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.     

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.     

The Price of Immediacy

This paper models transaction costs as the rents that a monopolistic market maker extracts from impatient investors who trade via limit orders. We show that limit orders are American options. The limit prices inducing immediate execution of the order are functionally equivalent to bid and ask prices and can be solved for various transaction sizes to characterize the market maker's entire supply curve. We find considerable empirical support for the model's predictions in the cross-section of NYSE firms. The model produces unbiased, out-of-sample forecasts of abnormal returns for firms added to the S&P 500 index.     

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.     

Short Selling and Index Arbitrage Profitability: Evidence from the SGX MSCI and TAIFEX Taiwan Index Futures Markets

There are numerous impediments to market efficiency and index arbitrage in real capital markets, including the uptick rule on short selling, execution risk, market impact costs, regulatory barriers, and capital constraints. Adopting and relaxing the uptick restriction in the Taiwan stock market facilitated a study on whether adjustments in this restriction influence the efficiency and arbitrage of the Singapore Exchange Limited (SGX) and the Taiwan Futures Exchange (TAIFEX) index futures markets. This study examines the above issues using five-minute intraday transaction data and performs an ex post test of arbitrage, ex ante test of arbitrage, and regression analysis. Empirical results indicate that relaxing the uptick rule should improve market efficiency and facilitate long arbitrage, subsequently accelerating the adjustment to no-arbitrage bounds and helping to decrease ex post and ex ante mispricing and underpricing following the relaxation.     

Order submission strategies,liquidity supply,and trading in pennies on the New York Stock Exchange

We use NYSE system order data to conduct a controlled experiment examining changes in trader behavior, displayed liquidity supply, and execution quality around the reduction in the minimum price variation to $0.01. Although traders do not substantially reduce their use of traditional limit orders in favor of market orders or non-displayed orders, they do decrease limit order size and cancel limit orders more frequently after decimals than before. These changes in order submission strategy appear to result in less displayed liquidity throughout the limit order book more than 15 cents from the quote midpoint. This reduction in displayed liquidity, however, does not manifest itself in poor execution quality. Even for large system orders, traditional execution quality is not worse with decimals than with fractions.     

Optimal high-frequency trading with limit and market orders

We propose a framework for studying optimal market-making policies in a limit order book (LOB). The bid–ask spread of the LOB is modeled by a tick-valued continuous-time Markov chain. We consider a small agent who continuously submits limit buy/sell orders at best bid/ask quotes, and may also set limit orders at best bid (resp. ask) plus (resp. minus) a tick for obtaining execution order priority, which is a crucial issue in high-frequency trading. The agent faces an execution risk since her limit orders are executed only when they meet counterpart market orders. She is also subject to inventory risk due to price volatility when holding the risky asset. The agent can then also choose to trade with market orders, and therefore obtain immediate execution, but at a less favorable price. The objective of the market maker is to maximize her expected utility from revenue over a short-term horizon by a trade-off between limit and market orders, while controlling her inventory position. This is formulated as a mixed regime switching regular/impulse control problem that we characterize in terms of a quasi-variational system by dynamic programming methods. Calibration procedures are derived for estimating the transition matrix and intensity parameters for the spread and for Cox processes modelling the execution of limit orders. We provide an explicit backward splitting scheme for solving the problem and show how it can be reduced to a system of simple equations involving only the inventory and spread variables. Several computational tests are performed both on simulated and real data, and illustrate the impact and profit when considering execution priority in limit orders and market orders.     

Limit Order Trading

We analyze the rationale for limit order trading. Use of limit orders involves two risks: 1) an adverse information event can trigger an undesirable execution, and 2) favorable news can result in a desirable execution not being obtained. On the other hand, a paucity of limit orders can result in accentuated short-term price fluctuations that compensate a limit order trader. Our empirical tests suggest that trading via limit orders dominates trading via market orders for market participants with relatively well balanced portfolios, and that placing a network of buy and sell limit orders as a pure trading strategy is profitable.     

A comparison of transaction costs on Xetra and on Nasdaq

Abstract

In today's financial world, providing high quality of order execution at low transaction costs is vitally important to the competitiveness of trading platforms; thus the stock market's microstructure has become a subject of fierce debate and models for computing transaction costs have been needed for quite a while. Capital market synergetics is appropriate to investigate the market microstructure's effectiveness and is implemented in the computer program KapSyn.

In this paper we compare transaction costs for small, medium-size and block-size orders on each exchange, examining different market scenarios. By investigating the peculiarities of Xetra and of Nasdaq we point out their comparative advantages: calculation results clearly show the high operating efficiency of Nasdaq's small-order execution system and Xetra's favourable execution of medium-size and block-size orders. Investors' trading decisions may benefit from taking these results into account. For policy makers and academics these findings contribute to the debate about the optimal design of a market microstructure by highlighting the areas of high performance.     

Equity trading by institutional investors: Evidence on order submission strategies

The trading volume channeled through off-market crossing networks is growing. Passive matching of orders outside the primary market lowers several components of execution costs compared to regular trading. On the other hand, the risk of non-execution imposes opportunity costs, and the inherent “free riding” on the price discovery process raises concerns that this eventually will lead to lower liquidity in the primary market. Using a detailed data set from a large investor in the US equity markets, we find evidence that competition from crossing networks is concentrated in the most liquid stocks in a sample of the largest companies in the US. Simulations of alternative trading strategies indicate that the investor’s strategy of initially trying to cross all stocks was cost effective: in spite of their high liquidity, the crossed stocks would have been unlikely to achieve at lower execution costs in the open market.     

