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.     

Optimal and equilibrium execution strategies with generalized price impact

This paper examines the execution problems of large traders with a generalized price impact. Constructing two related models in a discrete-time setting, we solve these problems by applying the backward induction method of dynamic programming. In the first problem, we formulate the expected utility maximization problem of a single large trader as a Markov decision process and derive an optimal execution strategy. Then, in the second model, we formulate the expected utility maximization problem of two large traders as a Markov game and derive an equilibrium execution strategy at a Markov perfect equilibrium. Both of these two models enable us to investigate how the execution strategies and trade performances of a large trader are affected by the existence of other traders. Moreover, we find that these optimal and equilibrium execution strategies become deterministic when the total execution volumes of non-large traders are deterministic. We also show, by some numerical examples, the comparative statics results with respect to several problem parameters.     

Lifting the Veil: An Analysis of Pre-trade Transparency at the NYSE

We study pre‐trade transparency by looking at the introduction of NYSE's OpenBook service that provides limit‐order book information to traders off the exchange floor. We find that traders attempt to manage limit‐order exposure: They submit smaller orders and cancel orders faster. Specialists' participation rate and the depth they add to the quote decline. Liquidity increases in that the price impact of orders declines, and we find some improvement in the informational efficiency of prices. These results suggest that an increase in pre‐trade transparency affects investors' trading strategies and can improve certain dimensions of market quality.     

Bullish/bearish/neutral strategies under short sale restrictions

This study investigates the effects of short sale restrictions by extending the model of Dridi and Germain (2004) and infers informed traders’ strategies and the relation between order imbalance and price thereunder. The results are generally in line with the empirical evidence documented in the literature and are summarized as follows: First, seller-initiated trading incurs a greater price reaction. Second, short sale restrictions shift the skewness of asset returns. Third, the restrictions can stimulate investors to acquire information or increase each individual trader's order flow under the bullish and neutral signals as well as the bearish signal, which is yet to be explored empirically.     

Bid ask spread in a competitive market with institutions and order size

Large orders, particularly from institutions, are quite common these days and hence there is interest to know if institutional trading has any bearing on the price effect associated with large trades. Recent empirical studies contradict earlier evidence of negative price effect on selling large blocks and find no price effect associated with large trades. Existing theoretical framework suggests a monotonic and increasing adverse price effect for large trades, where the motivation for a large trade is private information. We model a trading system where pure information, information-liquidity, and pure liquidity traders trade small and large sizes. The pure information traders strategically choose an order size. Institutions trade only large sizes because of their low execution costs for large trades; they are information-liquidity traders whose ability to use an information signal to determine their trades is subject to a binding liquidity constraint. We show that in such a market a separating equilibrium where trade size is informative does not exist and hence there is no price effect for large trades. Trade size may be revealing only if there is a buy sell asymmetry (large buy size is not equal to large sell size) or the corresponding price effect is asymmetric (price effect due to a large buy is not equal to that of a large sell). Further for a pooling equilibrium to exist, where trade size is not informative, the width of the market denoted by the ratio of order size (large size/small size) needs to be small, while the shallowness (inverse depth) of the market denoted by the ratio between pure information and institutional trades and the information signal needs to be stronger (higher). Our results on bid and ask prices and spread confirm recent empirical evidence on price effect of large and institutional trades found in the literature.

Regulation NMS and Market Quality

We show that both the quoted and effective spreads increased, the quoted depth decreased, and the market quality index decreased after the implementation of Regulation National Market System (NMS) (Reg NMS). We also find an increase in the price impact of trades and the dispersion of the pricing error after Reg NMS. The order execution speed is slower, the order fill rate is lower, and the order cancellation rate is higher for most trades after Reg NMS. Hence, contrary to the Securities and Exchange Commission's belief, Reg NMS has proven to be detrimental to most traders. NASDAQ provided faster and more reliable executions than the NYSE/AMEX, and NASDAQ gained market shares from the NYSE/AMEX and other trading venues after Reg NMS.     

Does the Limit Order Routing Decision Matter?

We examine the impact deciding to route limit orders away fromthe New York Stock Exchange (NYSE) has on three dimensions ofexecution quality with methodologies controlling for marketconditions and order submission strategies. Overall differencesin limit order execution quality between regional stock exchangesand the NYSE are small, suggesting that the order routing decisionmay not affect retail limit order traders substantively. Conditioningon the distance between the limit order's price and prevailingquotes, however, reveals systematic differences in executionquality. This implies that brokers can strategically route limitorders to improve retail limit order execution quality.     

News Trading and Speed

We compare the optimal trading strategy of an informed speculator when he can trade ahead of incoming news (is “fast”), versus when he cannot (is “slow”). We find that speed matters: the fast speculator's trades account for a larger fraction of trading volume, and are more correlated with short‐run price changes. Nevertheless, he realizes a large fraction of his profits from trading on long‐term price changes. The fast speculator's behavior matches evidence about high‐frequency traders. We predict that stocks with more informative news are more liquid even though they attract more activity from informed high‐frequency traders.     

