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.     

Making a Market with Spreads and Depths

Abstract:   In this paper we study the quote revision behavior of NASDAQ market makers by analyzing inter‐temporal changes in their spread and depth quotes. Using individual dealer quote and trade data for a sample of 2,319 stocks, we find that NASDAQ dealers make more frequent revisions in depths than in spreads and the extent of liquidity management is greater for stocks of smaller companies, lower‐priced stocks, and stocks with larger trade sizes and fewer number of transactions. We show that intraday variation in the number of quote revisions follows the U‐shaped pattern, indicating that the extent of liquidity management is greater during the early and late hours of trading than during midday.     

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.     

Weather and intraday patterns in stock returns and trading activity

We examine the relation between weather in New York City and intraday returns and trading patterns of NYSE stocks. While stock returns are found to be generally lower on cloudier days, cloud cover has a significant influence on stock returns only at the market open. There are significantly more seller-initiated trades when there is more cloud cover at the market open, which is consistent with the return results. Cloudy skies are associated with higher volatility and less market depth over the entire trading day. Finally, cloud cover is not significantly correlated with spread measures and turnover ratios. The findings overall suggest that weather has a significant influence on investors’ intraday trading behavior.     

DO DEALERS INFER INFORMATION FROM ORDER FLOW?

I examine strategic behavior among dealers in the NASDAQ market and document that there is a lead quote‐setting dealer in each security and that the quotes posted by this leader are informative. Other dealers free‐ride this information by following the lead quote‐setting dealer. The lead dealer can be identified by two information signals: (1) percentage of time spent on the inside market (i.e., posting inside quotes), and (2) trade volume transacted. Dealers that free‐ride the leader's quotes quickly update their posted quotes in the same direction as the leader's quote change. My findings suggest that directing trade to the lead dealer may be more advantageous than randomly routing trade.     

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.     

Trading Patterns and Prices in the Interbank Foreign Exchange Market

The behavior of quote arrivals and bid-ask spreads is examined for continuously recorded deutsche mark-dollar exchange rate data over time, across locations, and by market participants. A pattern in the intraday spread and intensity of market activity over time is uncovered and related to theories of trading patterns. Models for the conditional mean and variance of returns and bid-ask spreads indicate volatility clustering at high frequencies. The proposition that trading intensity has an independent effect on returns volatility is rejected, but holds for spread volatility. Conditional returns volatility is increasing in the size of the spread.     

Trade signing in fast markets

This study assesses the accuracy of trade signing algorithms in fast trading environments using NASDAQ and NYSE trade and quote data. Using data that contain true trade signs, we show that the Lee and Ready algorithm outperforms the tick rule and classifies trades at least as well as in earlier studies from slower trading environments, even in subsamples where the market is particularly fast. We conclude that trade signing remains viable in fast markets, and that the use of quote data continues to increase trade classification accuracy.     

THE IMPACT OF MARKET MAKER CONCENTRATION ON ADVERSE‐SELECTION COSTS FOR NASDAQ STOCKS

We examine the impact of market maker concentration on adverse‐selection costs for NASDAQ stocks and find that more market makers results in lower costs. Furthermore, this reduction in adverse selection exceeds the overall reduction in spreads that is attributable to market maker competition. We hypothesize that order flow internalization is increasing in market makers and allows for greater information production, and is an explanation for our findings. Our results provide an explanation for the puzzle documented by previous work that finds that adverse‐selection costs for NASDAQ tend to be lower than for the New York Stock Exchange, whereas spreads tend to be higher.     

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.     

Inferring Trade Direction from Intraday Data

This paper evaluates alternative methods for classifying individual trades as market buy or market sell orders using intraday trade and quote data. We document two potential problems with quote-based methods of trade classification: quotes may be recorded ahead of trades that triggered them, and trades inside the spread are not readily classifiable. These problems are analyzed in the context of the interaction between exchange floor agents. We then propose and test relatively simple procedures for improving trade classifications.     

