Market Integration and Price Execution for NYSE-Listed Securities

For New York Stock Exchange (NYSE) listed securities, the price execution of seemingly comparable orders differs systematically by location. In general, executions at the Cincinnati, Midwest, and New York stock exchanges are most favorable to trade initiators, while executions at the National Association of Security Dealers (NASD) are least favorable. These intermarket price differences depend on trade size, with the smallest trades exhibiting the biggest per share price difference. Collectively, these results raise questions about the adequacy of the existing intermarket quote system (ITS), the broker's fiduciary responsibility for “best execution,” and the propriety of order flow inducements.     

Quote-based competition and trade execution costs in NYSE-listed stocks

This study examines quotations, order routing, and trade execution costs for seven markets that compete for orders in large-capitalization NYSE-listed stocks. The competitiveness of quote updates from each market varies with measures of the profitability of attracting additional order and with volatility and inventory measures. The probability of a trade executing on each market increases when the market posts competitive quotes. Execution costs for non-NYSE trades when the local market posts competitive (non-competitive) quotes are virtually the same (substantially exceed) costs for matched NYSE trades. Collectively, these results imply a significant degree of quote-based competition for order flow and are consistent with off-NYSE liquidity providers using competitive quotations to signal when they are prepared to give better-than-normal trade executions.     

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.     

All else equal?: a multidimensional analysis of retail,market order execution quality

The extant execution quality literature generally suggests that brokers routing orders away from the NYSE might not fulfill their fiduciary best execution responsibility. This conclusion is drawn by comparing execution prices across trading venues and presumes that other execution-quality characteristics are equivalent. Using order audit-trail data, we find evidence that retail market orders obtain better trade prices on the NYSE but faster executions, more depth improvement, and order-flow payment at Trimark Securities, a Nasdaq dealer. Thus, non-price dimensions of execution quality are not equivalent across trading venues. Furthermore, considering order flow payments, brokers obtain better net prices with Trimark. If brokers pass enough of these payments through to investors in the form of lower commissions and/or better services, then investors also obtain better net prices with Trimark. Our results suggest that it may be misleading to evaluate execution quality or to base policy decisions on comparisons focusing on only execution prices.     

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.     

Trading and Ordering Patterns of Market Participants in High Frequency Trading Environment: Empirical Study in the Japanese Stock Market

In this study, we investigate ordering patterns of different types of market participants in Tokyo Stock Exchange (TSE) by examining order records of the listed stocks. Firstly, we categorize the virtual servers in the trading system of TSE, each of which is linked to a single trading participant, by the ratio of cancellation and execution in the order placement as well as the number of executions at the opening of the afternoon session. Then, we analyze ordering patterns of the servers in the categories in short intervals for the top 10 highest trading volume stocks. By classifying the intervals into four cases by returns, we observe how different types of market participants submit or execute orders in the market situations. Moreover, we investigate the shares of the executed volumes for the different types of servers in the swings and roundabouts of the Nikkei 225 index, which were observed in September in 2015. The main findings of this study are as follows: Server type A, which supposedly includes non-market making proprietary traders with high-speed algorithmic strategies, executes and places orders along with the direction of the market. The shares of the execution and order volumes along with the market direction increase when the stock price moves sharply. Server type B, which presumably includes servers employing a market making strategy with high cancellation and low execution ratio, shifts its market making price ranges in the rapid price movements. We observe that passive servers in Server type B have a large share and buy at low levels in the price falls. Also, Server type B, as well as Server type A, makes profit in the price falling days and particularly, the aggressive servers in the server type make most of the profit. Server type C, which is assumed to include servers receiving orders from small investors, constantly has a large share of execution and order volume.     

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.     

Quote-based competition,market share,and execution quality in NASDAQ-listed securities

We show that competitive quotes help increase dealer market share on NASDAQ, despite the fact that a large proportion of order flow is preferenced. We find that decimal pricing and the introduction of new trading platforms such as SuperSOES and SuperMontage have significantly changed the effect of quote aggressiveness on dealer market share. In particular, decimal pricing reduces (increases) the price (size) elasticity, SuperSOES increases the size elasticity, and SuperMontage increases both the size and price elasticity of dealer market share. We also show that market centers provide greater price improvements and faster executions when they post competitive quotes.     

Implied Lévy volatility

We study the cause of large fluctuations in prices on the London Stock Exchange. This is done at the microscopic level of individual events, where an event is the placement or cancellation of an order to buy or sell. We show that price fluctuations caused by individual market orders are essentially independent of the volume of orders. Instead, large price fluctuations are driven by liquidity fluctuations, variations in the market's ability to absorb new orders. Even for the most liquid stocks there can be substantial gaps in the order book, corresponding to a block of adjacent price levels containing no quotes. When such a gap exists next to the best price, a new order can remove the best quote, triggering a large midpoint price change. Thus, the distribution of large price changes merely reflects the distribution of gaps in the limit order book. This is a finite size effect, caused by the granularity of order flow: in a market where participants place many small orders uniformly across prices, such large price fluctuations would not happen. We show that this also explains price fluctuations on longer timescales. In addition, we present results suggesting that the risk profile varies from stock to stock, and is not universal: lightly traded stocks tend to have more extreme risks.     