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.     

Trading Mechanisms in Securities Markets

This paper analyzes price formation under two trading mechanisms: a continuous quote-driven system where dealers post prices before order submission and an order-driven system where traders submit orders before prices are determined. The order-driven system operates either as a continuous auction, with immediate order execution, or as a periodic auction, where orders are stored for simultaneous execution. With free entry into market making, the continuous systems are equivalent. While a periodic auction offers greater price efficiency and can function where continuous mechanisms fail, traders must sacrifice continuity and bear higher information costs.     

Institutional Trading and Soft Dollars

Proprietary data allow us to distinguish between institutional investors' orders directed to soft-dollar brokers and those directed to other types of brokers. We find that soft-dollar brokers execute smaller orders in larger market value stocks. Allowing for differences in order characteristics, we estimate the incremental implicit cost of soft-dollar execution at 29 (24) basis points for buyer- (seller-) initiated orders. For large orders, incremental implicit costs are 41 (30) basis points for buys (sells). However, we document substantial variability in these estimates, and research services provided by soft-dollar brokers may at least partially offset these costs.     

Hidden liquidity: An analysis of order exposure strategies in electronic stock markets

Many stock exchanges choose to reduce market transparency by allowing traders to hide some or all of their order size. We study the costs and benefits of order exposure and test hypotheses regarding hidden order usage using a sample of Euronext-Paris stocks, where hidden orders represent 44% of the sample order volume. Our results support the hypothesis that hidden orders are associated with a decreased probability of full execution and increased average time to completion, and fail to support the alternate hypothesis that order exposure causes defensive traders to withdraw from the market. However, exposing rather than hiding order size increases average execution costs. We assess the extent to which non-displayed size is truly hidden and document that the presence and magnitude of hidden orders can be predicted to a significant, but imperfect, degree based on observable order attributes, firm characteristics, and market conditions. Overall, the results indicate that the option to hide order size is valuable, in particular, to patient traders.     

Preferencing, Internalization, Best Execution, and Dealer Profits

The practices of preferencing and internalization have been alleged to support collusion, cause worse execution, and lead to wider spreads in dealership style markets relative to auction style markets. For a sample of London Stock Exchange stocks, we find that preferenced trades pay higher spreads, however they do not generate higher dealer profits. Internalized trades pay lower, not higher, spreads. We do not find a relation between the extent of preferencing or internalization and spreads across stocks. These results do not lend support to the "collusion" hypothesis but are consistent with a "costly search and trading relationships" hypothesis.     

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.     

Why Do Traders Split Orders?

We examine factors that influence decisions by U.S. equity traders to execute a string of orders, in the same stock, in the same direction, around the same time. Order splitting is more likely to occur when traders submit larger‐size orders and when market depth and trading activity are lower. Order splitters demand liquidity more and pay higher trading costs, but their overall performance is better. When controlling for execution time, split orders are more informative than single orders. Our results suggest that order splitting arises from a variety of factors, including informational differences, order and trader characteristics, and market conditions.     

Is market impact a measure of the information value of trades? Market response to liquidity vs. informed metaorders

We examine a data-set of institutional trades where approximately one-fourth of the trades were labelled as having been created for cash flow purposes. We aggregate near-overlapping trades into metaorders and consider information, market impact and metaorder size. We find that during the execution, the functional form and scale of market impact are similar for cash flows and other metaorders. Differences arise in the price reversion following the end of a metaorder. For cash flows, presumed to have no true information content, the impact reverts almost completely on average in two to five days. For other metaorders, we find that reversion erases about one-third of the peak impact: for each size, price reverts to the average execution price, leaving no immediate profits after accounting for trading costs. Observed mark-to-market profits on metaorders that aggregate multiple portfolio manager orders, new metaorders and Nasdaq-listed stocks suggest that these metaorders are more informed than the average. Vice-versa, we find mark-to-market losses are more likely to occur on cash flows, metaorders in large-cap stocks, metaorders that follow momentum and additions to a prior position seeking to take advantage of an improved price. The complete price reversion for cash flows suggests that the mechanical permanent impact that is considered in no-quasi-arbitrage arguments would be much smaller than the information in typical institutional metaorders.     

Volatility,Depth, and Order Composition: Evidence from a Pure Limit Order Futures Market

This paper investigates market behaviors (such as volatility, depth, and volume) and order-flow decomposition in a pure limit order futures market, the Taiwan Futures Exchange. The results are different from those in equity markets due to relatively high adverse selection costs in futures markets. We show that a volatility (depth) increase is followed by a depth (volatility) decrease; a market order increase (decrease) subsequently induces higher (lower) volatility; and a limit order increase (decrease) results in more (less) market orders and limit orders. When the upside (downside) volatility rises, buyers decrease (increase) subsequent limit bid orders, and sellers increase (decrease) limit ask orders.     

Impact of a tick size reduction on liquidity: evidence from the Sydney Futures Exchange

This paper examines the impact of a reduction in the minimum price increment on liquidity and execution costs in a futures market setting. In 2006, the Sydney Futures Exchange halved the minimum tick in the 3 Year Commonwealth Treasury Bond Futures. Results indicate that bid‐ask spreads are significantly reduced after the change. Quoted depth, both at the best quotes and visible in the limit order book, is significantly lower after the tick reduction. Further analysis reveals that execution costs are significantly reduced after the change. We conclude that a tick size reduction improves liquidity and reduces execution costs in a futures market setting.