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.     

Quote Stuffing

In this study we examine intense episodic spikes in quoting activity (frequently referred to as quote stuffing) on market conditions. We find that quote stuffing is pervasive and that over 74% of US exchange‐listed securities experienced at least one episode during 2010. We also find that stocks experience decreased liquidity, higher trading costs, and increased short‐term volatility during periods of intense quoting activity. We find that most quote‐stuffing events occur on the NYSE, ARCA, NASDAQ, and BATS and that during these quote‐stuffing events, the number of new orders and canceled orders increases substantially while the order size and order duration decrease.     

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).     

The dynamics of quote adjustments

Liquidity providers on the NYSE make faster quote adjustments towards equilibrium spreads and depths than they do on NASDAQ. Liquidity providers in both markets make faster spread and depth adjustments for stocks with more frequent trading, greater return volatility, higher prices, smaller market capitalizations, and smaller trade sizes. We find that stocks with greater information-based trading and in more competitive trading environments exhibit faster quote adjustments. The speed of quote adjustment is faster after decimalization in both markets. These results are robust and not driven by differences in stock attributes between the two markets or time periods. Overall, our results indicate that stock attributes, market structure, and tick size exert a significant impact on the speed of quote adjustment.     

Why effective spreads on NASDAQ were higher than on the New York stock exchange in the 1990s

Two hypotheses have been advanced to explain why spreads on NASDAQ were substantially higher than those on the NYSE in the 1990s: “collusion” and “preferencing and payment for order flow.” We present data on all actively traded stocks in these markets of relative effective spreads (RES), aggregated monthly over 1987–1999 and advance a third hypothesis: NASDAQ “SOES-day-trading.” We estimate NASDAQ and NYSE informed-trade losses and gains to market makers and other liquidity providers on six trade sizes, and find that losses on trades we ascribe to SOES day traders were substantially greater than those on other trades, offset somewhat by gains from small-trade-size investors. NASDAQ market makers' response to these losses and additional operations costs incurred to reduce the losses resulted in greater RES and increased trading within the best quotes, predominantly on larger trade sizes. The data are consistent with the “SOES-day-trading” hypotheses, but not with the other two. Furthermore, the mandatory SOES “experiment” provides insights into the negative effects of automated trading systems (such as ECNs, which now dominate NASDAQ) when their design does not adequately consider opportunistic traders.     

The Informational Role of Stock and Option Volume

This article analyzes the intraday interdependence of orderflows and price movements for actively traded NYSE stocks andtheir Chicago Board Options Exchange (CBOE)-traded options.Stock net trade volume (buyer-initiated volume minus seller-initiatedvolume) has strong predictive ability for stock and option quoterevisions, but option net trade volume has no incremental predictiveability. This suggests that informed investors initiate tradesin the stock market but not in the option market. On the otherhand, both stock and option quote revisions have predictiveability for each other. Thus, while information in the stockmarket is contained in both quote revisions and trades, informationin the option market is contained only in quote revisions.     

Trading Mechanisms and the Components of the Bid-Ask Spread

We compare the relative magnitudes of the components of the bid-ask spread for New York Stock Exchange (NYSE)/American Stock Exchange (AMEX) stocks to those of National Association of Securities Dealers Automated Quotations (NASDAQ)/National Market System (NMS) stocks. We find that the order-processing cost component is smaller, and the adverse selection component is greater on the NYSE/AMEX trading systems than on the NASDAQ/NMS system. The inventory holding component is also greater for exchange-traded stocks than for NASDAQ/NMS stocks, but this may be attributable to differences in the characteristics of the firms whose stocks trade on the respective systems.     

Liquidity in auction and specialist market structures: Evidence from the Italian bourse

Several studies find that bid-ask spreads for stocks listed on the NYSE are lower than for stocks listed on NASDAQ. While this suggests that specialist market structures provide greater liquidity than competing dealer markets, the nature of trading on the NYSE, which comprises a specialist competing with limit order flow, obfuscates the comparison. In 2001, a structural change was implemented on the Italian Bourse. Many stocks that traded in an auction market switched to a specialist market, where the specialist controls order flow. Results confirm that liquidity is significantly improved when stocks commence trading in the specialist market. Analysis of the components of the bid-ask spread reveal that the adverse selection component of the spread is significantly reduced. This evidence suggests that specialist market structures provide greater liquidity to market participants.     

PRICE AND QUANTITY QUOTES ON NASDAQ: A STUDY OF DEALER QUOTATION BEHAVIOR

We show that the majority of quotes posted by NASDAQ dealers are noncompetitive and only 19.5% (18.4%) of bid (ask) quotes are at the inside. The percentage of dealer quotes that are at the inside is higher for stocks with wider spreads, fewer market makers, and more frequent trading, and lower for stocks with larger trade sizes and higher return volatility. These results support our conjecture that dealers have greater incentives to be at the inside for stocks with larger market‐making revenues and smaller costs. Dealers post large depths when their quotes are at the inside and frequently quote the minimum required depth when they are not at the inside. The latter quotation behavior leads to the negative intertemporal correlation between dealer spread and depth.     

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.     

Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

Spreads, Depths, and Quote Clustering on the NYSE and Nasdaq: Evidence after the 1997 Securities and Exchange Commission Rule Changes

This paper examines liquidity and quote clustering on the NYSE and Nasdaq using data after the two market reforms—the 1997 order–handling rule and minimum tick size changes. We find that Nasdaq–listed stocks exhibit wider spreads and smaller depths than NYSE–listed stocks and stocks with higher proportions of even–eighth and even–sixteenth quotes have wider quoted, effective, and realized spreads on both the NYSE and Nasdaq. This result differs from the findings by Bessembinder (1999, p. 404) that "trade execution costs on Nasdaq in late 1997 are no longer significantly explained by a tendency for liquidity providers to avoid odd–eighth quotations," and "odd–sixteenth avoidance has little relevance for explaining post–reform Nasdaq trading costs."     

Liquidity and Stock Exchange Listing

This study examines the pattern of stock price behavior for a sample of 71 firms that moved from NASDAQ and NASDAQ/NMS to the American Stock Exchange (AMEX) between 1982 and 1987. The study tests the liquidity gains hypothesis, which states that investors expect liquidity gains for the less liquid over-the-counter stocks but not for their more liquid counterparts after their listing on the AMEX. The results support the hypothesis by showing a significant difference between the two groups of stocks on the day the AMEX announced approval of the listing. Thus, companies with low liquidity are the largest beneficiaries of listing. The evidence provides little support for the anomalous negative pattern of returns during the post-listing period reported in previous studies.     

The market liquidity of DIAMONDS,Q's,and their underlying stocks

We investigate the market liquidity effects of the introduction of index-tracking stocks for the Dow Jones Industrial Average (DIAMONDS) and the NASDAQ 100 index (Q's). Our main finding is liquidity of the underlying DJIA 30 index stocks improves after the introduction of the exchange-traded fund, largely because of a decline in the cost of informed trading. Further, we find the DIAMONDS has significantly lower liquidity costs over the first 50 days of trading as compared to the portfolio of its component stocks, again primarily because of lower adverse selection costs. Finally, we find weaker but qualitatively similar results for the Q's.     

Tiered Information Disclosure: An Empirical Analysis of the Advance Peek into the Michigan Index of Consumer Sentiment

This paper studies market microstructure implications of informed high‐frequency traders (HFTs) from two seconds of advance peek into the Michigan Index of Consumer Sentiment (ICS), provided by Thomson Reuters to its elite customers. Using individual stocks in the NASDAQ data set, we show how HFTs trade around ICS events. We find that liquidity demanders during two seconds of advance peek earn substantive profits, which are consistent with the notion that HFTs’ informational advantages may increase adverse selection costs for other market participants. This evidence elucidates the debate on regulatory oversight and its role in circumventing the potentially adverse effects from an advance peek into ICS.     

TRADING OF NASDAQ STOCKS ON THE CHICAGO STOCK EXCHANGE

We use a linear programming model to form two portfolios with approximately equal levels of attributes such as financial leverage. One portfolio comprises stocks that trade exclusively on NASDAQ and the other, stocks that trade on both the Chicago Stock Exchange (CSE) and NASDAQ (CSE/NASDAQ). We find that spreads are lower for the CSE/NASDAQ portfolio, but so is the percentage of quotes at spreads of $0.125. In fact, the lower spreads observed for the CSE/NASDAQ portfolio arise from fewer quotes with spreads of more than $0.25.     

The Declining Role of NASDAQ Market Makers

We compare the liquidity providing behavior of NASDAQ market makers in 2010 to their behavior in 2004. We examine how frequently market makers are at the inside quote, what market and stock specific factors influence market makers’ behavior, and the relation between market maker participation and intraday bid‐ask spread patterns. We observe a decrease in the percent of the trading day dealers’ quote at the inside, a decline in the number of market makers, and a decrease in the influence market makers have on intraday spread patterns. The results suggest that the role of NASDAQ market makers declines over time.     

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.     

Can quote competition reduce preferenced trading? A reexamination of the SEC’s 1997 order handling rules

In 1997, the SEC implemented the new order handling rules (OHRs) on the NASDAQ. We observe that some uncompetitive positions gained market share without improving quote competitiveness after the implementation of the OHRs. Also observed is a significant decline in the sensitivity of trading volume to quote competitiveness, indicating lower incentive for NASDAQ dealers to engage in quote competition in the post‐OHR regime. We find that positions that gained trading volume without improving quote competitiveness were less competitive and were more closely associated with stocks showing low information asymmetry, which suggests that preferenced trading might be responsible for the decline in the trading volume sensitivity. Examining entries and exits around the periods of adopting OHRs, we observe net entry of uncompetitive positions and net exit of competitive positions, which indicates that preferenced trading crowded out quote competition subsequent to the OHRs. Our findings suggest that forcing intense quote competition alone produced an unwanted effect that preferencing emerged as a more attractive alternative to quote competition.     

Short sales and speed of price adjustment: Evidence from the Hong Kong stock market

We present empirical evidence that short sales contribute to market efficiency by increasing the speed of price adjustment to not only private/public firm-specific information but also market-wide information. Shortable stocks are characterized by weaker trade continuity and stronger quote reversals. They adjust faster to new information than non-shortable counterparts. These findings remain robust even in an “up” market condition in which short sales are not binding. The amount of information incorporated in each trade is also significantly higher for shortable than non-shortable stocks in both “up” and “down” market conditions. After controlling for firm size, trading volume, liquidity, price and option trading, short sales stand out as one of the significant factors that speed up the price adjustment.