Does Market Manipulation Reduce the Information Efficiency of China's Stock Market？ Empirical Evidence from the Shanghai A-share Market's High-Frequency Trading Data
SUN Guangyu, LI Zhihui, DU Yang, WANG Jin
School of Finance, Zhejiang Gongshang University;
School of Economics, Nankai University;
Research Institute of Bank of China;
CIB Fund Management Co., Ltd
Summary:
Tremendous increases in scale have been achieved in the development of China's A-share market over the past 30 years. At the end of 2020, there were 4,154 listed companies in the A-share market, and the total value of the market was 80 trillion yuan. This equates to greater than 70% of China's 2020 GDP, meaning that the A-share market is the world's second largest stock market, after that of the United States. However, the frequent abnormal fluctuations that have occurred in the A-share market indicate that the quality of the market is not high. In particular, there have been continual illegal transactions in the stock market in recent years:China Securities Regulatory Commission reports that the illegal profits from market manipulation in 2020 totaled 416 million yuan. Clearly, such occurrences severely damage the legitimate rights and interests of investors and the healthy development of the capital market. To explore this illegal behavior from the perspective of stock market quality, we monitor and attempt to identify suspicious tail-market manipulation in China's stock market. Based on the results of this monitoring, we empirically analyze how market manipulation affects the information efficiency of China's stock market and suggest ways for regulatory authorities to improve market quality. Many studies explore the factors influencing information efficiency in the Chinese stock market. Recent studies explore these factors from the perspective of investors and find that institutional investors (Xin et al., 2018), foreign investors (Qinlin and Zhengfei, 2018), and investor sentiment (Yang et al., 2020; Xiong et al., 2020) are responsible for abnormal changes in information efficiency. However, scholars rarely analyze the relationship between market manipulation and information efficiency from the perspective of illegal traders. This is a crucial relationship to understand, as the capital advantage and shareholding advantage of market manipulators means that their manipulations have a profound effect on the formation of stock prices. In addition, market microstructure theory (O’Hara, 1995) holds that the process of formation of security prices is closely related to the type of traders involved. Thus, in the process of stock-price formation, market manipulators may either (i) play the role of informed traders, whereby they use information advantages to bring stock prices closer to their intrinsic values through value investment, which increases information efficiency, or (ii) play the role of uninformed traders, whereby they use capital advantages and shareholding advantages to speculate on stock prices to cause them to deviate from their intrinsic values, which decreases information efficiency. Therefore, it may be unclear how market manipulation affects information efficiency. Accordingly, in this paper, we explore whether market manipulation is necessarily harmful and the mechanism by which market manipulation affects information efficiency. Specifically, we use the daily high-frequency trading data of the Shanghai A-share market from 2013 to 2018 as a research sample. Then, based on the abnormal characteristics of stock-trading indicators in this sample, we construct a model to identify tail-trading manipulation and empirically test the effect of market manipulation on the information efficiency of stock prices. From these investigations, we obtain the following findings. (1) Market manipulation has an adverse effect on information efficiency, primarily via abnormal changes in stock liquidity and volatility after market manipulation. These findings remain stable after controlling endogeneity. (2) Manipulation has less adverse effects on the information efficiency when the enterprise is state-owend or have a high quality of information disclosure. Our findings on the adverse effects of market manipulation on information efficiency indicate that financial regulatory authorities should improve market-monitoring and early-warning systems, and increase penalties for violations.
孙广宇, 李志辉, 杜阳, 王近. 市场操纵降低了中国股票市场的信息效率吗——来自沪市A股高频交易数据的经验证据[J]. 金融研究, 2021, 495(9): 151-169.
SUN Guangyu, LI Zhihui, DU Yang, WANG Jin. Does Market Manipulation Reduce the Information Efficiency of China's Stock Market？ Empirical Evidence from the Shanghai A-share Market's High-Frequency Trading Data. Journal of Financial Research, 2021, 495(9): 151-169.
Aggarwal, R. K., and G. Wu, 2006, “Stock Market Manipulations”, Journal of Business, 79(4):1915～1953.
[29]
Aitken, M. J., et al., 2015, “Market Fairness: The Poor Country Cousin of Market Efficiency”, Journal of Business Ethics, 10(2):1～19.
[30]
Atanasov, V., et al.,2015, “ Financial Intermediaries in the Midst of Market Manipulation:Did They Protect the Fool or Help the Knave？”, Journal of Corporate Finance, 34(1):210～234.
