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.     

Estimating the profits from trading strategies

Price improvement is the difference between the execution priceof an order and the quoted bid or ask when the order was submitted.We show that expected price improvement falls off dramaticallyas the size of the order approaches the quoted depth, and becomesnegative for larger orders. This is particularly important forsmall firms because the quoted depths are low. Using quotedspreads and depths and our estimate of expected price improvement,we show that trading strategies that attempt to exploit theweekly predictability of small-firm returns would be swampedby transaction costs.     

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.     

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.     

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.     

Post-Reform Market-Order Execution Quality: Multidimensional Comparisons Across Market Centers

We use market‐order data to determine execution quality on the NYSE, four regional stock exchanges, and the Nasdaq InterMarket. We examine a sample period after the reduction in the minimum price variation and after the SEC imposed new order‐handling rules, and analyze dimensions of execution quality in addition to trade prices. We find that in the postreform environment, the NYSE offers execution prices that are more favorable to the investor. However, the regional exchanges and the InterMarket offer executions that are faster and that more frequently allow investors to execute orders with sizes exceeding the quoted depth at the quoted price.     

Information-Based Trading and Price Improvement

Abstract:  In this study we test the information hypothesis of price improvement. Our results show that price improvement is negatively related to both the probability of information-based trading and the price impact of trades. We interpret these results as evidence that liquidity providers selectively offer price improvements according to the information content of trades. We also show that liquidity providers offer greater (and more frequent) price improvements when they are at the NBBO, and for stocks with wider spreads, fewer trades, or smaller trade sizes relative to the quoted depth. Buyer-initiated trades receive smaller (larger) price improvements than seller-initiated trades on the NYSE (NASDAQ).     

Optimal liquidation in dark pools

We consider a large trader liquidating a portfolio using a transparent trading venue with price impact and a dark pool with execution uncertainty. The optimal execution strategy uses both venues continuously, with dark pool orders over-/underrepresenting the portfolio size depending on return correlations; trading at the traditional venue is delayed depending on dark liquidity. Pushing up prices at the traditional venue while selling in the dark pool might generate profits. If future returns depend on historical dark pool liquidity, then sending orders to the dark pool can be worthwhile simply to gather information.     

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.     

Tick Size,Share Prices,and Stock Splits

Minimum price variation rules help explain why stock prices vary substantially across countries, and other curiosities of share prices. Companies tend to split their stock so that the institutionally mandated minimum tick size is optimal relative to the stock price. A large relative tick size provides an incentive for dealers to make markets and for investors to provide liquidity by placing limit orders, despite its placing a high floor on the quoted bid-ask spread. A simple model suggests that idiosyncratic risk, firm size, and visibility of the firm affect the optimal relative tick size and thus the share price.     

Stock splits in a neutral transaction cost environment: Evidence from the Athens Stock Exchange

This paper investigates the value consequences of stock splits in a market where institutional characteristics minimize the effects of price realignment and signaling. We find that despite these market conditions, stock splits by Greek firms produce positive price reaction around the announcement day. Further, split factors are directly related to pre-split price levels and deviations from average market prices. Splitting firms also realize earnings improvement which is not reversed after the stock split. Consistent with these findings, market reaction is inversely related to the post-split target price and the size of firm. We interpret this as evidence in support, respectively, of the self-selection and “attention-gathering” hypotheses. As reported in other international studies, there is no evidence of liquidity improvement.     

Trader Anonymity, Price Formation and Liquidity

Using data from the Frankfurt Stock Exchange we analyze price formationand liquidity in a non-anonymous environment with similarities to thefloor of the NYSE. Our main hypothesis is that the non-anonymity allows the specialist to assess the probability that atrader trades on the basis of private information. He uses this knowledgeto price discriminate. This can be achieved by quoting a large spread and granting price improvement to traders deemed uninformed.Consistent with our hypothesis we find that price improvement reflects loweradverse selection costs but does not lead to a reduction in the specialist's profit. Further, the quote adjustmentfollowing transactions at the quoted bid or ask price is more pronounced than the quote adjustment aftertransactions at prices inside the spread. Our results indicate that anonymity comes at the cost ofhigher adverse selection risk.     

