Advertisement

Journal of Economic Interaction and Coordination

, Volume 14, Issue 4, pp 859–890 | Cite as

Differences in the effects of seller-initiated versus buyer-initiated crowded trades in stock markets

  • Liyun ZhouEmail author
  • Chunpeng Yang
Regular Article
  • 57 Downloads

Abstract

This paper illustrates the differences in the effects of seller-initiated versus buyer-initiated crowded trades in stock markets. First, a one-period multi-investor model is proposed to describe how crowded trades affect stock prices. Further, we theoretically decompose the crowded trades into buyer-initiated crowded trades and seller-initiated crowded trades and, respectively, analyse their effects on stock prices. An empirical study is conducted to examine the theoretical model, obtaining the following results. First, stock prices increase with crowded trades; second, stock prices are positively related to buyer-initiated crowded trades, but negatively related to seller-initiated crowded trades; and third, the effects of crowded trades, buyer-initiated crowded trades and seller-initiated crowded trades on stock prices are stronger for the younger stocks, lower price earnings ratio stocks, lower earnings per share stocks, and lower fixed asset ratio stocks. Collectively, our results can provide new insights into the roles of crowded trades on stock prices.

Keywords

Crowded trades Buyer-initiated crowded trades Seller-initiated crowded trades Stock prices 

JEL Classification

G1 G10 G12 

Notes

Acknowledgements

We are especially grateful to the editor (Prof. Thomas Lux), the Associate Editor and anonymous referees for constructive comments that have significantly improved the paper. This work was supported by the National Natural Science Foundation of China (71803051), the Natural Science Foundation of Guangdong Province (2018A030310218); the project of Guangdong Planning office of Philosophy and Social Science in 2017 (GD17XLJ04; GD17XGL14), the youth project of Department of Education of Guangdong Province (2017WQNCX014), National Science Foundation of China (71471067; 71720107002), and China Postdoctoral Science Foundation (2019M652913).

