Microstructure and reverse stock splits

In this paper we show that, similar to NYSE/AMEX stocks, NASDAQ stocks exhibit significant ex date returns for reverse stock splits. Although the 10-day cumulative return after the ex date is close to –10%, this does not violate market efficiency, because the average bid-ask spread for the reverse split stock is at least double this return. We also document that these large negative returns are mostly due to a drop in the ask price while bid prices barely change at all. Furthermore, the ex date returns are negatively related to trading volume.These results suggest that there is abnormal selling and a significant buildup of market makers' inventories near the ex date. To reduce the inventory buildup, market makers lower ask prices to induce buying by investors, resulting in the observed negative returns. Lowering bid prices, an alternative strategy for reducing inventories, is not attractive to market makers due to competitive factors and the reduction of commissions associated with a smaller number of transactions. Notably, selling investors have no incentives to sell their stocks early to avoid the observed negative ex date return, since this return is largely an ask price phenomenon and does not represent realized returns to sellers.     

Adverse selection costs for NASDAQ and NYSE after decimalization

NYSE and NASDAQ completed their decimalization on January 29, 2001 and on April 9, 2001 respectively. In this paper, we compare adverse selection component of the bid–ask spread for NASDAQ and NYSE stocks after decimalization using the data from May 2001 and July 2001. We find that the adverse selection component of the bid–ask spread is significantly lower on NASDAQ than on NYSE, and these differences cannot be attributed to the differences in the characteristics of the stocks traded in the two markets. In addition, we find that the adverse selection costs increase with trade size on NYSE, however there is no monotonic pattern observed for NASDAQ stocks. Lastly, we report that although the order flows arrived in the two markets are significantly different, they can at best explain a small portion of the observed differences in adverse selection costs.     

TRADING COSTS AND QUOTE CLUSTERING ON THE NYSE AND NASDAQ AFTER DECIMALIZATION

We examine execution costs and quote clustering on the New York Stock Exchange (NYSE) and NASDAQ using 517 matching pairs of stocks after decimalization. We find that the mean spread of NASDAQ stocks is greater than the mean spread of NYSE stocks when spreads are equally weighted across stocks, and the difference is greater for smaller stocks. In contrast, the mean NASDAQ spread is narrower than the mean NYSE spread when spreads are volume weighted, and the difference is statistically significant for large stocks. Both NYSE and NASDAQ stocks exhibit high degrees of quote clustering on nickels and dimes, and quote clustering has a significant effect on spreads in both markets.     

Impacts of trades in an error-correction model of quote prices

In this paper we analyze and interpret the quote price dynamics of 100 NYSE stocks stratified by trade frequency. We specify an error-correction model for the log difference of the bid and the ask price with the spread acting as the error-correction term, and include as regressors the characteristics of the trades occurring between quote observations, if any. From this model we are also able to extract the implied model for the spread and the mid-quote. We find that short duration and medium volume trades have the largest impacts on quote prices for all one hundred stocks. Further, we find that buys have a greater impact on the ask price than on the bid price, while sells have a greater impact on the bid price than on the ask price. Both buys and sells increase spreads in the short run, but in the absence of further trades, the spreads mean revert. Trades have a greater impact on quotes for the infrequently traded stocks than for the more actively traded stocks.     

The S&P500 index effect reconsidered: Evidence from overnight and intraday stock price performance and volume

This study focuses on S&P500 inclusions and deletions, examining the impact of potential overnight price adjustment after the announcement of an S&P500 index change. We find evidence of a significant overnight price change that diminishes the returns available to speculators although there are still profits available from the first day after announcement until a few days after the actual event. More importantly, observing the tick-by-tick stock price performance and volume effects on the key days during the event window for the first time, we find evidence of consistent trading patterns during trading hours. A separate analysis of NASDAQ and NYSE listed stocks allows for a detailed examination of the price and volume effect at an intra-day level. We find that index funds appear to cluster their rebalancing activities near to and after the close on the event date, suggesting that they are more concerned with tracking error than profit.     

Payout policy,taxes, and the relation between returns and the bid–ask spread

Recent evidence demonstrates that corporate payout policy has shifted from the nearly exclusive use of dividend payout to the inclusion of stock repurchase, primarily through open markets. This trend has been attributed to the tax advantages associated with repurchase relative to dividends. In this paper, we introduce personal taxation and stock repurchase to reexamine the relation between returns and the bid–ask spread. Our model provides insight into the nature of this relation. Tests performed using NYSE, AMEX, and NASDAQ data provide empirical support of our theoretical conclusions. We conclude that the firm’s choice of payout policy influences the relation between returns and spreads.     

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.     

