Liquidity distribution in the limit order book on the stock exchange of Thailand

The liquidity distribution, or the shape of the limit order book, influences trading behavior and choice of order submission by public liquidity suppliers. The present study seeks to discover whether liquidity providers are concerned about being picked off by informed traders, and whether they are less willing to supply liquidity at the market or demand higher price spreads. The results show that liquidity at the market is a small portion of total liquidity, and that firm size, minimum tick size, volatility, and trading volume play significant roles in determining the liquidity distribution within an order book.     

Modelling the buy and sell intensity in a limit order book market

In this paper, we model the buy and sell arrival process in the limit order book market at the Australian Stock Exchange. Using a bivariate autoregressive intensity model we analyze the contemporaneous buy and sell intensity as a function of the state of the market. We find evidence that trading decisions are both information as well as liquidity driven. Confirming predictions from market microstructure theory traders submit market orders by inferring from the recent order flow and the book with respect to upper and lower tail expectations as well as trading directions. However, traders also tend to take liquidity when the liquidity supply is high. Moreover, we find evidence that traders pay more attention to recent order arrivals and the current state of the order book than to the past order flow.     

High-frequency trading and stock liquidity: An intraday analysis

This paper studies the impact of high-frequency trading (HFT) on intraday liquidity of CAC40 stocks listed on Euronext. Spreads display an intraday L-shaped pattern, while quoted depth follows an inverse pattern: low at the open and increasing towards the end of the trading day. When liquidity demand is particularly high, there is a high rate of order cancellations attributable to high-frequency traders who use frequent order cancellations to strategically manage their limit orders and close positions near the market close. Using the generalized method of moments estimator, we generate strong evidence that greater intensity of HFT is associated with lower spreads and higher depth. The positive effect of HFT on liquidity is due mainly to decreased adverse selection costs arising from asymmetric information among market participants.     

Anonymity,liquidity and fragmentation

We examine the effects of the removal of broker identifiers from the central limit order book of the Australian Stock Exchange. We find that spreads and order aggressiveness decline, and order book depth increases, with the introduction of anonymous trading. This is consistent with the hypothesis that limit order traders are more willing to expose their orders when they can do so anonymously. Anonymous markets attract order flow from non-anonymous substitute markets, but this effect is only seen in large stocks. Our results suggest that exchanges operating in fragmented markets should consider anonymous trading to improve price competition and liquidity, although some of these benefits may be significant only if the stocks are sufficiently large and liquid.     

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.     

DOES SPEED MATTER? THE ROLE OF HIGH-FREQUENCY TRADING FOR ORDER BOOK RESILIENCY

We analyze limit order book resiliency following liquidity shocks initiated by large market orders. Based on a unique data set, we investigate whether high-frequency traders are involved in replenishing the order book. Therefore, we relate the net liquidity provision of high-frequency traders, algorithmic traders, and human traders around these market impact events to order book resiliency. Although all groups of traders react, our results show that only high-frequency traders reduce the spread within the first seconds after the market impact event. Order book depth replenishment, however, takes significantly longer and is mainly accomplished by human traders’ liquidity provision.     

Limit order books and trade informativeness

In the microstructure literature, information asymmetry is an important determinant of market liquidity. The classic setting is that uninformed dedicated liquidity suppliers charge price concessions when incoming market orders are likely to be informationally motivated. In limit order book (LOB) markets, however, this relationship is less clear, as market participants can switch roles, and freely choose to immediately demand or patiently supply liquidity by submitting either market or limit orders. We study the importance of information asymmetry in LOBs based on a recent sample of 30 German Deutscher Aktienindex (DAX) stocks. We find that Hasbrouck's (1991) measure of trade informativeness Granger causes book liquidity, in particular that required to fill large market orders. Picking-off risk due to public news-induced volatility is more important for top-of-the book liquidity supply. In our multivariate analysis, we control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity.     

Order Flow and Liquidity around NYSE Trading Halts

We study order flow and liquidity around NYSE trading halts. We find that market and limit order submissions and cancellations increase significantly during trading halts, that a large proportion of the limit order book at the reopen is composed of orders submitted during the halt, and that the market-clearing price at the reopen is a good predictor of future prices. Depth near the quotes is unusually low around trading halts, though specialists and/or floor traders appear to provide additional liquidity at these times. Finally, specialists appear to 'spread the quote' prior to imbalance halts to convey information to market participants.     

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.     

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.     

A market-clearing role for inefficiency on a limit order book

Limit order markets with stationary dynamics attract equal volumes of market orders and uncanceled limit orders, equalizing the supply and demand for liquidity and immediacy. To maintain this balance, market orders must share any benefit obtained by limit order traders from more efficient trading conditions, such as better order queuing policies. Therefore an efficient market places a low price on immediacy, producing small bid–ask spreads. Furthermore, when price-discreteness leads to a mainly constant spread, cutting the price tick raises surplus. This is modeled with a stochastic sequential game, using stationarity considerations to bypass direct analysis of traders’ intricate market forecasts.     