References

  1. Aitken M, Cumming D, Zhan F (2015) Exchange trading rules, surveillance and suspected insider trading. J Corp Finance 34:311–330Google Scholar
  2. Amihud Y (2002) Illiquidity and stock returns: cross-section and time-series effects. J Financ Mark 5(1):31–56Google Scholar
  3. Avramov D, Chordia T (2006) Asset pricing models and financial market anomalies. Rev Financ Stud 19(3):1001–1040Google Scholar
  4. Bailey W, Cai J, Yan LC, Wang F (2009) Stock returns, order imbalances, and commonality: evidence on individual, institutional, and proprietary investors in China. J Bank Finance 33(1):9–19Google Scholar
  5. Baker M, Wurgler J (2006) Investor sentiment and the cross-section of stock returns. J Finance 61(4):1645–1680Google Scholar
  6. Baltzer M, Jank S, Smajlbegovic E (2019) Who trades on momentum? J Financ Mark 42:56–74Google Scholar
  7. Barberis N, Thaler R (2003) A survey of behavioral finance. In: Constantinides GM, Harris M, Stulz RM (eds) Handbook of the economics of finance, vol 1. Elsevier, Amsterdam, pp 1053–1128Google Scholar
  8. Blocher J (2016) Network externalities in mutual funds. J Financ Mark 30:1–26Google Scholar
  9. Bollerslev T, Li SZ, Todorov V (2016) Roughing up beta: continuous versus discontinuous betas and the cross section of expected stock returns. J Financ Econ 120(3):464–490Google Scholar
  10. Bookstaber R, Foley MD, Tivnan BF (2016) Toward an understanding of market resilience: market liquidity and heterogeneity in the investor decision cycle. J Econ Interact Coord 11(2):205–227Google Scholar
  11. Brogaard J, Li D, Xia Y (2017) Stock liquidity and default risk. J Financ Econ 124(3):486–502Google Scholar
  12. Cen L, Lu H, Yang L (2013) Investor sentiment, disagreement, and the breadth-return relationship. Manag Sci 59(5):1076–1091Google Scholar
  13. Chan K, Hameed A, Kang W (2013) Stock price synchronicity and liquidity. J Financ Mark 16(3):414–438Google Scholar
  14. Chen J, Hong H, Stein JC (2002) Breadth of ownership and stock returns. J Financ Econ 66(2):171–205Google Scholar
  15. Cheung YL, Ouyang Z, Weiqiang TAN (2009) How regulatory changes affect IPO underpricing in China. China Econ Rev 20(4):692–702Google Scholar
  16. Chordia T, Subrahmanyam A (2004) Order imbalance and individual stock returns: theory and evidence. J Financ Econ 72(3):485–518Google Scholar
  17. Chordia T, Roll R, Subrahmanyam A (2001) Market liquidity and trading activity. J Finance 56(2):501–530Google Scholar
  18. Chordia T, Roll R, Subrahmanyam A (2002) Order imbalance, liquidity, and market returns. J Financ Econ 65(1):111–130Google Scholar
  19. Chordia T, Subrahmanyam A, Tong Q (2014) Have capital market anomalies attenuated in the recent era of high liquidity and trading activity? J Account Econ 58(1):41–58Google Scholar
  20. Chordia T, Hu J, Subrahmanyam A, Tong Q (2017) Order flow volatility and equity costs of capital. Manag Sci 65:1520–1551Google Scholar
  21. Cremers M, Halling M, Weinbaum D (2015) Aggregate jump and volatility risk in the cross-section of stock returns. J Finance 70(2):577–614Google Scholar
  22. Cumming D, Johan S, Li D (2011) Exchange trading rules and stock market liquidity. J Financ Econ 99(3):651–671Google Scholar
  23. Datar VT, Naik NY, Radcliffe R (1998) Liquidity and stock returns: an alternative test. J Financ Mark 1(2):203–219Google Scholar
  24. Ding R, Hou W (2015) Retail investor attention and stock liquidity. J Int Financ Mark Inst Money 37:12–26Google Scholar
  25. Eckbo BE, Norli Ø (2005) Liquidity risk, leverage and long-run IPO returns. J Corp Finance 11(1–2):1–35Google Scholar
  26. Eiling E (2013) Industry-specific human capital, idiosyncratic risk, and the cross-section of expected stock returns. J Finance 68(1):43–84Google Scholar
  27. Fama EF, French KR (1992) The cross-section of expected stock returns. J Finance 47(2):427–465Google Scholar
  28. Fama EF, French KR (1993) Common risk factors in the returns on stocks and bonds. J Financ Econ 33(1):3–56Google Scholar
  29. Fu F (2009) Idiosyncratic risk and the cross-section of expected stock returns. J Financ Econ 91(1):24–37Google Scholar
  30. Gerhold S, Guasoni P, Muhle-Karbe J, Schachermayer W (2014) Transaction costs, trading volume, and the liquidity premium. Finance Stoch 18(1):1–37Google Scholar
  31. Han B, Kumar A (2013) Speculative retail trading and asset prices. J Financ Quant Anal 48(2):377–404Google Scholar
  32. Hanson SG, Sunderam A (2014) The growth and limits of arbitrage: evidence from short interest. Rev Financ Stud 27(4):1238–1286Google Scholar
  33. Hausman JA (1978) Specification tests in econometrics. Econom J Econom Soc 46:1251–1271Google Scholar
  34. Hendershott T, Jones CM, Menkveld AJ (2011) Does algorithmic trading improve liquidity? J Finance 66(1):1–33Google Scholar
  35. Hong H, Li W, Ni SX, Scheinkman JA, Yan P (2015) Days to cover and stock returns. NBER working paperGoogle Scholar
  36. Hou K, Moskowitz TJ (2005) Market frictions, price delay, and the cross-section of expected returns. Rev Financ Stud 18(3):981–1020Google Scholar
  37. Jia Y, Yang C (2017) Disagreement and the risk-return relation. Econ Model 64:97–104Google Scholar
  38. Kimbro MB (2005) Managing underpricing? The case of pre-IPO discretionary accruals in China. J Int Financ Manag Account 16(3):229–262Google Scholar
  39. Kumar A, Lee C (2006) Retail investor sentiment and return comovements. J Finance 61(5):2451–2486Google Scholar
  40. Lee C, Ready MJ (1991) Inferring trade direction from intraday data. J Finance 46(2):733–746Google Scholar
  41. Li L (2006) Can corporate governance variables explain short-term IPO returns?: A study of the Chinese market. Account Account Perform 12(1):64Google Scholar
  42. Li M, Zheng H (2017) Heterogeneous trading and complex price dynamics. J Econ Interact Coord 12(2):437–442Google Scholar
  43. Ma R, Anderson HD, Marshall BR (2018) Stock market liquidity and trading activity: Is China different? Int Rev Financ Anal 56:32–51Google Scholar
  44. Menkveld AJ (2014) Crowded trades: an overlooked systemic risk for central clearing counterparties. SSRN working paperGoogle Scholar
  45. Pagano M (1989) Trading volume and asset liquidity. Q J Econ 104(2):255–274Google Scholar
  46. Pojarliev M, Richard ML (2011) Detecting crowded trades in currency funds. Financ Anal J 01:26–39Google Scholar
  47. Shang H, Yuan P, Huang L (2016) Macroeconomic factors and the cross-section of commodity futures returns. Int Rev Econ Finance 45:316–332Google Scholar
  48. Sias R, Turtle HJ, Zykaj B (2015) Hedge fund crowds and mispricing. Manag Sci 62:764–784Google Scholar
  49. Stein JC (2009) Presidential address: sophisticated investors and market efficiency. J Finance 64(4):1517–1548Google Scholar
  50. Yan P (2013) Crowded trades, short covering and momentum crashes. SSRN Working Papers. 2404272, Social Science Research Network, Inc. http://ssrn.com/abstract=2404272
  51. Yang C, Zhou L (2016) Individual stock crowded trades, individual stock investor sentiment and excess returns. N Am J Econ Finance 38:39–53Google Scholar
  52. Zhou L, Yang C (2019) Stochastic investor sentiment, crowdedness and deviation of asset prices from fundamentals. Econ Model 79:130–140Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Economics & ManagementSouth China Agricultural UniversityGuangzhouChina
  2. 2.School of Economics and Commerce, Finance and Security CenterSouth China University of TechnologyGuangzhouChina

Personalised recommendations