1198/jbes.2010.07136
[27] Aronow, P. M., Samii, C., & Assenova, V. A. (2015). Cluster-robust variance estimation for dyadic data. Political Analysis, 23(4), 564–577. DOI: https://doi.org/10.1093/pan/mpv018
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