Market Response to Liquidity Improvements: Evidence from Exchange Listings

The study examines a sample of 895 stocks that moved from Nasdaq to the New York Stock Exchange or to the American Stock Exchange (Amex) between 1971 and 1994. We show how various measures of liquidity such as the bid‐ask spread, trading volume, and stock price precision improve in somewhat different ways upon transfer to NYSE (Amex). We also find that reductions in trading costs (percentage spread) and in pricing error volatility (Hasbrouck's σ₅) can explain most of stock market's positive response to exchange listing. Thus, liquidity has many facets and cannot be represented by the bid‐ask spread alone.     

Trader Anonymity, Price Formation and Liquidity

Using data from the Frankfurt Stock Exchange we analyze priceformation and liquidity in a non-anonymous environment withsimilarities to the floor of the NYSE. Our main hypothesis isthat the non-anonymity allows the specialist to assess the probabilitythat a trader trades on the basis of private information. Heuses this knowledge to price discriminate. This can be achievedby quoting a large spread and granting price improvement totraders deemed uninformed. Consistent with our hypothesis wefind that price improvement reflects lower adverse selectioncosts but does not lead to a reduction in the specialist's profit.Further, the quote adjustment following transactions at thequoted bid or ask price is more pronounced than the quote adjustmentafter transactions at prices inside the spread. Our resultsindicate that anonymity comes at the cost of higher adverseselection risk. JEL Classification: G10.     

The Impact of the Reduction in Tick Increments in Major U.S. Markets on Spreads,Depth, and Volatility

This study presents an analysis of the impact of the introduction of quotes in sixteenths of a dollar on the AMEX, Nasdaq, and NYSE in mid-1997 on select market characteristics such as spreads, effective spreads, quoted depth, and volume. The findings of the study document reductions in the bid-ask spread, effective spread, and a statistically significant increase in the number of quotes. Interestingly, we find that liquidity, as measured by the total depth at the bid and ask, declines significantly on the AMEX and NYSE, but increases on the Nasdaq. Trading volume increases on the NYSE, but remains unchanged for the AMEX and Nasdaq. We also find that the proportion of even-increment quotes is a relevant factor affecting percentage spreads for Nasdaq both before and after and for the NYSE only after the change in quoting increments.     

The Dynamics of Security Trades,Quote Revisions,and Market Depths for Actively Traded Stocks

We examine the dynamics of return volatility, trading volume, and depth—in an intraday setting for a sample of actively traded NYSE and NASDAQ stocks. We show that depth is a useful intervening variable and mitigates the impact of trading activity on price volatility. Furthermore, depth is affected by the perception of prevailing information asymmetry between informed and uninformed traders. We demonstrate empirically that the NYSE supplies greater depth under conditions of high, perceived information asymmetry as compared to NASDAQ. NASDAQ makes up for this deficiency by its capability of managing large volume shocks without a major decline in depth.JEL Classification: C32, D82, G10     

Regulation Fair Disclosure and the Cost of Adverse Selection

Regulation Fair Disclosure (FD), imposed by the Securities and Exchange Commission in October 2000, was designed to prohibit disclosure of material private information to selected market participants. The informational advantage such select participants gain is unclear. If multiple “insiders” receive identical information, private information is immediately incorporated in price and each insider has zero expected profit. If, on the other hand, Regulation FD has curtailed the flow of information from firms, private information becomes longer‐lived and more valuable. Hence, market makers will demand increased compensation by widening the adverse selection component of the bid‐ask spread. We identify the cost components of the bid‐ask spread for a sample of NASDAQ stocks surrounding the implementation of Regulation FD. Controlling for other factors affecting the spread, we find that adverse selection costs increase approximately 36% after Regulation FD. We interpret our finding as Regulation FD failing to achieve one of its desired objectives.     

The Impact of Market Structure on Ex‐Dividend Day Stock Price Behavior

We explore the impact of market structure on the ex‐day price anomaly. Measuring the price‐drop ratio (PDR) as the ratio of the price change on the ex‐day to the dividend amount, we find that the average NASDAQ PDR is significantly less than one and significantly less than the New York Stock Exchange (NYSE) PDR. We then investigate a subset of firms that voluntary switch from NASDAQ to the NYSE and find that the PDR significantly increases after the switch, suggesting that market structure affects PDRs. We also create a matched sample and find that the NASDAQ PDR converges toward its matched NYSE counterpart, particularly after the introduction of SuperMontage. Our evidence is consistent with significant NASDAQ market structure changes reducing execution cost differences between the two exchanges and, in turn, reducing the PDR difference. Overall, our results highlight the important role market structure can play in understanding anomalies.     

