Order Submission Strategies Research Articles

Order submission, information asymmetry, and tick size

Our study investigates traders' order submission strategies with varying market conditions under information asymmetry. It examines how a reduction in tick size affects informed traders' order choices in response to changes in market conditions and subsequently influences the information content of the limit order book on the Tokyo Stock Exchange. We quantify the permanent price impact of orders with different levels of aggressiveness to measure the information content of different kinds of orders before and after a reduction in tick size. The results show that market orders and limit orders placed within or at the best bid and offer (BBO) are more informative than limit orders placed behind the BBO. Moreover, when the quoted spread is wider (narrower) and volatility is low (high), the information content of limit orders placed within or at the BBO is larger (smaller) than market orders, providing evidence that informed traders' order choice on market orders or limit orders is a trade-off between transaction costs and adverse selection costs. We further observe that the information content increases in market orders but decreases in limit orders placed within or at the BBO when the quoted spread becomes narrower and volatility changes from low to high after tick size reduction. This suggests that informed traders tend to shift from limit orders to market orders as transaction costs decrease and adverse selection costs increase, transactions become more informative, which reduces the information content of the limit order book.

Hidden liquidity, market quality, and order submission strategies

Using exogenous changes in hidden liquidity from the Tick Size Pilot Program, we show that hidden liquidity on lit venues has significant effects on various measures of market quality and order submission strategies after controlling for the impact of dark pools and stock attributes. We find that spreads, depths, trading volume, and trade size increase with hidden liquidity. The extent of informed trading and the price impact of a trade also increase with hidden liquidity on lit venues. Traders use more inside-the-quote limit orders, while algorithmic traders engage in more pinging activities and raise message traffic with more hidden liquidity.

Hidden Liquidity, Market Quality, and Order Submission Strategies

Hidden Liquidity, Market Quality, and Order Submission Strategies

Spoofing and pinging in foreign exchange markets

This paper investigates the susceptibility of foreign exchange (FX) spot markets to limit order submission strategies that are either intended to create a false impression of the state of the market (‘spoof orders’) or to extract hidden information from the market (‘ping orders’). Using a complete limit order book dataset from Electronic Broking Services (EBS), our findings suggest that spoofing is more likely to succeed in liquid markets, or on primary electronic trading platforms. Pinging, by contrast, might be more prevalent in illiquid markets, or on secondary electronic trading platforms.

Splitting and Shuffling: Institutional Trading Motives and Order Submissions Across Brokers

This paper studies order submission strategies by institutional investors when trading on private information. By merging institutional daily transactions with original/confidential 13F filings, I separate informed trades from uninformed ones. Informed large orders tend to be split across more brokers and over more days. While same brokers tend to work uninformed large orders over multiple days, the brokers who facilitated early parts of broken-up informed orders rarely receive the remaining parts of the same orders on later days. Institutional investors also provide camouflage for their informed orders by mixing an informed order with other uninformed orders simultaneously sent to the same broker. As a result, a higher degree of shuffling a portfolio of orders is associated with a larger share of informed trading volume. The splitting and shuffling strategies designed to conceal informed trades from brokers and other market participants tend to lower institutional trading costs, especially on informed orders.

Price discovery, order submission, and tick size during preopen period

Using limit order book data, this study investigates the effects of minimum tick size reduction on price discovery and order submission strategies during the preopen call auction period in the Tokyo Stock Exchange. Studying the largest stocks' changes before and after the tick size reduction, our findings suggest that price discovery becomes more efficient when a smaller tick size is employed. A reduction in tick size induces a decrease in market depth and spread and enhances the speed of price discovery by encouraging more aggressive order to be placed and providing investors a better learning and communicating environment to incorporate information into order decisions. Our results demonstrate that, although orders are not matched and no transaction occurs during the preopen period, the order placement at these moments is neither necessarily noisy nor completely manipulative; factors that impact the investor's order choice during the normal trading period also work in this period.

Hidden Liquidity, Market Quality, and Order Submission Strategies

Using a recent pilot program as an exogenous shock to hidden liquidity, we show that hidden liquidity has significant effects on various measures of market quality and order submission strategies after controlling for market volatility and other stock attributes. Spreads, depths, trading volume, and trade size increase with hidden liquidity. The extent of informed trading and the price impact of a trade also increase with hidden liquidity. Traders use more inside-the-quote limit orders, and algorithmic traders engage in more pinging activities and raise message traffic when there is more hidden liquidity.

