Earnings announcements,private information,and strategic informed trading

In this paper, we estimate and test a multi-period model of strategic informed trading developed by Foster and Viswanathan [Foster, F.-D., Viswanathan, S., 1996. Strategic trading when agents forecast the forecasts of others, J. Finance 51, 1437–1478]. We employ the GMM using intertemporal patterns of price, trading volume and market depth, leading up to the earnings announcements made by NYSE firms. We find that multiple informed traders with heterogeneous private signals trade prior to the announcements. In addition, by comparing the results from daily and intra-day estimations, we find that the number of informed traders increases while the intensity of liquidity trading decreases, and that the adverse selection problem becomes more pronounced as the announcements approach.     

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.     

The impact of competition and information on intraday trading

In a dynamic model of financial market trading multiple heterogeneously informed traders choose when to place orders. Better informed traders trade immediately, worse informed delay – even though they expect the market to move against them. This behavior generates intraday patterns with decreasing spreads, decreasing probability of informed trading (PIN), and increasing volume. We predict that policies that foster market entry improve the welfare of uninformed traders and lead to increased market participation by incumbent traders. Technological advances that lead to better signal processing also encourage market participation and increase volume but at the expense of uninformed traders’ welfare.     

Whose trades convey information? Evidence from a cross-section of traders

This paper contributes empirically to our understanding of informed traders. It analyzes traders’ characteristics in a foreign exchange electronic limit order market via anonymous trader identities. We use six indicators of informed trading in a cross-sectional multivariate approach to identify traders with high price impact. More information is conveyed by those traders’ trades which—simultaneously—use medium-sized orders (practice stealth trading), have large trading volume, are located in a financial center, trade early in the trading session, at times of wide spreads and when the order book is thin.     

Specialist participation and limit orders

We present a market microstructure model to examine specialist's strategic participation decisions in a security market where there are noise traders, limit order traders, an insider and a specialist. We argue that the specialist's participation rate depends on the depth of the limit book and its uncertainty. In particular, the specialist has incentives to trade against the market trend when the limit book depth is low and to trade with the market trend when the depth is high. Moreover, the specialist's participation rate is positively related to the limit book depth uncertainty and the asset price volatility, but is negative related to the average trading volume. We also discuss the specialist's participation strategies under the NYSE regulation that prohibits the specialist from trading with the market trend.     

Noise trading and the price formation process

This study proposes the dispersion in daily net initiated order flow across brokers as a proxy for the level of noise trading in a stock, and applies this proxy to test some basic implications of market microstructure theory. We use data from the Australian Stock Exchange, a computerized limit order market where price, quantity, and broker identity for each incoming order are shown on broker screens. We find daily movements in our noise measure are positively associated with trading volume and market depth, and negatively related to the bid-ask spread. We find monthly movements in our noise measure are negatively associated with the probability of informed trading, and positively correlated with the arrival rate of uninformed traders. We also find the sensitivity of stock prices to net initiated order flow decreases in the level of noise trading. In addition we find that, after controlling for noise trading, the sensitivity of stock prices to net initiated order flow is significantly greater on Mondays. These empirical results consistently support the implications of various models of market microstructure, suggesting that our proxy provides useful information as a daily measure of noise trading.     

Trade and the revelation of information through prices and direct disclosure

This article analyzes the volume of trade in a multiperiod noisyrational expectations model. When traders receive private signalsat the first trading date and are allowed a second round oftrade, two type of equilibria exist. In the first, traders donot learn about the average private signal from the second roundof trade, and all trade takes place at the first date. In thesecond, traders do learn from the second round, and trade thustakes places at both the first and second dates. The articlecharacterizes volume when a public signal is disclosed at thesecond date.     

