Order Submission Strategies Research Articles

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.

Dynamic Order Submission Strategies with Competition between a Dealer Market and a Crossing Network

We present a dynamic microstructure model where a dealer market (DM) and a crossing network (CN) interact. Sequentially arriving traders with different valuations for an asset maximise their profits either by trading on a DM or by submitting an order for (possibly) uncertain execution via a CN. We develop the analysis for three different informational settings: transparency, complete opaqueness of all order flow, and opaqueness (with observable DM trades). A key result is that the interaction of trading systems generates systematic patterns in order flow for the transparency and partial opaqueness settings. The precise nature of these patterns depends on the degree of transparency at the CN. While unambiguous with a transparent CN, they may reverse direction if the CN is opaque. Moreover, in all three informational settings, we find that a CN and a DM cater for different types of traders. Investors with a high willingness to trade are more likely to prefer a DM. The introduction of a CN next to a DM also affects welfare as it increases total order flow by attracting traders who would otherwise not submit orders (order creation); in addition, it diverts trade from the DM (trade diversion). We find that the coexistence of a CN and DM produces more trader welfare than a DM in isolation. Also, more transparent markets lead to greater trader welfare but may reduce overall welfare.

Order aggressiveness and order book dynamics

In this paper, we study the determinants of order aggressiveness and traders’ order submission strategy in an open limit order book market. Applying an order classification scheme, we model the most aggressive market orders, limit orders as well as cancellations on both sides of the market employing a six-dimensional autoregressive conditional intensity model. Using order book data from the Australian Stock Exchange, we find that market depth, the queued volume, the bid-ask spread, recent volatility, as well as recent changes in both the order flow and the price play an important role in explaining the determinants of order aggressiveness. Overall, our empirical results broadly confirm theoretical predictions on limit order book trading. However, we also find evidence for behavior that can be attributed to particular liquidity and volatility effects.

A local non-parametric model for trade sign inference

We investigate a regularity in market order submission strategies for 12 stocks with large market capitalization on the Australian Stock Exchange. The regularity is evidenced by a predictable relationship between the trade sign (trade initiator), size of the trade, and the contents of the limit order book before the trade. We demonstrate this predictability by developing an empirical inference model to classify trades into buyer-initiated and seller-initiated. The model employs a local non-parametric method, k-nearest neighbor, which in the past was used successfully for chaotic time series prediction. The k-nearest neighbor with three predictor variables achieves an average out-of-sample classification accuracy of 71.40%, compared to 63.32% for the linear logistic regression with seven predictor variables. The result suggests that a non-linear approach may produce a more parsimonious trade sign inference model with a higher out-of-sample classification accuracy. Furthermore, for most of our stocks the observed regularity in market order submissions seems to have a memory of at least 30 trading days.

The Informational Content of an Open Limit Order Book

We assess the informational content of an open limit order book from three directions: (1) Does the limit order book allow better inferences about a security's value than simply the best bid and offer prices from the first step of the book? If it does, how much additional information can be gleaned from the book? (2) Are imbalances between the demand and supply schedules informative about future price movements? and (3) Does the shape of the limit order book impact traders' order submission strategies? Our empirical evidence suggests that the order book beyond the first step is informative - its information share is about 30%. The imbalance between demand and supply from step 2 to 10 provides additional power in explaining future short-term returns. Finally, traders do use the available information on the state of the book, not only from the first step, but also from other steps, when developing their order submission strategies.

Order Aggressiveness and Order Book Dynamics

In this paper, we study the determinants of order aggressiveness and traders' order submission strategy in an open limit order book market. Using order book data from the Australian Stock Exchange, we model traders' aggressiveness in market trading, limit order trading as well as in order cancellations on both sides of the market using a six-dimensional autoregressive intensity model. The information revealed by the open order book plays an important role in explaining the degree of order aggressiveness in the individual processes. Moreover, evidence for significant dynamic interdependencies between the individual processes confirms the usefulness of the multivariate setting. Overall, our empirical results confirm theoretical findings on limit order book trading and show that a trader's decision of when and which order to submit is significantly influenced by the queued volume, the market depth, the inside spread, recent volatility, as well as recent changes in both the order flow and the price.

Order Dynamics: Recent Evidence from the NYSE

Abstract: 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.

Order Submission Strategies and Information: Empirical Evidence from the NYSE

We investigate the role of asymmetric information in affecting order submission strategies. In general, order aggressiveness depends on the state of the order book and on the asset dynamics. We find that the most important determinants are the depth on the same side of the book and a momentum indicator. When we focus on specific situations characterized by higher probability of information-based trading, we find that orders are less aggressive, suggesting strategic behavior of informed traders. This conjecture is supported by a different response to changes in some of their information set's variables.

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.

Discussion of “Equity trading by institutional investors: Evidence on order submission strategies” by Næs and Skjeltorp

Discussion of “Equity trading by institutional investors: Evidence on order submission strategies” by Næs and Skjeltorp

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.