Fast and slow cancellations and trader behavior

We investigate how short-lived liquidity supply due to order cancellations affects the order-placement behavior of slow traders. When order cancellations increase, slow traders submit fewer and less aggressive orders. Both short- and long-lived liquidity supply have positive effects on the market overall, reducing spreads and increasing depth. We conclude that it is not necessary to require limit orders to have a minimum lifespan. We develop econometric and machine-learning frameworks that allow traders to predict whether a quote is likely to have a short or long life, increasing the ability of slow traders to respond strategically to changing order flow.     

Do Proprietary Algorithmic Traders Withdraw Liquidity during Market Stress?

We investigate the role of proprietary algorithmic traders in facilitating liquidity in a limit order market. Using order‐level data from the National Stock Exchange of India, we find that proprietary algorithmic traders increase limit order supply following periods of both high short‐term stock‐specific volatility and extreme stock price movement. Even following periods of high marketwide volatility, they do not decrease their supply of liquidity. We define orders from high‐frequency traders as a subclass of orders from proprietary algorithmic traders that are revised in less than three milliseconds. The behavior of high‐frequency trading mimics the behavior of its parent class. This is inconsistent with the theory that fast traders leave the market when stress situations arise, although their limit‐order‐supplying behavior becomes weaker when the increase in short‐term volatility is more informational than transitory. Agency algorithmic traders and nonalgorithmic traders behave opposite to proprietary algorithmic traders by reducing the supply of liquidity during stress situations. The presence of faster traders in the market possibly instills the fear of adverse selection in them. We document that the order imbalance of agency algorithmic traders is positively related to future short‐term returns, whereas the order imbalance of proprietary algorithmic traders is negatively related to future short‐term returns.     

Low-latency trading

We define low-latency activity as strategies that respond to market events in the millisecond environment, the hallmark of proprietary trading by high-frequency traders though it could include other algorithmic activity as well. We propose a new measure of low-latency activity to investigate the impact of high-frequency trading on the market environment. Our measure is highly correlated with NASDAQ-constructed estimates of high-frequency trading, but it can be computed from widely-available message data. We use this measure to study how low-latency activity affects market quality both during normal market conditions and during a period of declining prices and heightened economic uncertainty. Our analysis suggests that increased low-latency activity improves traditional market quality measures—decreasing spreads, increasing displayed depth in the limit order book, and lowering short-term volatility. Our findings suggest that given the current market structure for U.S. equities, increased low-latency activity need not work to the detriment of long-term investors.     

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.     

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.     

Optimal trading strategy and supply/demand dynamics

In this paper, we study how the intertemporal supply/demand of a security affects trading strategy. We develop a general framework for a limit order book market to capture the dynamics of supply/demand. We show that the optimal strategy to execute an order does not depend on the static properties of supply/demand such as bid–ask spread and market depth, it depends on their dynamic properties such as resilience: the speed at which supply/demand recovers to its steady state after a trade. In general, the optimal strategy is quite complex, mixing large and small trades, and can substantially lower execution cost. Large trades remove the existing liquidity to attract new liquidity, while small trades allow the trader to further absorb any incoming liquidity flow.     

Limit Order Book as a Market for Liquidity

We develop a dynamic model of a limit order market populatedby strategic liquidity traders of varying impatience. In equilibrium,patient traders tend to submit limit orders, whereas impatienttraders submit market orders. Two variables are the key determinantsof the limit order book dynamics in equilibrium: the proportionof patient traders and the order arrival rate. We offer severaltestable implications for various market quality measures suchas spread, trading frequency, market resiliency, and time toexecution for limit orders. Finally, we show the effect of imposinga minimal price variation on these measures.     

Optimal Dynamic Order Submission Strategies in Some Stylized Trading Problems

This study derives optimal dynamic order submission strategies for trading problems faced by three stylized traders: an uninformed liquidity trader, an informed trader and a value-motivated trader. Separate solutions are obtained for quote- and order-driven markets. The results provide practicable rules for how to trade small orders and how to manage traders. Transaction cost measurement methods based on implementation shortfall are proven to dominate other methods.
Since investors demand liquidity when they submit market orders and supply liquidity when they submit limit orders, the results improve our understanding of market liquidity. In particular, the models illustrate the role of time in the search for liquidity by characterizing the demand for and supply of immediacy.     

Technology and liquidity provision: The blurring of traditional definitions

Limit orders are usually viewed as patiently supplying liquidity. We investigate the trading of one hundred Nasdaq-listed stocks on INET, a limit order book. In contrast to the usual view, we find that over one-third of nonmarketable limit orders are cancelled within two seconds. We investigate the role these “fleeting orders” play in the market and test specific hypotheses about their uses. We find evidence consistent with dynamic trading strategies whereby traders chase market prices or search for latent liquidity. We show that fleeting orders are a relatively recent phenomenon, and suggest that they have arisen from a combination of factors that includes improved technology, an active trading culture, market fragmentation, and an increasing utilization of latent liquidity.