Summary:
The daily price limit rule with a range of 10%, which aims to dampen abnormal price fluctuations and mitigate price bubbles, has been strictly imposed in Chinese stock markets since 1996. The launch of the Sci-Tech Innovation Board on the Shanghai Stock Exchange on July 22, 2019, increased the price limit range from 10% to 20%. Following the gradually advanced market-oriented reform of trading mechanisms, such price limit relaxation was introduced to the ChiNext board on the Shenzhen Stock Exchange on August 24, 2020. Until now, few researchers have investigated whether price limit relaxation can enhance market efficiency without exacerbating market stability. Academic researchers document both benefits and costs to imposing a price limit. Supporters argue that a price limit helps to reduce overreaction by panicked investors, moderate price volatility, and increase market efficiency (e.g., Greenwald and Stein, 1991; Kim et al., 2013). Opponents, however, criticize that a price limit may result in trading interference, which delays the instant price discovery process and squeezes liquidity (e.g., De Long et al., 1990; Kim and Rhee, 1997; Chen et al., 2017). The above studies are either based on the change in the price limit policy in the 1990s or compare Chinese stock markets to other markets without price limit constraints, which signifies a lack of time effectiveness as Chinese stock markets have become more mature after 20 years of development. This paper uses the relaxation of the price limit on the ChiNext board as an exogenous shock and investigates the effect of price limit relaxation on market efficiency. Because the policy is imposed on all stocks traded on the ChiNext board without considering the pre-policy conditions of firm characteristics or market status, the shock to the price limit is purely exogenous, so that our setting is immune to most endogeneity issues in the literature. Specifically, we divide the full sample period into the pre-policy regime period, consisting of the 62 trading days before the policy effective date, and the post-policy regime period, consisting of the 64 days after the policy effective date (August 24, 2020). For our sample, we obtain transaction data for 742 stocks for each regime. We define the beta coefficient and R2 based on the market model as the proxy for market efficiency in each regime and compare their changes over the policy shock. The mean difference test suggests that the stock price is more sensitive to public market information and incorporates more idiosyncratic firm information after the policy change. Moreover, we define stocks on the ChiNext board as the treatment group and stocks on the PSM-matched SME board as the control group, and the difference-in-differences test shows that the stock price of the treatment group is more sensitive to public information and incorporate more firm-specific information. In summary, our evidence suggests that the relaxation of the price limit helps improve price efficiency at the market level. Following the literature evaluating the effect of the price limit (e.g., Kim and Rhee, 1997), we conduct an event study to provide a mechanism analysis. We compare abnormal returns, intraday volatility, and turnover around the price-limit-hitting events before and after the policy shock. When the price limit relaxes from 10% to 20%, we observe a significant decrease in abnormal returns, intraday volatility, and turnover following the event window. These findings demonstrate that price limit relaxation helps mitigate trading interference and prevent delaying trading behavior so that information can be more quickly incorporated into the stock price, resulting in less volatility spillover and delayed price discovery. Thus, our firm-level evidence identifies the direct mechanism through which price limit relaxation improves price efficiency. Moreover, we classify firms into low and high information transparency groups based on a comprehensive information transparency score and conduct a heterogeneity test based on the two subsamples. We find that firms with low information transparency benefit from more improvement in price efficiency at both market and firm levels. In addition, we exploit the high-frequency intraday data in 5-minute increments to estimate the magnet effect, volatility clustering, and spillover effect around the price-limit-hitting events before and after the policy shock. We show that price limit relaxation decreases the magnet effect, intraday volatility clustering, and volatility spillover, consistent with evidence from our market-and firm-level analyses. In conclusion, this study highlights that price limit relaxation can improve market performance by speeding up price discovery and mitigating market fluctuations. Policymakers could refer to our first-hand evidence to evaluate the effectiveness of the gradually advanced market-oriented reform on trading mechanisms. Our findings suggest that regulators could try to relax the price limit on stocks that satisfy certain liquidity requirements, which could further improve market efficiency and competitiveness.
顾明, 曾力, 陈海强, 倪博. 交易限制与股票市场定价效率——基于创业板涨跌幅限制放宽的准自然实验研究[J]. 金融研究, 2022, 509(11): 189-206.
GU Ming, ZENG Li, CHEN Haiqiang, NI Bo. Trading Restrictions and Stock Market Price Efficiency: AQuasi-Natural Experiment Based on the Registration System of the ChiNext Board. Journal of Financial Research, 2022, 509(11): 189-206.
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