Dynamic Order Submission Strategies with Competition between a Dealer Market and a Crossing Network

We present a dynamic microstructure model where a dealer market (DM) and a crossing network (CN) interact. We consider sequentially arriving agents having different valuations for an asset. Agents maximize their profits by either trading at a DM or by submitting an order for (possibly) uncertain execution at a CN. We develop the analysis for three different informational settings: transparency, “complete” opaqueness of all order flow, and “partial” opaqueness (with observable DM trades). We find that a CN and a DM cater for different types of traders. Investors with a high eagerness to trade are more likely to prefer a DM. The introduction of a CN increases overall order flow by attracting traders who would not otherwise submit orders (“order creation”). It also diverts trades from the DM. The transparency and “partial” opaqueness settings generate systematic patterns in order flow. With transparency, the probability of observing a CN order at the same side of the market is smaller after such an order than if it was not. Buy (sell) orders at a CN are also less likely to attract subsequent sell (buy) orders at the DM.

Order Submission Strategy and the Curious Case of Marketable Limit Orders

We provide empirical evidence on order submission strategy of investors with similar commitments to trade by comparing the execution costs of market orders and marketable limit orders (i.e., limit orders with the same trading priority as market orders). The results indicate the unconditional trading costs of marketable limit orders are significantly greater than market orders. We attribute the difference in costs to a selection bias and provide evidence suggesting the order submission strategy decision is based on prevailing market conditions and stock characteristics. After correcting for the selection bias, the results show the average trader chooses the order type with lower conditional trading costs.

The Toronto Stock Exchange preopening session

This paper documents order submission strategies during the Toronto Stock Exchange preopening session. I find that the registered trader (RT) actively participates in the market opening, even though he cannot set the opening price directly, and has no apparent informational advantage. RT opening trades are profitable, moderate overnight price changes, and appear to be motivated, in part, by inventory adjustment concerns. I examine interlisted stocks that simultaneously open for trading under two different mechanisms and show how the comparative levels of pre-trade market transparency of each exchange impacts RT profits and participation.

Does the Limit Order Routing Decision Matter?

We examine the impact deciding to route limit orders away from the New York Stock Exchange (NYSE) has on three dimensions of execution quality with methodologies controlling for market conditions and order submission strategies. Overall differences in limit order execution quality between regional stock exchanges and the NYSE are small, suggesting that the order routing decision may not affect retail limit order traders substantively. Conditioning on the distance between the limit order's price and prevailing quotes, however, reveals systematic differences in execution quality. This implies that brokers can strategically route limit orders to improve retail limit order execution quality. Copyright 2002, Oxford University Press.

Empirical Analysis of Limit Order Markets

We provide empirical restrictions of a model of optimal order submissions in a limit order market. A trader’s optimal order submission in our model depends on the trader’s valuation for the asset and the trade os between order prices, execution probabilities and picking o risks. The optimal order submission strategy is a monotone function of a trader’s valuation for the asset. We use the monotonicity restriction to test if the traders follow the optimal order submission strategy in our sample, using the order prices, execution probabilities and picking o risks of the orders chosen by the traders in the sample. We compute a semiparametric test using a sample of order submissions from the Stockholm Stock Exchange. We do not reject the monotonicity restriction for buy orders or sell orders separately, but do reject the monotonicity restriction when we combine buy and sell orders. The expected payos from submitting limit orders away from the quotes are too low relative to the expected payos from submitting limit orders close to the quotes to rationalize all the observed order submissions in our sample.

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.

Transactions costs and investment style: an inter-exchange analysis of institutional equity trades

This paper examines the magnitude and determinants of transactions costs for a sample of institutional traders with different investment styles. Using order-level data for recent equity transactions totaling $83 billion, we find that trading costs are economically significant and increase with trade difficulty. In addition, costs vary with traderspecific factors such as investment style and order submission strategy, as well as stock-specific factors such as exchange listing. We find evidence that institutional trades in exchange-listed stocks have lower costs than in comparable Nasdaq stocks.

Market vs. Limit Orders: The SuperDOT Evidence on Order Submission Strategy

Market vs. Limit Orders: The SuperDOT Evidence on Order Submission Strategy

Market vs. Limit Orders: The SuperDOT Evidence on Order Submission Strategy

This paper discusses performance measures for market and limit orders. We suggest two measures: one for precommitted traders (who must trade) and another for passive traders (who are indifferent to trading). We compute these measures for a sample of NYSE Super? DOT orders. The results suggest that the limit order placement strategies most commonly used by NYSE SuperDOT traders do in fact perform best. Limit orders placed at or better than the prevailing quote perform better than do market orders, even after imputing a penalty for unexecuted orders, and after taking into account market order price improvement. Un? conditional order submission strategies that use SuperDOT to offer liquidity in competition with the specialist do not appear to be profitable.