Short-selling,margin-trading,and stock liquidity: Evidence from the Chinese stock markets

This paper examines the impacts of two forms of leveraged trading—margin trading and short selling—on the trading liquidity of individual stocks in China. We find that trading liquidity for relevant stocks generally improves after restrictions on leveraged trading are removed. However, margin trading and short selling have opposite impacts on liquidity. During ordinary periods, margin trading benefits liquidity, whereas short selling damages liquidity; however, during market downturns, their roles are reversed. We also provide evidence suggesting that short sellers are informed traders in China and that short selling reduces stock liquidity because of the increased risk of adverse selection faced by uninformed traders.     

Flying under the radar: The real effects of anonymous trading

Using unique data on TSX Attributed Trading and a new proxy of Tobin's Q that accounts for intangible capital (Peters and Taylor, 2017), we investigate the impact of anonymous trading (AT) on managers' ability to use feedback conveyed by stock prices to improve investment efficiency. We show that AT reduces investment efficiency and that both anonymous buyer-initiated and seller-initiated trades have comparable effects. The negative effect of AT on managerial learning from stock prices is significant only for tangible investments and when disagreement among anonymous traders is high. Taken together, our new evidence indicates that AT distorts investment sensitivity to Tobin's Q, plausibly because anonymity attracts additional (uninformed) liquidity trading, which negatively impacts the effectiveness of asset prices in aggregating private information and in revealing fundamentals.     

The “make or take” decision in an electronic market: Evidence on the evolution of liquidity

This paper uses experimental asset markets to investigate the evolution of liquidity in an electronic limit order market. Our market setting includes salient features of electronic limit order markets, as well as informed traders and liquidity traders. We focus on the strategies of the traders and how these are affected by trader type, characteristics of the market, and characteristics of the asset. We find that informed traders use more limit orders than do liquidity traders. Our main result is that liquidity provision shifts as trading progresses, with informed traders increasingly providing liquidity in markets. The change in the behavior of the informed traders seems to be in response to the dynamic adjustment of prices to information; they take (provide) liquidity when the value of their information is high (low). Thus, a market-making role emerges endogenously in our electronic markets and is ultimately adopted by the traders who are least subject to adverse selection when placing limit orders.     

Explaining Intraday Pattern of Trading Volume from the Order Flow Data

Based on a comprehensive order flow data from the Taiwan stock market, this study examines directly how the intraday pattern of trading volume is related to the trading behavior of both informed and uninformed traders. The results indicate that both informed and uninformed investors have a strong desire to place orders at the market open and the close. Most of the orders at the market open are conservative and hence are waiting orders for price priority. The findings show that intraday trading volume as well as the real orders from both types of investors are J-shaped. In addition, both information and liquidity trading can explain the intraday pattern of trading volume. However, the impact of liquidity trading on volume is slightly higher than that of information trading.     

Knowing me, knowing you: : Trader anonymity and informed trading in parallel markets

In this paper we empirically analyze whether the degree of trader anonymity is related to the probability of information-based trading. We use data from the German stock market where non-anonymous traditional floor based exchanges co-exist with an anonymous computerized trading system. We use an extended version of the Easley et al. (J. Finance 51 (1996) 1405) model that allows for simultaneous estimation for two parallel markets. We find that the probability of informed trading is significantly lower in the floor based trading system. We further document that the size of the spread and the adverse selection component are positively related to the estimated probabilities of information-based trading.     

Stock market dynamics with rational liquidity traders

In the Kyle (1985) finite horizon model of stock market dynamics with a trader who holds long-lived information, informed trading intensities rise with time, and the slopes of the equilibrium price schedules fall. This paper shows that this result depends crucially on the irrational liquidity trader assumption. We replace the irrational noise traders with a sequence of rational, risk averse, liquidity traders who receive endowment shocks to their holdings of the risky asset. We demonstrate that unless liquidity traders are sufficiently risk averse, the slope of equilibrium price schedule rises over time, while informed trading intensities fall. In particular, Kyle's result holds only when liquidity traders are so risk averse that they ‘over-rebalance’ their portfolio's holdings of the risky asset, so that their final holdings of the risky asset have the opposite sign of their initial position.     

What does PIN identify? Evidence from the T-bill market

The probability of informed trading (PIN) measure has been increasingly used in empirical research in finance. However, there is a growing debate as to whether PIN measures information-based or liquidity-based trading. We contribute to the discussion by estimating PIN using transaction data for one-month T-bills. Our PIN estimates exceed those reported for equities, despite it being unlikely that the probability of informed trading is higher in T-bills than equities. We conclude that PIN identifies trading clusters and that the source of the clustering depends on the economics of the market. The economics of the T-bill market suggest discretionary liquidity traders are the likely source of the clustering.     

