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.     

Microstructure-based manipulation: Strategic behavior and performance of spoofing traders

We examine how investors strategically spoof the stock market by placing orders with little chance of being executed, but which mislead other traders into thinking there is an imbalance in the order book. Using the complete intraday order and trade data of the Korea Exchange (KRX) in a custom data set identifying individual accounts, we find that investors strategically placed spoofing orders which, given the KRX's order-disclosure rule at the time, created the impression of a substantial order book imbalance, with the intent to manipulate subsequent prices. This manipulation, which made use of specific features of the market microstructure, differs from previously studied forms of manipulation based on information or transactions. Roughly half of the spoofing orders were placed in conjunction with day trading. Stocks targeted for manipulation had higher return volatility, lower market capitalization, lower price level, and lower managerial transparency. We also find that spoofing traders achieved substantial extra profits. The frequency of spoofing orders decreased drastically after the KRX altered its order-disclosure rule.     

Characteristics of the order flow through an electronic open limit order book

We estimate and examine certain characteristics of the order flow through an electronic open limit order book, using order (not trade) data. In doing this, we bring out new evidence on order flow from a market with microstructure different from that of the NYSE. We find that the proportion of informed orders is less than 10%, lower than previous estimates. Informed traders choose smaller orders than uninformed traders, but do not materially differ in their choice of limit or market orders. The proportion of informed investors is similar between good and bad news days. Finally, there are U-shaped intraday patterns in order arrival, and the information content of the order flow appears to follow this pattern across the day.     

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.     

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.     

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.     

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.     

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.     

Can order exposure be mandated?

In this paper, we examine whether the hidden portion of limit orders represents depth that would be revealed if traders were not allowed to hide it, and the associated market quality implications. Specifically, we examine the decisions by the Toronto Stock Exchange to first abolish the use of hidden limit orders in 1996, and then reintroduce them in 2002. We find that quoted depth does not change following either decision, suggesting that the hidden portion of orders represents depth that would otherwise not be exposed. Using confidential order data for the period following the reintroduction of hidden limit orders, we find that total inside depth increases. For both events, volume does not change and the usage of the limit order book increases if hidden limit orders are allowed. This suggests that if traders are required to expose their orders they will not exit the market, but instead will switch to using market orders. We also find evidence to suggest that informed traders use hidden limit orders to minimize price impact if the probability of non-execution is small.     

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.     

透明度变化对股票市场投资者委托单提交行为和交易成本影响研究

基于2003年12月8日沪深交易所交易前市场透明度改革背景,本文利用一家营业部的投资者报价和交易数据,研究同一个机构投资者和散户投资者在透明度改革前后委托单提交激进程度的变化,以及这种变化对其完成交易的成本的影响。我们发现,透明度改革前后,机构投资者的委托单提交激进程度都显著大于散户投资者的委托单提交激进程度。透明度增加以后,机构投资者的委托单激进程度显著减少,而散户投资者的委托单提交激进程度增加。同时发现,透明度增加以后,机构投资者通过分拆委托单,增加交易次数,导致完成交易的时间增加,但价格影响力基本没有变化,散户投资者的成交时间和价格影响力有显著改善。     

Market transparency: who wins and who loses?

This study uses laboratory experiments to determine the effectsof trade and quote disclosure on market efficiency, bid-askspreads, and trader welfare. We show that trade disclosure increasesthe informational efficiency of transaction prices, but alsoincreases opening bid-ask spreads, apparently by reducing market-makers'incentives to compete for order flow. As a result, trade disclosurebenefits market makers at the expense of liquidity traders andinformed traders. We find that quote disclosure has no discernibleeffects on market performance. Overall our results demonstratethat the degree of market transparency has important effectsof market equilibria and on trader and market-maker welfare.     

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.     

1-share orders and trades

1-share trades are the most common odd lot trade size, accounting for 9.62% of all odd lot transactions and 3.65% of all trades on NASDAQ in 2012. While 50.41% of 1-share trades result from broken orders, 34.89% of 1-share trades are intentional. We provide substantial evidence that traders use 1-share trades to “ping” for hidden liquidity. In particular, our results indicate that 1-share trades are disproportionately aggressive and also execute against hidden liquidity more than any other odd lot trade size. We also find a relative increase in trading immediately following a 1-share trade. Our results are in line with Clark-Joseph (2014), who suggests that traders may use small, unprofitable trades to detect information from other traders. Specifically, 1-share trades represent the minimum cash outlay necessary to trade, while simultaneously producing the smallest possible effects on a market maker's inventory, and in turn, a security's price.     

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.     

Informed trading and order type

Each trader must choose between a limit order, a market order, or using a floor broker. We hypothesize that informed investors will: (1) concentrate their trading in floor broker orders and (2) sometimes trade patiently. Consistent with our hypotheses, empirical results suggest that most informed trading occurs through orders executed by floor brokers and that informed floor brokers are sometimes patient. Regardless of their patience, however, quote revisions following trade executions are consistent with the hypothesis that markets recognize that floor traders are more likely to be informed than other traders. As a result, informed trading moves equilibrium security values.     

Price Movement Effects on the State of the Electronic Limit‐Order Book

This paper investigates public‐trader order‐placement strategies by examining the relations between the state of the limit‐order book and previous price movements. There is support for an information effect, as traders become more aggressive in buying and more patient in selling after previous positive stock returns. The widening of the bid‐ask spread also causes traders to place less aggressive orders. However, there is no evidence of the options effect on limit‐order trading. This study also reveals that orders at the best quotes react faster and complete the adjustment earlier than orders that are far away from the best quotes.     

Traders’ choice between limit and market orders: evidence from NYSE stocks

In this paper, we examine a trader's order choice between market and limit orders using a sample of orders submitted through NYSE SuperDot. We find that traders place more limit orders relative to market orders when: (1) the spread is large, (2) the order size is large, and (3) they expect high transitory price volatility. A rise in informational volatility appears neither to increase nor decrease the placement of limit orders. We also find that a rise in lagged price volatility decreases the size of spread, which is driven by the increase in the placement of limit orders.     

Transparency and Liquidity: A Comparison of Auction and Dealer Markets with Informed Trading

Trading systems differ in their degree of transparency, here defined as the extent to which market makers can observe the size and direction of the current order flow. We investigate whether greater transparency enhances market liquidity by reducing the opportunities for taking advantage of uninformed participants. We compare the price formation process in several stylized trading systems with different degrees of transparency: various types of auction markets and a stylized dealer market. We find that greater transparency generates lower trading costs for uninformed traders on average, although not necessarily for every size of trade.     

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.