Deleveraging commonality

We empirically show that stock-level margin trading commoves significantly with market-aggregate margin trading even after controlling for market return and market-wide liquidity. The commonality during the deleveraging process is more pronounced than when leverage increases, and deleveraging commonality contributes to the decline in stock liquidity and heightened surges in liquidity commonality. We also find that market-aggregate margin trading exerts a much larger impact on selling and investors’ order submission strategies than its stock-level counterpart during market crashes. Overall, recognizing the existence of commonality offers a simple and alternative way to think about the systematic risk associated with leverage trading.

Could Market Making be Profitable in The European Carbon Market?

We investigate when market making can be profitable in the European Carbon Futures market, by developing an order type selection rule, based solely on transaction level data. We employ a granular approach that uses an observable variable, i.e. trading intensity, to extract the liquidity and information price components and we investigate their impact on spreads, volatility and ultimately on the profitability of different order types. We find that market orders are always less profitable than limit orders. In addition, market makers are expected to derive most of their profits in a low trading intensity environment, mainly due to higher liquidity commissions and a lower probability of dealing with better informed agents. In contrast, an unconditional limit order submission strategy from an off-floor trader should not be preferred, apart from a medium trading intensity environment, where information and liquidity premia adequately compensate them for execution and information risk.

Stylized algorithmic trading: satisfying the predictive near-term demand of liquidity

Regulatory reform enacted (e.g., the Dodd-Frank Act enforced in the U.S.) requires the financial service industry to consider the “reasonably expected near term demand” (i.e., RENTD) in trading. To manage the price impact and transaction cost associated with orders submitted to an order driven market, market makers or specialists must determine their trading styles (aggressive, neutral, or passive) based on the market liquidity in response to RENTD, particularly for trading a large quantity of some financial instrument. In this article we introduce a model considering different trading styles to satisfy the predictive near-term customer demand of market liquidity in order to find an optimal order submission strategy based on different market situations. We show some analytical properties and numerical performances of our model in search of optimal solutions. We evaluate the performances of our model with simulations run over a set of experiments in comparison with two alternative strategies. Our results suggest that the proposed model illustrates superiority in performance.

Why and how do foreign institutional investors outperform domestic investors in futures trading: Evidence from Taiwan

AbstractA unique data set containing all transactions from the Taiwan Futures Exchange allows us to dissect the long‐lasting outperformance of foreign institutional investors in this emerging market. We show that foreign institutional investors comprehensively outperform domestic investors in trade directions, submission types, trading counterparties, order sizes, and order aggressiveness. Although submitting passive orders increases the trading profits of each investor group significantly, particularly for foreign institutions, the most passive domestic trades still lose to the most aggressive foreign institutional trades. We suggest that information advantage plays a more important role than order submission strategy in foreign institutional investors’ superior performance.

Could Market Making Be Profitable in the European Carbon Market?

We investigate when market making can be profitable in the European Carbon Futures market, by developing an order type selection rule, based solely on transaction level data. We employ a granular approach that uses an observable variable, i.e. trading intensity, to extract the liquidity and information price components and we investigate their impact on spreads, volatility and ultimately on the profitability of different order types. We find that market orders are always less profitable than limit orders. In addition, market makers are expected to derive most of their profits in a low trading intensity environment, mainly due to higher liquidity commissions and a lower probability of dealing with better informed agents. In contrast, an unconditional limit order submission strategy from an off-floor trader should not be preferred, apart from a medium trading intensity environment, where information and liquidity premia adequately compensate them for execution and information risk.

Spoofing and Pinging in Foreign Exchange Markets

This paper investigates the susceptibility of FX spot markets to limit order submission strategies that are either intended to create a false impression of the state of the market (‘spoof orders’) or to extract hidden information in the market (‘ping orders’). Using a complete limit order book dataset from EBS, we study currency pairs that have mature algorithmic markets (EUR/USD and USD/JPY), as well as other G10 and emerging market currencies where EBS is used as a secondary electronic trading platform (EUR/SEK, USD/RUB and USD/TRY). Our results, indicating that EUR/USD and USD/JPY are highly sensitive to information-rich orders, suggests that spoofing tactics might be more dependent on the chosen electronic trading venue, rather than the overall market liquidity of the currency pairs. Furthermore, we find widespread adoption of pinging tactics in the EUR/SEK and USD/RUB markets.

