The Quality of ECN and Nasdaq Market Maker Quotes

This paper compares the quality of quotes submitted by electronic communication networks (ECNs) and by traditional market makers to the Nasdaq quote montage. An analysis of the most active Nasdaq stocks shows that ECNs not only post informative quotes, but also, compared to market makers, ECNs post quotes rapidly and are more often at the inside. Additionally, ECN quoted spreads are smaller than dealer quoted spreads. The evidence suggests that the proliferation of alternative trading venues, such as ECNs, may promote quote quality rather than fragmenting markets. Moreover, the results suggest that a more open book contributes to quote quality.     

Inferring Public and Private Information from Trades and Quotes

We propose a new model that uses nonsynchronous, ultra‐high frequency data to analyze the sequential impact of trades and quotes on the price process. Private information is related to the impact of trades and public information to the impact of quotes. The model is extended to include various other factors that affect public and private information. For 20 active Nasdaq stocks, private information causes, on average, 9.43% of daily stock price movements. Additionally, quotes are more informative when (1) many dealers set the best price and (2) traditional market makers rather than Electronic Communication Networks set the best price.     

Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong

We examine the clustering pattern in trade and quote prices on the electronic limit order book of the Stock Exchange of Hong Kong (SEHK). Earlier research into clustering focuses on transaction prices only. We study clustering on quote prices over a maximum of five queues on the limit order book. We observe an abnormally high frequency of even and integer prices in trade and quote prices for all tick size groups on the SEHK. The deeper quotes display stronger clustering than the best quotes, indicating that the farther away the quotes are from the best queue, the less information they carry. Our analysis further reveals that an extremely fine tick size itself works as a binding constraint to hinder the price resolution process. We also find that short sale prohibition imposed on the majority of stocks listed on the SEHK causes a significant bias in clustering towards the ask side of the limit order book. This implies that a short sale prohibition impairs efficient price discovery in the market.     

A comparison of trading and non-trading mechanisms for price discovery

This paper compares trading and non-trading mechanisms for price discovery during the Nasdaq pre-open and examines whether prices discovered though non-trading mechanisms are less efficient or reveal less information than prices discovered through trading. As Nasdaq pre-open trading volume increased, the opening price became more efficient and price discovery shifted from the opening trade to the pre-open. Price discovery shifted from the trading day to the pre-open only for the highest-volume stocks. These results suggest that pre-open trading contributes to the efficiency of the opening price, but that a critical threshold of trading volume is required to increase the amount of information in the opening price.     

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."     

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.     

Is there price discovery in equity options?

We use tick-by-tick quote data for 39 liquid US stocks and options on them, and we focus on events when the two markets disagree about the stock price in the sense that the option-implied stock price obtained from the put-call parity relation is inconsistent with the actual stock price. Option market quotes adjust to eliminate the disagreement, while the stock market quotes behave normally, as if there were no disagreement. The disagreement events are typically precipitated by stock price movements and display signed option volume in the direction that tends to eliminate the disagreements. These results show that option price quotes do not contain economically significant information about future stock prices beyond what is already reflected in current stock prices, i.e., no economically significant price discovery occurs in the option market. We also find no option market price discovery using a much larger sample of disagreement events based on a weaker definition of a disagreement, which verifies that the findings for the primary sample are not due to unusual or unrepresentative market behavior during the put-call parity violations.     

Inter-market competition for NYSE-listed securities under decimals

Blume and Goldstein (J Finance 52:221–244, 1997) suggest that quote competition between trading venues may diminish following tick size reductions. We test this suggestion by studying the competitive landscape in the NYSE-listed stocks before and after decimalization. We find that NBBO (National Best Bid and Offer) participation by non-NYSE venues declines following decimalization consistent with the prediction. At the same time, the importance of quote competitiveness in attracting order flow increases. In addition, although not as active in determining and maintaining the best quotes under decimals, non-NYSE venues become more active in price discovery. Finally, decimalization leads to lower trading costs and to smaller differences in trading costs across trading venues.     

Order imbalance and liquidity supply: Evidence from the bubble burst of Nasdaq stocks

In this study we analyze the effect of order imbalance on the quotation behavior of Nasdaq market makers. We find that Nasdaq market makers use both price and quantity quotes when dealing with order imbalances. However, order imbalance affects only price movement, not spreads. We also find that Nasdaq market makers quote more shares and compete more intensively on bid-side (ask-side) when public sells (buys) exceed public buys (sells). These suggest that market makers increase liquidity supply when order imbalances exist. More interestingly, we show that both market conditions and price movements affect investors' trading behavior.     

One Security,Many Markets: Determining the Contributions to Price Discovery

When homogeneous or closely-linked securities trade in multiple markets, it is often of interest to determine where price discovery (the incorporation of new information) occurs. This article suggests an econometric approach based on an implicit unobservable efficient price common to all markets. The information share associated with a particular market is defined as the proportional contribution of that market's innovations to the innovation in the common efficient price. Applied to quotes for the thirty Dow stocks, the technique suggests that the preponderance of the price discovery takes place at the New York Stock Exchange (NYSE) (a median 92.7 percent information share).     

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.     