Market Microstructure and the Ex-Date Return

This article examines the role of measurement biases, due to order flow effects, in abnormal split ex-day returns. We conjecture that postsplit orders consist of numerous small buyers and fewer larger sellers. This change in order flow causes closing prices to occur more frequently at the ask price, consistent with Maloney and Mulherin (1992) and Grinblatt and Keim (1991) . In addition, this change causes specialists' spreads to increase, perhaps to offset larger average inventories. We examine both NYSE and NASDAQ samples and find that order flow biases can explain approximately 80 percent (48 percent) of the NYSE (NASDAQ) ex-day return.     

The liquidity effects associated with addition of a stock to the S&P 500 index: evidence from bid/ask spreads

This study examines changes in stock liquidity, as measured by the bid/ask spread, when a stock is added to the S&P 500 Index. The paper presents evidence of a significant decrease in the bid/ask spread upon S&P 500 addition, however, this effect is limited to only those stocks that were not trading listed options. Further, the decrease in the bid/ask spread for nonoptioned stocks is accompanied by a significant and permanent increase in share price and trading volume. While optioned stocks experience a permanent increase in trading volume, they experience only a temporary increase in share price. The findings for optioned stocks support the hypothesis that the price and volume effects associated with S&P 500 addition derive from temporary price pressure. Findings pertaining to the nonoptioned stocks indicate that the price and volume effects associated with S&P addition reflect enhanced stock liquidity. The decrease in the bid/ask spread for nonoptioned stocks is attributed to informational efficiencies achieved via index arbitrage trading, and it is argued that this effect is mitigated for optioned stocks due to the pre-existence of arbitrage trading between the option and the underlying stock.     

An Investigation of Market Microstructure Impacts on Event Study Returns

We investigate the importance of bid-ask spread-induced biases on event date returns as exemplified by seasoned equity offerings by NYSE listed firms. We document significant negative return biases on the offering day which explain a large portion of the negative event date return documented in the literature. Buy-sell order flow imbalance is prominent around the offering and induces a relatively large spread bias. If order imbalances are suspected, the researcher can use returns calculated from the midpoint of the closing bid and ask quotes instead of returns calculated from closing transaction prices to avoid this return bias.     

The impact of tick size on intraday stock price behavior: evidence from the Taiwan Stock Exchange

This research examines the impact of tick size on intraday stock price behavior for stocks listed on the Taiwan Stock Exchange over the 2-year period of 1998–1999. The sample involves the same 80 firms that trade under the tick size of (New Taiwan Dollars) NT$0.1 and NT$0.5, respectively. The sample firms display a U-shaped intraday pattern of bid–ask spread, volatility, autocorrelation, and trading volume. The empirical results indicate that a larger tick size is associated with a wider bid–ask spread, larger volatility, and more negative autocorrelation. Moreover, a larger tick size is associated with a higher percentage increase of bid–ask spread and volatility in the middle of the trading period. Finally, the effect of tick size on trading volume is insignificant.     

Structural changes,bid–ask spread composition and tick size in inter-bank futures trading

This paper studies a period containing three major structural changes, which constitute a natural experiment in the NYSE.Euronext-LIFFE European short-term interest rate (STIR) futures market. These changes comprise (1) a 50% reduction in minimum tick size for the most heavily traded contract, (2) European Monetary Union and (3) the transition from open outcry to electronic trading. We analyse a number of microstructure features of the four largest European interest rate futures contracts throughout this period. In particular, we focus on bid–ask spread composition using a recent model which is appropriate for this market structure. Our analysis identifies the tick size as the largest bid–ask spread component in almost every instance, which suggests that participants in this STIR future market might benefit from a reduction in minimum tick sizes.     

The relevance of information and trading costs in explaining momentum profits: Evidence from optioned and non-optioned stocks

Considerable evidence from many countries suggests momentum strategies generate profits. These have been difficult to rationalise and evidence on the sources of such profitability is inconclusive. We utilise a sample of optioned stocks, characterised by high liquidity, high market capitalisation and fewer short sales constraints and compare results with control samples of non optioned stocks chosen on the basis of market value, turnover and bid–ask spread. The sample characteristics, and the fact that derivatives improve the impounding of information into prices, enable us to draw conclusions about the causes of momentum profits. While we find that short sales constraints are not the major driver of profitability and that most momentum profits disappear using two transactions costs measures of the bid–ask spread, one not previously used, the persistence of some momentum profits indicates that the market underreacts even to the most publicly available information.     

Explaining the intra-day variation in the bid–ask spread in competitive dealership markets – A research note

There are many possible explanations for variation in the inside bid–ask spread during the trading day, including informed trading, price inelastic market demand, price discovery, statistical artefact and market concentration. Each of these explanations is examined for consistency with respect to both the inside and average bid–ask spread, observed both inside and outside the mandatory quote period in the London Stock Exchange.