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.     

Dual Trading in Futures Markets

With dual trading, brokers trade both for their customers and for their own account. We study dual trading and find that customers who are less likely to be informed have higher expected profits with dual trading while customers who are more likely to be informed have higher expected profits without dual trading. We also examine the effects of frontrunning. We test the major empirical implications of our model. Consistent with the model, dual traders earn higher profits than non-dual traders, and customers of dual-trading brokers do better than customers of non-dual-trading brokers.     

The trades of NYSE floor brokers

This paper studies the contribution of NYSE floor brokers to the Exchange's agency auction market. Floor brokers represent 44%, specialists 11%, and system orders 45% of the value of all executed orders in our sample. We analyze how the cross-sectional distribution of floor broker trading depends on liquidity, block volume, on- and off-exchange competition, volatility, and order flow internalization. Floor brokers participate in large trades, primarily in liquid stocks, and they trade more when volatility is high. They provide two-sided liquidity to the market and often provide liquidity that would otherwise have been supplied by NYSE specialists.     

Intraday time and order execution quality dimensions

We examine intraday execution quality patterns on Nasdaq stocks using proprietary order-level data from a US broker dealer. Orders submitted midday execute slower than orders submitted around the open and close. However, midday orders have lower execution costs. Our results indicate that execution speed and execution cost exhibit offsetting intraday time-dependent patterns and these patterns appear to be induced by variations in informed trading levels. While some traders concentrate their trading activity around the open and close, others prefer to trade midday. Traders have varying preferences for when to trade, and offsetting patterns exist between speed and cost. These factors highlight the complexity in defining an optimal trading time, which, among other things, is dependent on the dimensional preferences of individual traders.     

The Determinants of Execution Costs in Short‐Term Money Markets

Prior research attributes the observed negative relation between execution costs and trade size in opaque markets to two factors—information asymmetry and broker‐client relationships. We provide evidence that a trader's ex ante transaction price information and the relationship traders have with their brokers are both significant determinants of a trader's execution costs in an opaque market; however, traders who establish strong relationships with their brokers will achieve a greater reduction in execution costs than traders with ex ante transaction price information. We also find evidence that trade size has little explanatory power after controlling for a trader's ex ante transaction price information and broker‐client relationships.     

Trader see,trader do: How do (small) FX traders react to large counterparties’ trades?

We show that information about the counterparty of a trade affects the future trading decisions of individual traders. The effect is such that traders tend to reverse their order flow in line with the better-informed counterparties. Informed traders primarily incorporate their own private as well as publicly available information into prices, whereas uninformed traders mainly magnify the effect of the informed. This pattern of interaction among traders extends to different order types: traders treat their own and others’ market orders as more informative than limit orders.     

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.     

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.     

Reputation Effects in Trading on the New York Stock Exchange

Theory suggests that reputations allow nonanonymous markets to attenuate adverse selection in trading. We identify instances in which New York Stock Exchange (NYSE) stocks experience trading floor relocations. Although specialists follow the stocks to their new locations, most brokers do not. We find a discernable increase in liquidity costs around a stock's relocation that is larger for stocks with higher adverse selection and greater broker turnover. We also find that floor brokers relocating with the stock obtain lower trading costs than brokers not moving and brokers beginning trading post‐move. Our results suggest that reputation plays an important role in the NYSE's liquidity provision process.     

Working Orders in Limit Order Markets and Floor Exchanges

We analyze limit order markets and floor exchanges, assuming an informed trader and discretionary liquidity traders use market orders and can either submit block orders or work their demands as a series of small orders. By working their demands, large market order traders pool with small traders. We show that every equilibrium on a floor exchange must involve at least partial pooling. Moreover, there is always a fully pooling (worked order) equilibrium on a floor exchange that is equivalent to a block order equilibrium in a limit order market.     

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.     