基于面板数据的我国知情交易与股价信息含量研究

知情交易概率是指知情交易委托单占总交易委托单的比重,用于度量我国知情交易强度。R2代表公司回报率能被市场回报率解释的程度,R2越大,股价信息含量越低。在以往的研究基础上,利用面板数据来考察知情交易概率与股价信息含量的关系,发现知情交易概率越低,R2越高,股价信息含量越低。在控制了流动性与部分公司财务指标后,实证结果依然显示我国股价信息含量与知情交易概率存在正相关关系,说明我国知情交易者进行交易时,更有利于公司特质信息进入股票价格。     

VPIN,liquidity, and return volatility in the U.S. equity markets

We examine the volume-synchronized probability of informed trading metric (the VPIN flow toxicity metric, developed by Easley, Lopez de Prado, & O'Hara, 2012) as a real-time risk management tool for liquidity deteriorations in the U.S. equity markets. We find that VPIN provides information about market liquidity and stock return volatility on ex-ante basis. These results indicate that VPIN can be a useful risk-management tool for market makers, regulators and traders in the U.S. equity markets. We also document that VPIN is negatively associated with volume and number of trades, but positively associated with trade size and volume fragmentation. These findings suggest that VPIN indicates the adverse selection problem of liquidity providers by capturing the information in volume.     

Is faster or slower trading better? An examination of order type execution speed and costs

We examine order type execution speed and costs for US equity traders. Marketable orders that execute slower exhibit lower execution costs. Those who remove liquidity faster and pay higher trading costs transact in smaller size, spread trading across more venues, take more liquidity, and are better informed. Nonmarketable limit orders that execute slower exhibit greater adverse selection; and larger, uninformed traders who concentrate their trading in fewer venues submit them. Our findings suggest that slowing down the trading process, when faster options exist, can benefit certain market participants who seek to cross the bid–ask spread.     

Trade Disclosure,Information Learning and Securities Market Performance

In this paper we examine the effect of information disclosure on securities market performance when liquidity traders are able to acquire information about inside trading. We show that the bid-ask spread increases with the liquidity trader's learning efficiency, which is greater when trade information is disclosed. The bid-ask spread is always higher when trade information is not disclosed. However, the discrepancy between the bid-ask spreads with and without information disclosure narrows when the learning efficiency increases. We also show that the gains of the informed traders in a market without trade information disclosure are reduced in the presence of the liquidity trader's learning. Nevertheless, liquidity traders do not necessarily benefit from increased transparency. In particular, liquidity traders may face higher trading costs.     

A microstructure examination of trading activity following stock splits

In a study of 1,131 stock splits spanning the period 1983–1989 we observe an increase in the number of trades as well as a reduction in the mean trade size following the split. Combined with earlier reported findings of an increase in the number of shareholders postsplit, we conclude that the number of liquidity traders increases after a split. We confirm the previously observed increase in the bid-ask spread following a split, and upon decomposition of the spread find an increase in its adverse selection component in the postsplit period. This is consistent with the finding by Brennan and Hughes (1991) of an increase in the number of analysts following a stock after a split. Further, observing a decrease in market depth following a split we determine that Kyle-type models incorporating diverse private information for informed traders most correctly describe the nature of security trading. Since this decrease in postsplit market depth is not related to the trading volume or the split factor, we reject price correction explanations for stock splits.     

Informed Futures Trading and Price Discovery: Evidence from Taiwan Futures and Stock Markets

This article focuses on the information effects between the futures market and its spot market. Intraday data are used to investigate the lead-lag relationships between the returns and trading activity of Taiwan stock index futures and the spot returns. We focus on the transmission direction and the sources of information. Consistent with most previous studies, our results show that other than the contemporaneous relationship predicted by carry-cost theory and efficient market theory, futures returns significantly lead spot returns, which implies that informed trades may occur in the futures market. Using private transaction information, net open buy, as a proxy for futures trading activity and distinguishing different types of futures traders, we find that foreign institutional traders are the major source of informed trades because their trading has predictive power for future movements in both spot and futures prices. Traders in other categories are information laggards.     

