This article develops a theoretical model to explain the permanent price impact asymmetry between buyer- and seller-initiated block trades (the permanent price impact of buys is larger than that of sells). The model shows how the trading strategy of institutional portfolio managers creates a difference between the information content of buys and sells. The main implication of the model is that the history of price performance influences the asymmetry: the longer the run-up in a stock's price, the less the asymmetry. The intensity of institutional trading and the frequency of information events affect the asymmetry differently depending on recent price performance.

We investigate how and why relative tick sizes influence traders’ order strategies, and how this affects liquidity provision in the market. Using unique NYSE data, we find that a larger relative tick size benefits high-frequency trading (HFT) market makers: they leave orders in the book longer, trade more aggressively, and have higher profit margins. In a tick-constrained (tick-unconstrained) environment, larger relative ticks result in greater (less) depth, which is consistent with greater adverse selection coming from increased undercutting of limit orders by informed HFT market makers. Received October 12, 2017; editorial decision August 21, 2018 by Editor Thierry Foucault.

We propose a mechanism that relates asset returns to the firm's optimal listing choice. We use a theoretical model to show that a stock will be more liquid when it is listed on a market where “similar” securities are traded. We empirically examine the implications of our model using New York Stock Exchange (NYSE) and Nasdaq securities. We find that the return patterns of stocks that switch markets become more similar to the return patterns of securities listed on the new market prior to the switch. Stocks that are eligible to switch but stay put are more similar to securities listed on their market than to securities listed on the other market. Our results suggest that managers make listing decisions that enhance the liquidity of their firms' stocks.

This article investigates the information content of signals about the identity of investors and their role in price formation. Whereas we document that investors use multiple brokers, broker identity is nevertheless a powerful signal about the identity of investors who initiate trades. The market also correctly processes this signal: the permanent price impact of orders coming from different brokers fits the information profile of the investors associated with these brokers. Our results suggest that an increase in the degree of anonymity may render order flow less informative, which could explain why the literature has documented liquidity improvements in exchanges that reduce transparency.

We examine product differentiation in the high-frequency trading (HFT) industry, where the “products” are secretive proprietary trading strategies. We demonstrate how principal component analysis can be used to detect underlying strategies common to multiple HFT firms and show that there are three product categories with distinct attributes. We study how HFT competition in each product category affects the market environment and present evidence that indicates how it influences the short-horizon volatility of stocks as well as the viability of trading venues. Received October 10, 2016; editorial decision September 30, 2017 by Editor Itay Goldstein. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Extending an empirical technique developed in Easley, Kiefer, and O'Hara (1996), (1997a), we examine different hypotheses about stock splits. In line with the trading range hypothesis, we find that stock splits attract uninformed traders. However, we also find that informed trading increases, resulting in no appreciable change in the information content of trades. Therefore, we do not find evidence consistent with the hypothesis that stock splits reduce information asymmetries. The optimal tick size hypothesis predicts that stock splits attract limit order trading and this enhances the execution quality of trades. While we find an increase in the number of executed limit orders, their effect is overshadowed by the increase in the costs of executing market orders due to the larger percentage spreads. On balance, the uninformed investors' overall trading costs rise after stock splits.

ABSTRACT This paper investigates the dynamic relation between net individual investor trading and short‐horizon returns for a large cross‐section of NYSE stocks. The evidence indicates that individuals tend to buy stocks following declines in the previous month and sell following price increases. We document positive excess returns in the month following intense buying by individuals and negative excess returns after individuals sell, which we show is distinct from the previously shown past return or volume effects. The patterns we document are consistent with the notion that risk‐averse individuals provide liquidity to meet institutional demand for immediacy.

Postcrisis bank regulations raised market-making costs for bank-affiliated dealers. We show that this can, somewhat surprisingly, improve overall investor welfare and reduce average transaction costs despite the increased cost of immediacy. Bank dealers in OTC markets optimize between two parallel trading mechanisms: market making and matchmaking. Bank regulations that increase market-making costs change the market structure by intensifying competitive pressure from nonbank dealers and incentivizing bank dealers to shift their business activities toward matchmaking. Thus, postcrisis bank regulations have the (unintended) benefit of replacing costly bank balance sheets with a more efficient form of financial intermediation.

ABSTRACT This paper provides evidence of informed trading by individual investors around earnings announcements using a unique data set of NYSE stocks. We show that intense aggregate individual investor buying (selling) predicts large positive (negative) abnormal returns on and after earnings announcement dates. We decompose abnormal returns following the event into information and liquidity provision components, and show that about half of the returns can be attributed to private information. We also find that individuals trade in both return‐contrarian and news‐contrarian manners after earnings announcements. The latter behavior has the potential to slow the adjustment of prices to earnings news.

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.