High‐Frequency Trading around Large Institutional Orders

Liquidity suppliers lean against the wind. We analyze whether high‐frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders. The alternative is HFTs trading with the wind, that is, in the same direction. We find that HFTs initially lean against these orders but eventually change direction and take positions in the same direction for the most informed institutional orders. Our empirical findings are consistent with investors trading strategically on their information. When deciding trade intensity, they seem to trade off higher speculative profits against higher risk of being detected and preyed on by HFTs.     

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 “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.     

Hide-and-Seek in the Market: Placing and Detecting Hidden Orders

This paper investigates why traders hide their orders and howother traders respond to hidden depth. Using a logit model,we provide empirical findings suggesting that traders use hiddenorders to manage both exposure risk and picking off risk. Usingprobit models, we show that hidden depth increases order aggressiveness.Our interpretation of this empirical evidence is threefold.First, hidden depth detection is possible and frequent. Second,when traders detecthidden volume at the best opposite uote,they strategically adjust their order submission to seize theopportunity for depth improvement. Third, traders' responsewhen hidden depth is detected suggests either that they do notassociate hidden orders with informed trading or that the riskof trading with an informed trader is widely offset by the opportunityfor depth improvement.     

Lifting the Veil: An Analysis of Pre-trade Transparency at the NYSE

We study pre‐trade transparency by looking at the introduction of NYSE's OpenBook service that provides limit‐order book information to traders off the exchange floor. We find that traders attempt to manage limit‐order exposure: They submit smaller orders and cancel orders faster. Specialists' participation rate and the depth they add to the quote decline. Liquidity increases in that the price impact of orders declines, and we find some improvement in the informational efficiency of prices. These results suggest that an increase in pre‐trade transparency affects investors' trading strategies and can improve certain dimensions of market quality.     

Trade Size Preference of Informed Traders in Indian Equity Markets

This study utilized high frequency transactions data to analyze the trade size preference of informed traders in Indian equity markets. It is observed that informed traders at an aggregate level adopt stealth trading strategy, wherein they prefer medium sized trades over large sized trades in order to camouflage their private information. However, the stealth trading behavior varies across stocks, wherein informed traders prefer more large sized trades on firms that are part of an index compared to non-index firms. Trading behavior also varies across other market conditions. It has been noted that informed traders prefer large sized trades during periods of high market thickness, negative returns, and low volatility. This study also provides a rationale for such varied behavior of informed traders.     

Do Prices Reveal the Presence of Informed Trading?

Using a comprehensive sample of trades from Schedule 13D filings by activist investors, we study how measures of adverse selection respond to informed trading. We find that on days when activists accumulate shares, measures of adverse selection and of stock illiquidity are lower, even though prices are positively impacted. Two channels help explain this phenomenon: (1) activists select times of higher liquidity when they trade, and (2) activists use limit orders. We conclude that, when informed traders can select when and how to trade, standard measures of adverse selection may fail to capture the presence of informed trading.     

Dealer attention,the speed of quote adjustment to information,and net dealer revenue

Using trade and quote data from the NYSE, we examine the relation between dealer attention, dealer revenue, and the probability of informed trade. We find that dealer revenue net of losses to better-informed traders in NYSE stocks is positively related to the speed at which quotes adjust to full information levels. The speed of quote adjustment is faster for stocks with greater dealer attention, as measured by a stock’s relative prominence at its post and panel location on the NYSE floor. The level of dealer attention in turn is positively related to a stock’s probability of information-based trading. The results are consistent with a theoretical model we derive in which dealers trade multiple securities and must optimally allocate their limited attention to monitoring order flow to minimize losses to better-informed traders.     

Hidden Liquidity: Some New Light on Dark Trading

Using a laboratory market, we investigate how the ability to hide orders affects traders’ strategies and market outcomes in a limit order book environment. We find that order strategies are greatly affected by allowing hidden liquidity, with traders substituting nondisplayed for displayed shares and changing the aggressiveness of their trading. As traders adapt their behavior to the different opacity regimes, however, most aggregate market outcomes (such as liquidity and informational efficiency) are not affected as much. We also find that opacity appears to increase the profits of informed traders but only when their private information is very valuable.