Order dynamics: Recent evidence from the NYSE

We examine investor order choices using evidence from a recent period when the NYSE trades in decimals and allows automatic executions. We analyze the decision to submit or cancel an order or to take no action. For submitted orders, we distinguish order type (market vs. limit), order side (buy vs. sell), execution method (auction vs. automatic), and pricing aggressiveness. We find that the NYSE exhibits positive serial correlation in order type on an order-by-order basis, which suggests that follow-on order strategies dominate adverse selection or liquidity considerations at a moment in time. Aggregated levels of order flow also exhibit positive serial correlation in order type, but appear to be non-stationary processes. Overall, changes in aggregated order flow have an order-type serial correlation that is close to zero at short aggregation intervals, but becomes increasingly negative at longer intervals. This implies a liquidity exhaustion–replenishment cycle. We find that small orders routed to the NYSE's floor auction process are sensitive to the quoted spread, but that small orders routed to the automatic execution system are not. Thus, in addition to foregoing price improvement, traders selecting the speed of automatic executions on the NYSE do so with little regard for the quoted cost of immediacy. As quoted depth increases, traders respond by competing on price via limit orders that undercut existing bid and ask prices. Limit orders are more likely and market sells are less likely late in the trading day. These results are helpful in understanding the order arrival process at the NYSE and have potential applications in academics and industry for optimizing order submission strategies.     

Can Brokers Have It All? On the Relation between Make‐Take Fees and Limit Order Execution Quality

We identify retail brokers that seemingly route orders to maximize order flow payments, by selling market orders and sending limit orders to venues paying large liquidity rebates. Angel, Harris, and Spatt argue that such routing may not always be in customers’ best interests. For both proprietary limit order data and a broad sample of trades from TAQ, we document a negative relation between several measures of limit order execution quality and rebate/fee level. This finding suggests that order routing designed to maximize liquidity rebates does not maximize limit order execution quality and thus brokers cannot have it all.     

Correlated Trading and Returns

A German broker's clients place similar speculative trades and therefore tend to be on the same side of the market in a given stock during a given day, week, month, and quarter. Aggregate liquidity effects, short sale constraints, the systematic execution of limit orders (coordinated through price movements) or the correlated trading of other investors who pick off retail limit orders do not fully explain why retail investors trade similarly. Correlated market orders lead returns, presumably due to persistent speculative price pressure. Correlated limit orders also predict subsequent returns, consistent with executed limit orders being compensated for accommodating liquidity demands.     

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.     

Is faster or slower trading better? An examination of order type execution speed and costs

We examine order type execution speed and costs for US equity traders. Marketable orders that execute slower exhibit lower execution costs. Those who remove liquidity faster and pay higher trading costs transact in smaller size, spread trading across more venues, take more liquidity, and are better informed. Nonmarketable limit orders that execute slower exhibit greater adverse selection; and larger, uninformed traders who concentrate their trading in fewer venues submit them. Our findings suggest that slowing down the trading process, when faster options exist, can benefit certain market participants who seek to cross the bid–ask spread.     

Upstairs Market for Principal and Agency Trades: Analysis of Adverse Information and Price Effects

This paper directly tests the hypothesis that upstairs intermediation lowers adverse selection cost. We find upstairs market makers effectively screen out information-motivated orders and execute large liquidity-motivated orders at a lower cost than the downstairs market. Upstairs markets do not cannibalize or free ride off the downstairs market. In one-quarter of the trades, the upstairs market offers price improvement over the limit orders available in the consolidated limit order book. Trades are more likely to be executed upstairs at times when liquidity is lower in the downstairs market.     

Depth improvement and adjusted price improvement on the New York stock exchange

Traditional price improvement improperly assesses large orders’ execution quality by ignoring additional liquidity depth-exceeding orders receive at the quoted price and viewing orders that “walk the book” as “disimproved”. Ignoring this additional liquidity is particularly problematic when assessing execution quality in markets with significant non-displayed liquidity. To correct this deficiency, we modify the price benchmark used to determine whether an order is price improved by making the benchmark a function of the order's size relative to the quoted depth. We document that the differences between conventional price improvement and our measure, adjusted price improvement, can be dramatic and show that the difference depends on trading volume, stock price, and volatility.     

Lot Size Constraints and Market Quality: Evidence from the Borsa Italiana

Trading venues often impose a minimum lot size (minimum trade unit [MTU]) to facilitate order execution. We document changes in market quality associated with the reduction of the MTU to one share on the Italian stock exchange, the Borsa Italiana. We observe a substantial improvement in liquidity, with an average decrease in the relative spread of 10.2%, and more significant improvements for those firms for which the MTU constraint was more binding. We also show that the improvement in liquidity is mainly driven by a reduction in adverse selection; that informational efficiency is not significantly affected; and there is an increase in retail trading. We interpret our findings in light of a model of asymmetric information in which the MTU affects traders’ choice of order size.     

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.     

On the hidden side of liquidity

This article deals with the informativeness of iceberg orders, also known as hidden limit orders (HLOs). Namely, we analyze how the market reacts when the presence of hidden volume in the limit order book is revealed by the trading process. We use high-frequency book and transaction data from the Spanish Stock Exchange, including a large sample of executed HLOs. We show that just when hidden volume is detected, traders on the opposite side of the market become more aggressive, exploiting the opportunity to consume more than expected at the best quotes. However, neither illiquidity nor volatility increases in the short term. Furthermore, the detection of hidden volume has no relevant price impact. Overall, our results suggest that market participants do not attribute any relevant information content to the hidden side of liquidity.     