Institutional stakeholdings and better-informed traders at earnings announcements

Utama and Cready [Utama, S., Cready, W.M., 1997. Institutional ownership, differential predisclosure precision and trading volume at announcement dates. Journal of Accounting and Economics 24, 129–150] use total institutional ownership to proxy for the proportion of better-informed traders, an important determinant of trading around earnings announcements. We argue that institutions holding small stakes cannot justify the fixed cost of developing private predisclosure information. Also, institutions with large stakes generally do not trade around earnings announcements since they are dedicated investors or face regulations that make informed trading difficult. However, institutions holding medium stakes have incentives to develop private predisclosure information and trade on it; we show that their ownership is a finer proxy for the proportion of better-informed traders at earnings announcements.     

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.     

Strategic trading, asymmetric information and heterogeneous prior beliefs

We develop a multi-period trading model in which traders face both asymmetric information and heterogeneous prior beliefs. Heterogeneity arises because traders agree to disagree on the precision of an informed trader's private signal. In equilibrium, the informed trader smooths out her trading on asymmetric information gradually over time, but concentrates her entire trading on heterogeneous beliefs toward the last few periods. As a result, the model's volume dynamics are consistent with the U-shaped intraday pattern at the close. Furthermore, the model predicts a positive autocorrelation in trading volume, and a positive correlation between trading volume and contemporaneous price volatility.     

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.     

The Effect of Sequential Information Arrival on Asset Prices: An Experimental Study

A complete understanding of security markets requires a simultaneous explanation of price behavior, trading volume, portfolio composition (ie., asset allocation), and bid-ask spreads. In this paper, these variables are observed in a controlled setting—a computerized double auction market, similar to NASDAQ. Our laboratory allows experimental control of information arrival—whether simultaneously or sequentially received, and whether homogeneous or heterogeneous. We compare the price, volume, and share allocations of three market equilibrium models: telepathic rational expectations, which assumes that traders can read each others minds (strong-form market efficiency); ordinary rational expectations, which assumes traders can use (some) market price information, (a type of semi-strong form efficiency); and private information, where traders use no market information. We conclude 1) that stronger-form market models predict equilibrium prices better than weaker-form models, 2) that there were fewer misallocation forecasts in simultaneous information arrival (SIM) environments, 3) that trading volume was significantly higher in SIM environments, 4) and that bid-ask spreads widen significantly when traders are exposed to price uncertainty resulting from information heterogeneity.     

The Relationship Among Market-Making Revenue, Payment for Order Flow, and Trading Costs for Market Orders

We study the division of market-making revenue among dealer, broker, and trader. When Knight Securities, a major Nasdaq dealer, interacts with market orders in actively traded stocks during the fourth quarter of 1996, we estimate that its revenue is $0.057 per share. Knight pays brokers at least $0.025 per share (44% of revenue) for orders. To examine whether brokers appear to share these payments with traders, we compare net trading costs (trade price net of commissions) for traders using brokers routing Knight orders with estimated net trading costs for traders using the only discount broker we can determine did not directly receive market-making revenue. We find that the net trading cost of the broker refusing order-flow payments does not dominate the net trading cost of all brokers selling order flow to Knight. This finding suggests that order-flow payments do not unambiguously harm traders and challenges the conclusions of extant studies using only trade prices to assess market quality.     

Individuals’ Trading Prior to Earnings Announcements

This paper investigates the relationship between individuals’ net trading and stock price movements before and after annual earnings announcements for the Taiwan Stock Exchange. We conduct an event study on the effects of pre‐event individual trade imbalances on pre‐ and post‐announcement abnormal returns. With a unique and comprehensive dataset, we accurately classify executed orders by aggressiveness of order price. The evidence indicates that while individuals, as a group, are not informed about impending earnings announcements, individuals who place aggressive orders are informed as their net trading coincides with contemporaneous and future stock returns. Aggressive individuals lose their edge during the financial crisis. More importantly, the advantage (disadvantage) for individuals who adopt aggressive (passive) orders weakens when foreign institutions own concentrated equity in firms. We also find that net individual trading contains information about abnormal returns that either past returns or volume does not subsume. Controlling for past returns, trading volume and volatility, or using an alternative measure of net individual trading does not change our conclusions.     