The effectiveness of competing regulatory regimes and the switching effects: Evidence from an emerging market

I investigate the effectiveness of two competing regulatory regimes and the effect of switching from strict price limits to circuit breakers on volatility spillover, and also on trading interference hypotheses. I find that switching to the circuit breakers' regime increases volatility and disrupts the price discovery mechanism. Stock prices are prevented from reaching their equilibrium levels and traders are unable to obtain their desired positions on limits hit day. Moreover, I find that volatility is spread out over the following 2 days post-limit hits within the strict price limits regime. Finally, the results show that price limits interfere with trading activity and affect investors' beliefs and liquidity positions.     

Information, speed vs. cost trade-offs, and order routing decisions in U.S. equity markets

Prior research indicates that both execution speed and cost are important to traders, but that these two dimensions of execution quality are negatively related across U.S. equity markets. In our paper, we examine how U.S. equity traders, who are (un)informed about future price changes, trade-off between speed and cost in their order-routing decisions. We find that informed traders are more likely to choose trading systems that allow them to trade-off lower cost for faster speed; whereas, uninformed traders are more likely to choose trading systems that allow them to sacrifice speed for lower costs. Our results indicate that traders have varying preferences for the different dimensions of execution quality based on their information levels. These differences subsequently influence order-routing decisions.     

Do Limit Orders Alter Inferences about Investor Performance and Behavior?

Individual investors lose money around earnings announcements, experience poor posttrade returns, exhibit the disposition effect, and make contrarian trades. Using simulations and trading records of all individual investors in Finland, I find that these trading patterns can be explained in large part by investors' use of limit orders. These patterns arise mechanically because limit orders are price‐contingent and suffer from adverse selection. Reverse causality from behavioral biases to order choices does not appear to explain my findings. I propose a simple method for measuring a data set's susceptibility to this limit order effect.     

Anticipated Earnings Announcements and the Customer–Supplier Anomaly

I test whether the anticipation of earnings news stimulates acquisition of customer information and mitigates returns to the customer–supplier anomaly documented by Cohen and Frazzini (“Economic Links and Predictable Returns.” The Journal of Finance 63 (2008): 1977–2011). I find that attention to a firm's publicly disclosed customers increases shortly before the firm announces earnings, and that customer stock returns predict supplier stock returns shortly before, but not after, the supplier's earnings announcement. I further find some evidence that these predictable returns are increasing in the level of customer information acquisition. These results are unique to anticipated disclosure events and suggest that anticipation of supplier earnings announcements resolves investor limited attention to customer information and accelerates price discovery of customer news.     

Beliefs Aggregation and Return Predictability

We study return predictability using a model of speculative trading among competitive traders who agree to disagree about the precision of private information. Although traders apply Bayes' Law consistently, returns are predictable. In addition to trading on long-term fundamental value, traders also trade on perceived short-term opportunities arising from foreseen future disagreement, as in a Keynesian beauty contest. Contradicting conventional wisdom, this short-term speculation dampens price fluctuations and generates time-series momentum. Model calibration shows quantitatively realistic patterns of return dynamics. Consistent with empirical evidence, our model predicts more pronounced momentum for stocks with higher trading volume.     

Speed,distance, and electronic trading: New evidence on why location matters

We examine the execution quality of electronic stock traders who are geographically dispersed throughout the United States. Traders who are located near market central computers in the New York City area experience faster order execution. Moreover, the time to execute orders rises as a trader’s actual distance (mileage) to NYC widens. In electronic market settings, data transfer limitations and transmission slowdowns result in geographically-dispersed electronic traders having different access to trading speed. We find that speed differences are costly to traders and that speed-advantaged traders engage in strategies that are more conducive to speed.     

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.     

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.     

The incremental impact of analyst initiation of coverage

I compare the return surrounding a sell-side analyst's initiation of coverage to the return surrounding a recommendation by an analyst who already covers the stock. The market responds more positively to analysts' initiations than to other recommendations. The incremental price impact of an initiation is 1.02% greater than the reaction to a recommendation by an analyst who already covers the stock. I examine whether the hypothesis that analyst coverage increases liquidity explains this incremental return. I find that liquidity improves after initiations, but that one must extend the liquidity hypothesis in order to fully explain the incremental price impact. Liquidity gains subsequent to analyst initiation depend on the analyst's recommendation. The more positive the initial recommendation, the greater the subsequent liquidity improvement. I also find that the initiation abnormal return correlates with the subsequent improvements in liquidity. Corporations should encourage analyst coverage to capture this liquidity benefit.     

Price dynamics in foreign currency futures markets

Nested tests of Samuelson's submartingale and martingale models of price behavior in an efficient futures market find significant autocorrelation at low lags in daily changes of log prices for four of ten currency futures contracts satisfying the assumptions of the statistical tests. Negative serial correlation following large price changes is also found. The analysis controls for bias due to institutional limits on daily price movements. Simulated trading based on out-of-sample forecasts suggests the dependencies probably could be exploited by traders who are members of the futures exchange to earn net profits greatly exceeding buy and hold.     

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.     

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.