Intraday Variation in the Bid-Ask Spread: Evidence after the Market Reform

In this article we show that intraday variation in spreads for Nasdaq‐listed stocks has converged to intraday variation in spreads for NYSE‐listed stocks after the implementation of the new order‐handling rules. We attribute this convergence to the Limit Order Display Rule, which requires that limit orders be displayed in Nasdaq best bid and offer when they are better than quotes posted by market makers. Our findings suggest that the different patterns of intraday spreads between NYSE and Nasdaq stocks reported in prior studies can largely be attributed to the different treatment of limit orders between the NYSE and Nasdaq before the market reform.     

Entry, exit, market makers, and the bid-ask spread

The probability of entry and exit of dealers on the NASDAQ NationalMarket (NNM) is significantly affected by trading intensity,volatility and the quoted bid-ask spread. Entry and exit ofmarket makers is a pervasive phenomenon. Large-scale entry (exit)is associated with substantial declines (increases) in quotedend-of-day inside spreads, even after controlling for the effectsof changes in volume and volatility. The spread changes arelarger in magnitude for issues with few market makers; however,even for issues with a large number of market makers, substantialchanges in quoted spreads take place. The results are consistentwith the competitive model of dealer pricing.     

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.     

Price impact and bursts in liquidity provision

This paper analyses brief episodes of high-intensity quote turnover and revision—‘bursts’ in quotes—in the US equity market. Such events occur very frequently, several hundred times a day for actively traded stocks. We find significant price impact associated with these market maker initiated events, about five times higher than during non-burst periods. Bursts in quotes are concurrent with short-lived structural breaks in the informational relationship between market makers and market takers. During bursts, market makers no longer passively impound information from order flow into quotes—a departure from the traditional market microstructure paradigm. Rather, market makers significantly impact prices during bursts in quotes. Further analysis shows that there is asymmetry in adverse selection between the bid and ask sides of the limit order book and only a sub-population of market makers enjoys an informational advantage during bursts. Market makers on the side opposite the burst suffer elevated adverse selection costs, while market makers on the side of the burst realize positive spread, irrespective of the order flow direction. Our results call attention to the need for a new microstructure perspective in understanding modern high-frequency limit order book markets and the quote manipulation strategies at the disposal of the fast market makers.     

Market Maker Performance: The Search for Fair Weather Market Makers

The London Stock Exchange has long been concerned that some market makers do not fulfill their obligations. This study describes a range of measures to identify such fair weather market makers. The results indicate that three firms of market makers meet the criteria for fair weather market making. It is also discovered that market makers in a given stock all quote the same fixed spread in round pennies and that this is about twice the touch. Internalized order flow is pervasive, with market makers receiving 57% of their order flow from associated brokers. However, fair weather market making is found to be distinct from order preferencing and internalization.     

Exit,Survival, and Competitive Equilibrium in Dealer Markets

In this study we analyze dealer exit, survival, and competitive equilibrium in the NASDAQ Stock Market using data from a unique period that entails major changes in regulatory and competitive environments. We decompose the forces that affect dealer survival into market factors and dealer attributes. Market factors encompass those variables that affect the demand for and profitability of dealer services as a whole. Variation in survival probability across dealers results mainly from their competitive advantages in business strategies, information, quote aggressiveness, access to order flow, and economies of scale. On the whole, our results suggest that dealer markets exhibit a Darwinian survival of the fittest.     

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 EFFECT OF THE TRADING SYSTEM ON IPO UNDERPRICING: EVIDENCE FROM THE 1997 ORDER‐HANDLING RULES

We use a natural experiment resulting from the 1997 Securities and Exchange Commission rule mandating a change in the order‐handling rules (OHR) for all NASDAQ stocks to test whether secondary market structure affects initial public offering (IPO) underpricing. We find that the increase in liquidity that the OHR represent led to a decrease in underpricing for cold NASDAQ IPOs, suggesting that when liquidity is lowest, changes in market liquidity display a negative relation to initial returns.     

FORECASTING STOCK INDEX VOLATILITY: COMPARING IMPLIED VOLATILITY AND THE INTRADAY HIGH–LOW PRICE RANGE

The intraday high–low price range offers volatility forecasts similarly efficient to high‐quality implied volatility indexes published by the Chicago Board Options Exchange (CBOE) for four stock market indexes: S&P 500, S&P 100, NASDAQ 100, and Dow Jones Industrials. Examination of in‐sample and out‐of‐sample volatility forecasts reveals that neither implied volatility nor intraday high–low range volatility consistently outperforms the other.