Timing under individual evolutionary learning in a continuous double auction

The moment of order submission plays an important role for the trading outcome in a Continuous Double Auction; submitting an offer at the beginning of the trading period may yield a lower profit, as the trade is likely to be settled at the own offered price, whereas late offers result in a lower probability of trading. This timing problem makes the order submission strategy more difficult. We extend the behavioral model of Individual Evolutionary Learning to incorporate the timing problem and study the limiting distribution of submission moments and the resulting offer function that maps submission moments to offers. We find that traders submit different offers at different submission moments the distribution of which uni-modal with a peak moving from late to early as the market size increases. This behavior exacerbates efficiency loss from learning. If traders evaluate profitability of their strategies over longer history, orders are submitted later with the same effect of market size.

Do Behavioral Biases Affect Order Aggressiveness?*

We extend previous studies on the effect of behavioral biases on investor hold/sell decisions, and examine whether behavioral biases affect the order submission strategies. We use a unique database provided by the Shanghai Stock Exchange, which contains order submissions and executions as well as trading records of all investors. We find investors are less aggressive in submitting sell orders for stocks that experienced losses, and more aggressive in submitting sell orders for stocks that experienced gains. The sell order aggressiveness is negatively related to the size of losses, but has a quadratic relationship with the size of gains. Results are consistent with the combination of the disposition and the house money effects.

Order Aggressiveness, Trading Patience, and Trader Types in a Limit Order Market

This study examines the order aggressiveness and trading patience of foreign institutional traders, futures proprietary firm traders, individual day and non‐day traders in the Taiwan index futures market. We consider order choice given a completely transparent limit order book. Our empirical results show that individual (foreign institutional) traders use a more aggressive (patient) order submission strategy than the other trader types. We find significant differences among trader types in the timing of order aggressiveness and trading patience over the intraday time period. Both top and rest‐of‐the‐order‐book activities affect traders’ order submission decisions. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:1094–1123, 2017

Do Behavioral Biases Affect Order Aggressiveness?

We extend previous studies on the effect of behavioral biases on investor hold/sell decisions, and examine whether behavioral biases affect the order submission strategies. We use a unique database provided by the Shanghai Stock Exchange, which contains order submissions and executions as well as trading records of all investors. We find investors are less (more) aggressive in submitting sell orders for stocks that experienced losses (gains). The sell order aggressiveness is negatively related to the size of losses, but has a quadratic relationship with the size of gains. Results are consistent with the combination of disposition and house money effects.

Investor sentiment, order submission, and investment performance on the Taiwan Stock Exchange

We examine investor sentiment, order submission decisions, and investment performance on the Taiwan Stock Exchange. We first specifically investigate whether investor sentiment affects investors' order aggressiveness and/or order size. Second, we empirically analyze the relation between investor sentiment and order submission strategies across various investor classes. Third and finally, we examine the relation between investor sentiment, order submission decisions, and the short- and long-term investment performance. Our analysis yields the following findings: 1) People's order submission behavior is quite different in optimistic versus pessimistic periods. 2) Buy and sell orders demonstrate different patterns and asymmetric effects. 3) The sensitivity of order submission decisions on investor sentiment is significantly different across different trader classes. 4) Mutual funds, compared with other investors, perform better on the Taiwan Stock Exchange.

The information content of special orders

We consider the role of special orders in informed traders' order submission strategies and their effect on the market price discovery process. Special orders, such as Fill-and-Kill and All-or-Nothing orders, are not entered in the order book; instead, they are executed immediately. This means they do not require costly monitoring and are not visible to other traders. Due to the fact that informed institutional traders, including high-frequency traders, use aggressive special orders, they generate higher price impacts than normal orders, particularly in volatile markets.

Do Behavioral Biases Affect Order Aggressiveness?

We extend previous studies on the effect of behavioral biases on investor hold/sell decisions, and examine whether behavioral biases affect the order submission strategies. We use a unique database provided by the Shanghai Stock Exchange, which contains order submissions and executions as well as trading records of all investors. We find investors are less (more) aggressive in submitting sell orders for stocks that experienced losses (gains). The sell order aggressiveness is negatively related to the size of losses, but has a quadratic relationship with the size of gains. Results are consistent with the combination of disposition and house money effects.