Hybrid markets, tick size and investor trading costs

This paper shows how the tick size affects equilibrium outcomes in a hybrid stock market such as the NYSE that features both a specialist and a limit order book. Reducing the tick size facilitates the specialist's ability to step ahead of the limit order book, resulting in a reduction in the cumulative depth of the limit order book at prices above the minimum tick. If market demand is price-sensitive, and there are costs of limit order submission, the limit order book can be destroyed by tick sizes that are either too small or too large. We show that trading cost is minimized at larger tick sizes for larger market orders, creating an incentive to submit smaller orders when tick size is reduced. With a smaller tick size, specialist participation increases and specialist profit increases slightly for small market orders, and considerably for large market orders.     

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.     

A Specialist's Quoted Depth and the Limit Order Book

By partitioning quoted depth into the specialist's contribution and the limit order book's contribution, the paper investigates whether specialists manage quoted depth to reduce adverse selection risk. The results show that both specialists and limit order traders reduce depth around information events, thereby reducing their exposure to adverse selection costs. Moreover, specialists' quotes may reflect only the limit order book on the side (or sides) of the market where they believe there is a chance of informed trading. Changes in quoted depth are consistent with specialists managing their inventory as well as having knowledge of the stock's future value.     

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.     

Liquidity determination in an order-driven market

We exploit full order level information from an electronic FX broking system to provide a comprehensive account of the determination of its liquidity. We not only look at bid-ask spreads and trading volumes, but also study the determination of order entry rates and depth measures derived from the entire limit order book. We find strong predictability in the arrival of liquidity supply/demand events. Further, in times of low (high) liquidity, liquidity supply (demand) events are more common. In times of high trading activity and volatility, the ratio of limit to market order arrivals is high but order book spreads and depth deteriorate. These results are consistent with market order traders having better information than limit order traders.     

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.     

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.     

SLIPPAGE AND THE CHOICE OF MARKET OR LIMIT ORDERS IN FUTURES TRADING

Retail futures traders face uncertainty regarding the price they will obtain when trading. This price "surprise," known as slippage, can be substantial. Using unique data from an introducing brokerage for Chicago Board of Trade (CBOT) wheat, corn, and soybean futures contracts, we quantify time-to-clear and the magnitude of slippage. We then identify factors that affect these trade quality measures. Finally, we analyze individual trader choice between market and limit orders and find that the likelihood of placing limit orders, where regulations protect traders from slippage, is greater when order and market characteristic indicate that adverse slippage is likely.     

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.     

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.     

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.     

Market or limit orders?

In this paper we investigate the problem of optimal order placement of an asset listed on an exchange using both market and limit orders in a simple model of market dynamics. We seek to understand under which settings it is optimal to place limit or market orders. Limit orders typically lower transaction costs but increase the risk of incomplete order execution, whereas market orders typically have higher transaction costs but are guaranteed to be executed. Rather than considering order book dynamics to determine if a limit order is executed we rely on price dynamics for this. We look at implementation shortfall in this setup with market impact of trading and propose a dynamic program to find the optimal placement of both market and limit orders for risk-neutral and risk-averse traders. With this we find a bound on the expected cost of trading and show that a trader who behaves optimally should always expect to pay less to trade less. We then solve the dynamic program numerically and examine optimal order placement strategies. We find that the decision between market and limit orders is sensitive to price volatility, risk aversion, and trading costs.     

The specialist's discretion: stopped orders and price improvement

When a market order arrives, the NYSE specialist can offer aprice one tick better than the limit orders on the book andtrade for his own account. Alternatively, the specialist can'stop' the market order, which means he guarantees executionat the current quote but provides the possibility of price improvement.My model shows that specialists can use stops to sample thefuture order flow before making a commitment to trade. I presentempirical evidence that both stops and immediate price improvementimpose adverse selection costs on limit order traders.     

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.     

Electronic limit order book and order submission choice around macroeconomic news

We investigate the dynamics of the displayed part of the Island ECN limit order book for the equity-index-linked securities market around macroeconomic news releases. Our results indicate that the quality of the electronic market, measured by spread and depth, deteriorates during the releases. Furthermore, they show that traders appear to switch to more aggressive strategies as early as 3 min before an announcement and are most aggressive within the first minute after the announcement. Also, there is a noticeable difference in the response of the limit order book to the macroeconomic news during pre-market hours relative to regular trading hours.     

A dynamic limit order market with fast and slow traders

This paper considers the role of high-frequency trading in a dynamic limit order market. Fast traders? ability to revise their quotes quickly after news arrivals helps to reduce the inefficiency that is rooted in the risk of being picked off, which increases trade. However, their presence induces slow traders to strategically submit limit orders with a lower execution probability, thereby reducing trade. Because speed is a source of market power, it enables fast traders to extract rents from other market participants and triggers a costly arms race that reduces social welfare. The model generates a number of testable implications concerning the effects of high-frequency trading in limit order markets.     

Undisclosed orders and optimal submission strategies in a limit order market

Reserve orders enable traders to hide a portion of their orders and now appear in most electronic limit order markets. This paper outlines a theory to determine an optimal submission strategy in a limit order book, in which traders choose among limit, market, and reserve orders and simultaneously set price, quantity, and exposure. We show that reserve orders help traders compete for the provision of liquidity and reduce the friction generated by exposure costs. Therefore, total gains from trade increase. Large traders always benefit from reserve orders, whereas small traders benefit only when the tick size is large.     

Competition,signaling and non-walking through the book: Effects on order choice

We investigate the effects of competition and signaling in a pure order driven market and examine the trading patterns of agents when walking through the book is not allowed. Our results suggest that the variables capturing the cost of a large market order are not informative for an impatient trader under this market mechanism. We also document that the competition effect is not present only at the top of the book but persistent beyond the best quotes. Moreover, it dominates the signaling effect for both a limit order and a market order trader. Finally, we show that institutional investors’ order submission strategies are characterized by only a few pieces of the limit order book information. This is consistent with informed traders placing orders based on their own private valuations rather than the state of the book.     

Neoclassical finance,behavioral finance and noise traders: A review and assessment of the literature

While mainstream neoclassical finance ignores the role played by noise traders, a significant amount of empirical evidence is available to show that noise traders are active market participants and that their participation gives rise to market anomalies. Unlike neoclassical finance, behavioral finance allows for market inefficiency on the grounds that market participants are subject to common human errors that arise from heuristics and biases. In this paper we review the literature on the behavior of noise traders and analyze the consequences of their presence in the market, starting with a distinction between neoclassical finance and behavioral finance. We identify the market anomalies that provide evidence for the tendency of markets to trade at irrational levels, demonstrate how noise trading is related to some market fundamentals, and describe the models used to quantify noise trader risk.     

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.