On the origin of power-law tails in price fluctuations

We analyse large stock price changes of more than five standard deviations for (i) TAQ data for the year 1997 and (ii) order book data from the Island ECN for the year 2002. We argue that a large trading volume alone is not a sufficient explanation for large price changes. Instead, we find that a low density of limit orders in the order book, i.e. a small liquidity, is a necessary prerequisite for the occurrence of extreme price fluctuations. Taking into account both order flow and liquidity, large stock price fluctuations can be explained quantitatively.     

Order Preferencing and Market Quality on U.S. Equity Exchanges

We present a detailed view of market quality in the presenceof preferencing arrangements. A unique dataset provides theopportunity to measure trading costs of marketable orders andfill rates and ex post costs of limit orders across tradingvenues. For market orders, we find the primary exchange providesthe lowest execution costs. However, the preferencing exchangesare no worse than, and in most cases better than, the nonpreferencingregional exchanges. For limit orders, the regionals executelimit orders more frequently than the primary market and withan ex post execution cost that is not very different from theprimary market.     

Limit Orders, Depth, and Volatility: Evidence from the Stock Exchange of Hong Kong

We investigate the role of limit orders in the liquidity provision in a pure order-driven market. Results show that market depth rises subsequent to an increase in transitory volatility, and transitory volatility declines subsequent to an increase in market depth. We also examine how transitory volatility affects the mix between limit orders and market orders. When transitory volatility arises from the ask (bid) side, investors will submit more limit sell (buy) orders than market sell (buy) orders. This result is consistent with the existence of limit-order traders who enter the market and place orders when liquidity is needed.     

Order Imbalance in the FTSE Index Futures Market: Electronic versus Open Outcry Trading

Abstract:  This study examines trading activities before and after the transfer of the FTSE 100 index futures contract from open outcry to electronic trading. Daily order imbalance exhibits strong serial persistence in the electronic limit order market, but not in open-outcry trading. Both excess buying and selling reduce liquidity. In the electronic venue, prior market movements barely affect investors' buying or selling decisions. Excess buy orders do not generate any price impact, but sell orders do. Positive imbalances are more strongly autocorrelated than negative imbalances. No trading elements, such as order imbalance, volume, or open interest, are associated with volatility. Moreover, excess buying decreases volatility. Such evidence suggests that the development and growth of electronic trading has changed the dynamics of trading activities in many important ways.     

Optimal liquidation in dark pools

We consider a large trader liquidating a portfolio using a transparent trading venue with price impact and a dark pool with execution uncertainty. The optimal execution strategy uses both venues continuously, with dark pool orders over-/underrepresenting the portfolio size depending on return correlations; trading at the traditional venue is delayed depending on dark liquidity. Pushing up prices at the traditional venue while selling in the dark pool might generate profits. If future returns depend on historical dark pool liquidity, then sending orders to the dark pool can be worthwhile simply to gather information.     

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.     

Does the Limit Order Routing Decision Matter?

We examine the impact deciding to route limit orders away fromthe New York Stock Exchange (NYSE) has on three dimensions ofexecution quality with methodologies controlling for marketconditions and order submission strategies. Overall differencesin limit order execution quality between regional stock exchangesand the NYSE are small, suggesting that the order routing decisionmay not affect retail limit order traders substantively. Conditioningon the distance between the limit order's price and prevailingquotes, however, reveals systematic differences in executionquality. This implies that brokers can strategically route limitorders to improve retail limit order execution quality.     

A MICROSTRUCTURE ANALYSIS OF THE LIQUIDITY IMPACT OF OPEN MARKET REPURCHASES

We examine the liquidity impact of Canadian open market repurchases and find that spreads are smaller and depths greater during repurchase programs (as compared to the prerepurchase period) and on repurchase days (as compared to nonrepurchase days). We examine the types of orders used by repurchasing companies and find that all repurchase orders are limit orders and more than 70% of these unambiguously add liquidity to the limit order book. The improved liquidity is consistent with U.S. research but different from results from other markets. We attribute the difference to an uptick restriction that limits the aggressiveness of North American repurchases.     

The informational effect and market quality impact of upstairs trading and fleeting orders on the Australian Securities Exchange

This paper investigates the informational effect of trading and market segmentation on the Australian Securities Exchange (ASX) paying particular attention to the recent phenomenon: fleeting orders.¹ Confirming theoretical predictions, this study finds that permanent price effect (PPE) is significantly greater in the central limit order book (LOB) than in the upstairs market and that less informed institutional trades are routed to the upstairs market. It also finds that a well functioning upstairs market often results in lower transaction cost, higher volatility and larger trade size on the ASX. In the context of fleeting orders specifically, it finds the informational effect and market quality impact of upstairs market to be weaker after removing fleeting orders, which subsequently leads to the conclusion that recently introduced execution algorithms, which leave a trace of fleeting orders, often result in lower PPE and are mostly used my uninformed liquidity traders.     

The use of undisclosed limit orders on the Australian Stock Exchange

This paper investigates the use of undisclosed limit orders on the Australian Stock Exchange (ASX). Our findings suggest that undisclosed limit orders are used to reduce the option value of limit orders. We find no evidence that undisclosed limit orders are more frequently used by informed traders than disclosed limit orders. The effects of recent changes in undisclosed order regulation are also examined. We find that the enhancement in pre-trade transparency, through tightening the undisclosed order regulation in October 1994, resulted in a significant decline in trading volume. The impact of the second regulation change in October 1996, which further tightened undisclosed order regulation, resulted in a less significant trading volume reduction.