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 informativeness of domestic and foreign investors’ stock trades: Evidence from the perfectly segmented Chinese market

This paper uses the perfect market segmentation setting in China's stock market to compare the information content of the stock trades of domestic and foreign investors. We study 76 firms that issue both A-shares (for domestic investors) and B-shares (for foreign investors) and compare the price discovery role of the two segmented markets in China. Before Feb 19, 2001, the A-share market led the B-share market in price discovery, as the signed volume and quote revision of the A-share market had strong predictive ability for B-share quote returns, but not vice versa. After Feb 19, 2001, because some domestic investors were allowed to invest in the B-share market, we find evidence for a reverse causality from the B-share to the A-share market. Nevertheless, the [Hasbrouck (1995). One security, many markets: determining the contributions to price discovery, Journal of Finance 50, 1175–1199.] information share analysis reveals that A-shares continue to dominate the price discovery process.     

Adverse selection costs,trading activity and price discovery in the NYSE: An empirical analysis

This paper studies the role that trading activity plays in the price discovery process of a NYSE-listed stock. We measure the expected information content of each trade by estimating its permanent price impact. It depends on observable trade features and market conditions. We also estimate the time required for quotes to incorporate all the information content of a particular trade. Our results show that price discovery is faster after risky trades and also at the extreme intervals of the session. The quote adjustment to trade-related shocks is progressive and this causes risk persistency and unusual short-term market conditions.     

Price discovery and common factor models

If a financial asset is traded in more than one market, common factor models may be used to measure the contribution of these markets to the price discovery process. We examine the relationship between the Hasbrouck (J. Finance (50) (1995) 1175) and Gonzalo and Granger (J. Bus. Econ. Stat. 13 (1995) 27) common factor models. These two models complement each other and provide different views of the price discovery process between markets. The Gonzalo and Granger model focuses on the components of the common factor and the error correction process, while the Hasbrouck model considers each market's contribution to the variance of the innovations to the common factor. We show that the two models are directly related and provide similar results if the residuals are uncorrelated between markets. However, if substantive correlation exists, they typically provide different results. We illustrate these differences using analytic examples plus a real world example consisting of electronic communications networks (ECNs) and other Nasdaq market makers.     

Can Island Provide Liquidity and Price Discovery in the Dark?

On September 23, 2002, facing a regulatory mandate issued by the Securities and Exchange Commission, Island teminated the position of the Nasdaq 100 Index Tracking Stock (QQQ) on its book. While the market volume remained almost the same, Island's market share in the QQQ fell significantly. However, Island still dominates other trading centers in the price discovery process and volatility spillovers. The spreads on most trading centers became narrower after Island removed its quotes from the public view. The overall results suggest that the decrease in market transparency does not compromise market liquidity. Informed traders who provide price discovery in the QQQ are willing to sacrifice potential price improvements for the fast speed and reliable execution that Island offers, and are able to trade in the absence of displayed quotes.     

The dynamics of price discovery for cross-listed shares: Evidence from Australia and New Zealand

This paper studies the dynamics of price discovery for markets with bilateral cross-listings. Using a sample of four Australian stocks cross-listed in New Zealand and five New Zealand stocks cross-listed in Australia for the period January 2002 to December 2007, we assess Hasbrouck (1995) information shares and Grammig et al. (2005) conditional information shares over time. We observe that in both cases the home market is dominant in terms of price discovery. However, when studying price discovery over time, we find that the importance of the Australian market (the larger of the two markets) is increasing for both Australian and New Zealand domiciled firms. Finally, using panel regression analysis, we find that the growth in the importance of the Australian market is positively related to the growth in the size of the firm and negatively related to the size of the percentage spread in the Australian market, implying that as firms grow larger and their cost of trading in Australia declines, the Australian market becomes more informative.     

Price Discovery without Trading: Evidence from the Nasdaq Preopening

This paper studies Nasdaq market makers' activities during the one and one-half hour preopening period. Price discovery during the preopening is conducted via price signaling as opposed to the auction used to open the NYSE or the continuous market used during trading. In the absence of trades, Nasdaq dealers use crossed and locked inside quotes to signal to other market makers which direction the price should move. Furthermore, we find evidence of price leadership among market makers that bears little resemblance to their IPO\SEO lead underwriter participation.     

Price Discovery in Initial Public Offerings and the Role of the Lead Underwriter

We examine the price discovery process of initial public offerings (IPOs) using a unique dataset. The first quote entered by the lead underwriter in the five-minute preopening window explains a large proportion of initial returns even for hot IPOs. Significant learning and price discovery continues to take place during these five minutes with hundreds of quotes being entered. The lead underwriter observes the quoting behavior of other market makers, particularly the wholesalers, and accordingly revises his own quotes. There is a strong positive relationship between initial returns and the time of day when trading starts in an IPO.     

Does Algorithmic Trading Improve Liquidity?

Algorithmic trading (AT) has increased sharply over the past decade. Does it improve market quality, and should it be encouraged? We provide the first analysis of this question. The New York Stock Exchange automated quote dissemination in 2003, and we use this change in market structure that increases AT as an exogenous instrument to measure the causal effect of AT on liquidity. For large stocks in particular, AT narrows spreads, reduces adverse selection, and reduces trade‐related price discovery. The findings indicate that AT improves liquidity and enhances the informativeness of quotes.