Information, Trading Demand, and Futures Price Volatility

We examine the relation between futures price volatility and trading demand by type of trader in the Standard & Poor's (S&P) 500-stock index futures market. We find that volatility covaries negatively with signed speculative demand shocks but is positively related to signed hedging demand shocks. No significant relation between volatility and demand shocks for small traders is found. Our results suggest that changes in positions of large hedgers destabilize the market, whereas changes in positions of large speculators stabilize volatility. Consistent with models with asymmetrically informed traders, we find that large speculators are likely to possess superior forecasting ability, large hedgers behave like positive feedback traders, and small traders are liquidity traders.     

Insider Trading after Repurchase Tender Offer Announcements: Timing versus Informed Trading

Abnormally high net insider selling is commonly observed after repurchase tender offer (RTO) announcements although, on average, firms experience positive abnormal returns in the years after the repurchases. We explore two potential explanations: liquidity trade timing and informed trading. Consistent with the notion that fixed price RTOs are more likely than Dutch-auction RTOs to signal undervaluation, the results suggest that insider selling after fixed price RTO announcements are driven largely by insiders who time their trades with the repurchase announcements. In contrast, selling after Dutch-auction RTOs seems to be driven primarily by informed traders who exploit mispricing associated with the repurchase announcements.     

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.     

Bid ask spread in a competitive market with institutions and order size

Large orders, particularly from institutions, are quite common these days and hence there is interest to know if institutional trading has any bearing on the price effect associated with large trades. Recent empirical studies contradict earlier evidence of negative price effect on selling large blocks and find no price effect associated with large trades. Existing theoretical framework suggests a monotonic and increasing adverse price effect for large trades, where the motivation for a large trade is private information. We model a trading system where pure information, information-liquidity, and pure liquidity traders trade small and large sizes. The pure information traders strategically choose an order size. Institutions trade only large sizes because of their low execution costs for large trades; they are information-liquidity traders whose ability to use an information signal to determine their trades is subject to a binding liquidity constraint. We show that in such a market a separating equilibrium where trade size is informative does not exist and hence there is no price effect for large trades. Trade size may be revealing only if there is a buy sell asymmetry (large buy size is not equal to large sell size) or the corresponding price effect is asymmetric (price effect due to a large buy is not equal to that of a large sell). Further for a pooling equilibrium to exist, where trade size is not informative, the width of the market denoted by the ratio of order size (large size/small size) needs to be small, while the shallowness (inverse depth) of the market denoted by the ratio between pure information and institutional trades and the information signal needs to be stronger (higher). Our results on bid and ask prices and spread confirm recent empirical evidence on price effect of large and institutional trades found in the literature.

The threshold effect in expected volatility: a model based on asymmetric information

This article develops theoretical insight into the thresholdeffect in expected volatility, which means that large shocksare less persistent in volatility than small shocks. The modeluses the Kyle-Admati-Pfleiderer setup with liquidity traders,informed traders, and a market maker. Information is modeledas a GARCH process. It is shown that the GARCH process for informationis transformed into a TARCH process (for 'threshold GARCH')for the market price changes. Working with information flowsallows one to derive implications for trading volume and marketliquidity which provide the basis for a more complete test ofthe model.     

News Trading and Speed

We compare the optimal trading strategy of an informed speculator when he can trade ahead of incoming news (is “fast”), versus when he cannot (is “slow”). We find that speed matters: the fast speculator's trades account for a larger fraction of trading volume, and are more correlated with short‐run price changes. Nevertheless, he realizes a large fraction of his profits from trading on long‐term price changes. The fast speculator's behavior matches evidence about high‐frequency traders. We predict that stocks with more informative news are more liquid even though they attract more activity from informed high‐frequency traders.