Strategic Trading When Agents Forecast the Forecasts of Others

We analyze a multi-period model of trading with differentially informed traders, liquidity traders, and a market maker. Each informed trader's initial information is a noisy estimate of the long-term value of the asset, and the different signals received by informed traders can have a variety of correlation structures. With this setup, informed traders not only compete with each other for trading profits, they also learn about other traders' signals from the observed order flow. Our work suggests that the initial correlation among the informed traders' signals has a significant effect on the informed traders' profits and the informativeness of prices.     

Subsidizing Liquidity: The Impact of Make/Take Fees on Market Quality

Facing increased competition over the last decade, many stock exchanges changed their trading fees to maker‐taker pricing, an incentive scheme that rewards liquidity suppliers and charges liquidity demanders. Using a change in trading fees on the Toronto Stock Exchange, we study whether and why the breakdown of trading fees between liquidity demanders and suppliers matters. Posted quotes adjust after the change in fee composition, but the transaction costs for liquidity demanders remain unaffected once fees are taken into account. However, as posted bid‐ask spreads decline, traders (particularly retail) use aggressive orders more frequently, and adverse selection costs decrease.     

Does proprietary day trading provide liquidity at a cost to investors?

Capitalizing on the special case of Malaysia in which proprietary day traders (PDTs) are mandated to boost liquidity and the recent availability of trading data, this paper empirically examines the liquidity effect of proprietary day trading. Using daily data spanning October 2012 to June 2018, we find evidence that PDTs' trade volume is associated with higher aggregate liquidity in the Malaysian stock market, which can be attributed to the theoretical channel of intense competition among informed traders. However, such improved liquidity comes at a cost to investors, as proprietary day trading is found to be associated with higher conditional volatility and conditional skewness of closing percent quoted spreads. The former is due to the exchange-imposed immediacy for PDTs to close their open positions, whereas the latter can be attributed to the exclusive rights granted to PDTs to engage in intraday short selling.     

TRADING PATTERNS OF SMALL AND LARGE TRADERS AROUND STOCK SPLIT EX-DATES

We investigate the trading patterns of small and large traders around stock split ex-dates. Using the intraday transaction database for the Toronto Stock Exchange during 1983–89, we find that stock splits are associated with significant changes in trading patterns. Although stock splits appear to have little effect on the trading behavior of large traders (trade value of at least $100,000), they are associated with significant decreases in odd-lot trading and increases in small board-lot trading (trade value of less than $10,000). Although the liquidity premia decrease for all trade sizes, trade direction changes significantly from sell to buy after split ex-dates for all but the large trades, where the change is in the opposite direction. The significant increase in variances after split ex-dates is explained by various microstructure-related variables, and small (large) trades appear to be (de)stabilizing.     

并购重组前的知情交易行为研究

并购重组中基于内幕信息的知情交易行为既是监管重点,也是学术界关注的热点问题。本文以2006—2020年我国上市公司并购重组事件为样本,考察并购重组前的知情交易行为对并购公告收益的影响。研究发现：并购重组前的知情交易行为引发了主并公司股价的提前反应,从而降低了并购公告时的市场反应,这一现象是由内幕信息泄露引起,且内幕信息主要来源于包括员工在内的公司内部人,而非机构投资者。进一步分析表明,改善信息环境可以有效缓解并购重组的信息泄露问题,体现为知情购买交易的信息泄露效应受到分析师跟踪、审计质量和问询函制度的有效制约。本文研究深化了现有的并购重组内幕交易行为研究,为实施精准监管和防范内幕交易等政策提供了一定参考和依据。     

Competition among Trading Venues: Information and Trading on Electronic Communications Networks

This paper explores the competition between two trading venues, Electronic Communication Networks (ECNs) and Nasdaq market makers. ECNs offer the advantages of anonymity and speed of execution, which attract informed traders. Thus, trades are more likely to occur on ECNs when information asymmetry is greater and when trading volume and stock‐return volatility are high. ECN trades have greater permanent price impacts and more private information is revealed through ECN trades than though market‐maker trades. However, ECN trades have higher ex ante trading costs because market makers can preference or internalize the less informed trades and offer them better executions.     

Stealth trading: The case of the Tokyo Stock Exchange

The stealth trading hypothesis asserts that informed traders trade strategically by breaking up their orders so as to more easily hide among the liquidity traders. Using data for the Tokyo Stock Exchange (TSE), a pure order-driven market, we find evidence that price changes are driven by small- and medium-size trades, with small trades making the greatest contribution to price change relative to their contribution to trading volume. We also find that large trades explain a greater portion of the cumulative price change on high volatility days. Hence, our results support the stealth trading hypothesis for the TSE.