Liquidity provider incentives in fragmented securities markets

We test theoretical predictions of changes in make/take fees in a setting with isolated make rebates for liquidity providers on a single trading venue (Xetra) by examining the impact on both Xetra and the overall market. The rebates lead to higher quoted depth but do not change bid–ask spreads or trading volume on Xetra. For the overall market, no change in trading volume or liquidity is observable. This shows that market participants redistribute their orders to the venue offering fee rebates rather than providing additional liquidity to the overall market. Consequently, the impact of fee changes depends on the setting.     

Limit order book,anonymity and market liquidity: evidence from the Sydney Futures Exchange

This study examines the impact of the removal of broker mnemonics on the Sydney Futures Exchange. Early research finds that a decrease in transparency reduces liquidity in the market, whereas more recent research finds that reduced transparency improves market quality. Results of the present study indicate an improvement in liquidity after the removal of broker mnemonics. There is a significant increase in quoted depth and trading volume, and a significant decrease in quoted spreads in the 90 day Bank Accepted Bill, 3 year Treasury Bond and 10 year Treasury Bond Futures. This improvement in liquidity is robust to the length of the event window around the structural change and trading in a control market.     

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.     

Risk Aversion, Transparency, and Market Performance

Using a model of market making with inventories based on Biais (1993), we find that investors obtain more favorable execution prices, and they hence invest more, when markets are fragmented. In our model, risk-averse dealers use less aggressive price strategies in more transparent markets (centralized) because quote dissemination alleviates uncertainty about the prices quoted by other dealers and, hence, reduces the need to compete aggressively for order flow. Further, we show that the move toward greater transparency (centralization) may have detrimental effects on liquidity and welfare.     

THE DYNAMICS OF QUOTED LIQUIDITY AROUND LARGE TRADES ON THE NYSE

Large trades have potentially disruptive effects on the continuation of subsequent trade. If the large trade executes against volume from limit orders or specialist quotations, continued trade may be unavailable until new liquidity enters the market. Evidence presented in this paper indicates that large trades on the NYSE are followed by decreases in quoted liquidity, which last for an average of fifteen minutes. Both the decreases in quoted liquidity and the time to its subsequent return are related to trade-specific factors. This evidence suggests that not all large trades have the same effect on the continuation of trade.     

The informational effect and market quality impact of upstairs trading and fleeting orders on the Australian Securities Exchange

This paper investigates the informational effect of trading and market segmentation on the Australian Securities Exchange (ASX) paying particular attention to the recent phenomenon: fleeting orders.¹ Confirming theoretical predictions, this study finds that permanent price effect (PPE) is significantly greater in the central limit order book (LOB) than in the upstairs market and that less informed institutional trades are routed to the upstairs market. It also finds that a well functioning upstairs market often results in lower transaction cost, higher volatility and larger trade size on the ASX. In the context of fleeting orders specifically, it finds the informational effect and market quality impact of upstairs market to be weaker after removing fleeting orders, which subsequently leads to the conclusion that recently introduced execution algorithms, which leave a trace of fleeting orders, often result in lower PPE and are mostly used my uninformed liquidity traders.     

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.     

Latency,liquidity and price discovery

The speed of trading is an important factor in modern security markets, although relatively little is known about the effect of speed on liquidity and price discovery, two important aspects of market quality. On April 23, 2007, Deutsche Boerse made an important upgrade to their trading system. With the 8.0 release of Xetra, system latency was reduced from 50 ms to 10 ms. Subsequently, both quoted and effective spreads decreased, which are mainly concentrated in small- and medium-sized stocks. This increase in liquidity is due to dramatically lower adverse selection costs that were only partially translated into higher liquidity. We interpret this as a decrease in the competition between liquidity suppliers who are able to increase their revenues by more than 90 million euros. The contribution of quotes to price discovery doubles to 90% post upgrade, indicating that prices are more efficient.