[31]
Bagehot ,W. ,1971, “The Only Game in Town”, Financial Analysts Journal, 27(2):12～14.
[32]
Baker ,S. R., N. Bloom, and S. J.Davis, 2016, “Measuring Economic Policy Uncertainty”, Quarterly Journal of Economics, 131(4) : 1593～1636.
[33]
Ben,D., I., F. Franzoni, A. Landier, et al, 2013, “Do Hedge Funds Manipulate Stock Prices？” Journal of Finance, 68(6):2383～2434.
[34]
Black, F., 1988, “An Equilibrium Model of the Crash”, NBER Macroeconomics Annual, 3(5): 269～275.
[35]
Boehmer, E. and J. Wu, 2012,“Short Selling and the Price Discovery Process”, Review of Financial Studies, 26(2): 287～322.
[36]
Bris, A. , W. N. Goetzmann, and N. Zhu, 2007, “Efficiency and the Bear: Short Sales and Markets Around the World”, Journal of Finance ,62(3):1029～1079.
[37]
Carhart, M. M., et al., 2002, “Leaning for The Tape: Evidence of Gaming Behavior in Equity Mutual Funds”, Journal of Finance, 57(2):661～693.
[38]
Chamberlain, T. W., and C. C. Y. Kwan, 1989, “Expiration-Day Effects of Index Futures and Options: Some Canadian Evidence”, Financial Analysts Journal, 45(5):67～71.
[39]
Chordia, T., et al. , 2008, “Liquidity and Market Efficiency” , Journal of Financial Economics, 87(2):249～268.
[40]
Comerton-Forde, C., and T. J. Putnins, 2011, “Measuring Closing Price Manipulation”, Journal of Financial Intermediation, 20(2):135～158.
[41]
Copeland,T. E., and D. Galai , 1983, “Information Effects on the Bid-ask Spread”, Journal of Finance, 38(5):1457～1469.
[42]
Easley, D., and M. O'Hara, 1987, “Price, Trade Size, and Information in Securities Markets”, Journal of Financial Economics, 19(1):69～90.
[43]
Easley, D., and M. O'Hara, 1992, “Time and the Process of Security Price Adjustment”, Journal of Finance,47(2):577～605.
[44]
Foucault T.,1998, “Order Flow Composition and Trading Costs in A Dynamic Limit Order Market”, Journal of Financial Markets, 1817(2):99～134.
[45]
Glosten, L. R., and P. R. Milgrom , 1985, “ Bid,Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders”, Journal of Financial Economics, 14(1):71~100.
[46]
Hillion, P., and M. Suominen, 2004, “The Manipulation of Closing Prices”, Journal of Financial Markets, 7(4):351～375.
[47]
Imisiker, S., and B. K. O. Tas, 2013, “Which Firms are More Prone to Stock Market Manipulation？”, Emerging Markets Review, 16(3):119～130.
[48]
Kim, O., and R. Verrecchia ,2001, “The Relation Among Disclosure, Returns, and Trading Volume Information”, Accounting Review, 76(4):633～654.
[49]
Kolasinski, A.C., A. Reed, and J. R. Thornock, 2013, “Can Short Restrictions Actually Increase Informed Short Selling？” , Financial Management, 42(1): 155～181.
[50]
Lee, I. H., 1998, “Market Crashes and Informational Avalanches”, Review of Economic Studies, 65(4): 741～759.
[51]
Lo, A. W., and A. C. Mackinlay, 1988, “Stock Market Prices Do not Follow Random Walks:Evidence from a Simple Specification Test”, Review of Financial Studies,1(1): 41～66.
[52]
Neupane, S., et al. , 2017, “Trade Based Manipulation: Beyond the Prosecuted Cases”, Journal of Corporate Finance, 42(2):115～130.
[53]
O'Hara, M., 1995, “Market Microstructure Theory”, Cambridge: Blackwell Publishers Inc.
[54]
Stoll, H. R. , and R. E. Whaley , 1987,“Program Trading and Expiration-day Effects”, Financial Analysts Journal,43(2):16～28.
[55]
Xu, N., K. C. Chan , and X. Jiang, 2013, “ Do Star Analysts Know More Firm-specific Information ？ Evidence from China . Journal of Banking & Finance, 37( 1):89～102.
