Research on Information-Driven Trades in China

Research on Information-Driven Trades in China

Juan Tao, Dongqi Sun, Yingying Wu
Copyright: © 2022 |Pages: 21
DOI: 10.4018/JGIM.299326
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Abstract

The authors examine the information-driven trades and informed traders' order size strategies in China's stock market. They find the aggregate U-shaped informed trading is not only explained by the time-of-day effect but is also related to the order size strategy, which is shown by intraday variations in the composition of small, medium, and large trades. The evidence of information predictability from early morning to market close and from late afternoon to the next day provides additional insights into the intraday informed trading pattern. They identify the non-negligible price impact (PI) of large trades and propose a modified model, VDPIN-PI, which better captures the trades with information advantage compared to the baseline model.
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1. Introduction

By examining information driven trades and trading strategies, this study unveils the information transmission and dissemination in China’s stock market. At the time when China gradually opens up the capital market (Ge et al., 2020) by introducing the Qualified Foreign Institutional Investor (QFII), RMB Qualified Foreign Institutional Investor (RQFII) and Stock Connect Programs, this research helps prospective international investors to better understand the China’s market, where the issue of information asymmetry is perceived to be more severe compared to more developed markets. The main cause of asymmetric information may include information leakage, superior forecasting of public information of some traders or their proprietary information collection.

One well-documented phenomenon about informed trades is that they concentrate at the opening, and sometimes the closing, period of the exchange (Madhavan et al., 1997; Barclay and Hendershott, 2003). Admati and Pfleiderer (1988) argue that, since the market opening and close are distinguished by the fact that they fall just after and before the exchange is closed, respectively, they may cause increased trading volume because of a rush to trade by informed and liquidity traders. Further, Gao et al. (2018) suggest that the intraday return predictability can be partially caused by late-informed trading near the market close to avoid overnight risk. Another strand of research focuses on the order submission strategies of informed traders. Kyle (1985) suggests that profit-maximising informed investors may attempt to camouflage their information and reduce the price impact by spreading trades over time. Barclay and Warner (1993) find that informed traders will concentrate on medium-sized trades, given their concerns such as costs related to regulatory requirements, delays and brokerage commission. In contrast, Barardehi et al. (2018) argue that aggressive market orders in large sizes may be used during high-liquidity times when the price impacts are small. The present study attempts to examine the trading strategies of informed traders in China’ s stock market, which is dominated by retail investors who are usually perceived to be irrational and impatient.1 To maximise their profits, do informed traders in China tend to behave cautiously and camouflage their trades or to trade aggressively, given the atmosphere of urgency and the likely consequence of high delay costs?

In this study, we examine the presence of informed trading and informed traders’ strategies concerning price impact and order size and offer three contributions to the related literature. First, we propose an intuitive method for examining the price impact of influential trades. Then we develop a modified informed trading measure by considering the price impact. Second, we investigate the intraday informed trades in China’s stock market and detect that these have an aggregated U-shape. We discover that in addition to the time-of-day effect, the overall U-shape stems mainly from variations in the trade size composition. Third, to gain more insights into the right-side peak of the U-shape, we analyse the unexpected return predictability. Thus we discover that the late afternoon informed trading is motivated not only by information retained from the early morning but also by privileged access to private information supposed to arrive the next day, which provides additional explanation for the high informed trading at the opening and near the market close. The information advantage of informed traders suggests their power to forecast future stock returns (Agrawal and Mittal, 2019), which explains the intraday return predictability documented in different markets and assets classes (Gao et al. (2018), Gao et al. (2019) and Zhang et al. (2020)). Our findings of intraday pattern of information driven trades also shed lights on information dissemination and price discovery in stock markets of developing countries.

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