Locals,foreigners, and multi-market trading of equities: Intraday evidence from Thailand

We study stock market orders and trades in a developing country, Thailand, where foreign ownership limits partially segment local and foreign investors into two distinct markets. Some foreigners forgo voting rights and distributions to trade on the “local board”, while some locals forgo such benefits and pay a price premium to trade on the “foreign board”. Regardless of nationality, these cross-market traders typically submit orders when liquidity is high, fill orders at relatively beneficial prices, exploit patterns in stock prices across markets, display profitable holding-period returns, and enhance price discovery. This suggests that skilled, informed trading that affects market quality does not depend on trader nationality.     

Short Sales Are Almost Instantaneously Bad News: Evidence from the Australian Stock Exchange

This paper investigates the market reaction to short sales on an intraday basis in a market setting where short sales are transparent immediately following execution. We find a mean reassessment of stock value following short sales of up to −0.20 percent with adverse information impounded within fifteen minutes or twenty trades. Short sales executed near the end of the financial year and those related to arbitrage and hedging activities are associated with a smaller price reaction; trades near information events precipitate larger price reactions. The evidence is generally weaker for short sales executed using limit orders relative to market orders.     

Locals, foreigners, and multi-market trading of equities: Intraday evidence from Thailand

We study stock market orders and trades in a developing country, Thailand, where foreign ownership limits partially segment local and foreign investors into two distinct markets. Some foreigners forgo voting rights and distributions to trade on the “local board”, while some locals forgo such benefits and pay a price premium to trade on the “foreign board”. Regardless of nationality, these cross-market traders typically submit orders when liquidity is high, fill orders at relatively beneficial prices, exploit patterns in stock prices across markets, display profitable holding-period returns, and enhance price discovery. This suggests that skilled, informed trading that affects market quality does not depend on trader nationality.     

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.     

Short-Sale Restrictions and Price Clustering: Evidence from SEC Rule 201

We provide a novel test of information-based theories of price clustering by examining trade, order, and the National Best Bid and Offer (NBBO) quote price clustering during periods when information is removed from the market. We use a natural experiment of short-sale restrictions resulting from Securities and Exchange Commission (SEC) Rule 201 to more effectively determine the impact of information on price clustering. We find evidence of increased price clustering for trades, orders, and NBBO prices during short-sale restrictions. Overall, our findings indicate that short-sale restrictions harm the price discovery process and lead to a reduction in market efficiency.     

High frequency trading and the new market makers

This paper characterizes the trading strategy of a large high frequency trader (HFT). The HFT incurs a loss on its inventory but earns a profit on the bid–ask spread. Sharpe ratio calculations show that performance is very sensitive to cost of capital assumptions. The HFT employs a cross-market strategy as half of its trades materialize on the incumbent market and the other half on a small, high-growth entrant market. Its trade participation rate in these markets is 8.1% and 64.4%, respectively. In both markets, four out of five of its trades are passive i.e., its price quote was consumed by others.     

Market Maker Quotation Behavior and Pretrade Transparency

We examine the impact of differing levels of pretrade transparency on the quotation behavior of Nasdaq market makers. We find that market makers are more likely to quote on odd ticks, and to actively narrow the spread, when they can do so anonymously by posting limit orders on Electronic Communication Networks (ECNs). From a public policy perspective, our findings suggest that making the level of pretrade transparency on Nasdaq more opaque by allowing anonymous quotes could improve price competition and narrow spreads further.     

The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity

We propose a model for determining the optimal bid-ask spread strategy by a high-frequency trader (HFT) who has an informational advantage and receives information about the true value of a security. We employ an information cost function that includes volatility and the volume of the asset. Subsequently, we characterize the optimal bid-ask price strategies and obtain a stable bid-ask spread. We assume that orders submitted by low-frequency traders (LFTs) and news events arrive at the market with Poisson processes. Additionally, our model supports the trading of the two-sided quote in one period. We find that more LFTs and a higher exchange latency both hurt market liquidity. The HFT prefers to choose a two-sided quote to gain more profits while cautiously chooses a one-sided quote during times of high volatility. The model generates some testable implications with supporting empirical evidence from the NASDAQ-OMX Nordic Market.     

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.     

Macroeconomic Announcements and the Distribution of Price-Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.     

Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong

We examine the clustering pattern in trade and quote prices on the electronic limit order book of the Stock Exchange of Hong Kong (SEHK). Earlier research into clustering focuses on transaction prices only. We study clustering on quote prices over a maximum of five queues on the limit order book. We observe an abnormally high frequency of even and integer prices in trade and quote prices for all tick size groups on the SEHK. The deeper quotes display stronger clustering than the best quotes, indicating that the farther away the quotes are from the best queue, the less information they carry. Our analysis further reveals that an extremely fine tick size itself works as a binding constraint to hinder the price resolution process. We also find that short sale prohibition imposed on the majority of stocks listed on the SEHK causes a significant bias in clustering towards the ask side of the limit order book. This implies that a short sale prohibition impairs efficient price discovery in the market.