A SPECIALIST'S QUOTED DEPTH AS A STRATEGIC CHOICE VARIABLE: AN APPLICATION TO SPREAD DECOMPOSITION MODELS

Although there is a sizable literature demonstrating that liquidity and transaction costs are multidimensional, researchers continue to estimate adverse‐selection costs using only prices. We present a model of a profit‐maximizing specialist who posts prices and depths. The model is simulated to measure changes in the adverse‐selection component of the spread that result under different levels of informed trading. We find that spread decompositions fail to capture the full extent of adverse‐selection risk when specialists choose depth. We recommend that researchers use adverse‐selection measures that account for depth as well as spread to mitigate this problem.     

Market Quote and Spread Component Cost Behavior Around Trading Halts for Stocks Interlisted on the Montreal and Toronto Stock Exchanges

We use intraday quotes and transactions on halted securities that interlisted on the Toronto Stock Exchange and Montreal Exchange to decompose the spreads and examine quote depths. Our results show that order‐processing costs differ for trading halts at the open compared to halts during the rest of the trading day. We find that the adverse‐selection cost component of the spread is higher around trading halts and highest at the trading halt. We also find that print‐media articles that appear within the four‐day window centered on the halt have no impact on the time‐series behavior of the spread cost.     

Adverse-Selection Costs and the Probability of Information-Based Trading

Prior studies offer various empirical models to decompose the observed bid‐ask spread into the adverse‐selection and transitory (order‐processing and inventory‐holding) components. There is limited evidence, however, on whether the spread components estimated from these models indeed measure what they purport to measure. In this study, we show that the estimates of the adverse‐selection component given by these models are positively and significantly related to the probability of information‐based trading (PIN), after controlling for the endogeneity of the PIN and other stock attributes. These results provide direct empirical support for the spread component models examined in the present study.     

Specialists,Limit‐Order Traders,and the Components of the Bid‐Ask Spread

This study compares the components of the bid‐ask spread estimated from quotes that reflect the trading interest of specialists with those estimated from limit‐order quotes and all available quotes for a sample of New York Stock Exchange (NYSE) stocks. The results show that the adverse selection component of the spread estimated from specialist quotes is significantly smaller than the corresponding figures from limit‐order quotes and entire quotes. We interpret this as evidence that NYSE specialists transfer at least a part of adverse selection costs to outsiders through the discretionary use of limit orders. Our results show that the estimation/interpretation of the components of the spread using quote data that include both specialist and limit‐order interests is problematic.     

TRADE SIZE AND INFORMED TRADING: WHICH TRADES ARE “BIG”?

We find adverse‐selection spread components increase sharply in the ratio of trade size to quoted depth, and spike when trade size equals quoted depth. We find that two previously documented and prominent indicators of informed trading, raw trade size and high‐trading volume half‐hours, offer almost no explanatory power for informed trading measures beyond trade size to quoted depth, and a third indicator, time of day, offers no explanatory power among trades with high trade size to quoted depth. Our results suggest trade size to quoted depth is perhaps the single most important indicator that a trade is informed.     

Investor protection, adverse selection, and the probability of informed trading

The purpose of this study is to investigate the relation between investor protection, adverse selection, and the probability of informed trading. Previous research has established a direct relation between investor protection and firm liquidity, measured by bid-ask spreads and depths. In this study, we test the hypothesis that adverse selection is the mechanism through which poor investor protection leads to higher costs of liquidity. The Hong Kong equity market provides a unique opportunity to compare adverse selection differences across distinct investor protection environments, holding constant the trading platform and currency. Using various bid-ask spread decomposition models and probability of informed trading estimates, we confirm the hypothesized relation between investor protection quality and adverse selection costs. These findings contribute to the literature by establishing one of the links in the chain connecting investor protection to firm valuation.

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.     

INTRADAY VARIATIONS IN TRADING ACTIVITY,PRICE VARIABILITY,AND THE BID-ASK SPREAD

In this paper intraday variations in trading activity and the bid-ask spread are examined. Intraday variations in volume and price variability demonstrate a U-shaped pattern as in previous studies. However, I find a U-shaped pattern for a measure of the spread component that is related to the degree of information asymmetry between the specialist and informed traders and an inverted U-shaped pattern for the other spread component related to inventory and order costs. Two alternative explanations are given.     

A Specialist's Quoted Depth and the Limit Order Book

By partitioning quoted depth into the specialist's contribution and the limit order book's contribution, the paper investigates whether specialists manage quoted depth to reduce adverse selection risk. The results show that both specialists and limit order traders reduce depth around information events, thereby reducing their exposure to adverse selection costs. Moreover, specialists' quotes may reflect only the limit order book on the side (or sides) of the market where they believe there is a chance of informed trading. Changes in quoted depth are consistent with specialists managing their inventory as well as having knowledge of the stock's future value.     

Co‐managers,Information, and the Secondary Market Liquidity of Initial Public Offerings

We provide evidence that co‐managers improve initial public offering (IPO) liquidity through the “information” services they provide. Based on a sample of IPOs completed from January 1993 to December 2005, we find that a high number of co‐managers in the syndicate are associated with a lower spread, lower adverse selection costs, and a lower probability of informed trading. Moreover, increases in the offer price revision, in co‐managers’ underwriting rank, and in the number of analyst recommendations are all associated with the improvement in liquidity. This evidence is consistent with the hypotheses that co‐managers’ premarket and postmarket services mitigate information risk in the aftermarket.     

Knowing me, knowing you: : Trader anonymity and informed trading in parallel markets

In this paper we empirically analyze whether the degree of trader anonymity is related to the probability of information-based trading. We use data from the German stock market where non-anonymous traditional floor based exchanges co-exist with an anonymous computerized trading system. We use an extended version of the Easley et al. (J. Finance 51 (1996) 1405) model that allows for simultaneous estimation for two parallel markets. We find that the probability of informed trading is significantly lower in the floor based trading system. We further document that the size of the spread and the adverse selection component are positively related to the estimated probabilities of information-based trading.     

Specialist Risk Attitudes and the Bid‐Ask Spread

This paper examines the relation between the bid‐ask spread and the risk of the underlying stock. It provides evidence that the specialist is not only sensitive to the absolute level of volatility, but also to changes in the level of volatility. This sensitivity arises because of increased inventory risk for the specialist when volatility is changing. For the sample of very liquid stocks in this paper, the quoted spread and the inventory cost component of the spread are shown to increase significantly during trading periods when volatility is both increasing and decreasing.     

The relationship between the frequency of news release and the information asymmetry: The role of uninformed trading

This paper shows that the degree of information asymmetry is lower for firms with more frequent news releases. The relation holds for various measures of information asymmetry such as the probability of information-based trading (PIN), permanent price impact, and adverse selection component of bid-ask spread, even after adjusting for endogeneity between news release and information asymmetry. By decomposing the PIN into intensities of uninformed and informed trades, similarly to Brown and Hillegeist (2007), we find that intensity of uninformed trading increases much more than that of informed trading for firms with more frequent news releases. As a result, information asymmetry, as is measured by PIN, decreases for such firms due to the large increase in the intensity of uninformed trading. Our findings highlight not only the importance of news releases in leveling the playing field of investors but also the role of uninformed investors in reducing trading cost due to information asymmetry.     

An analysis of depth behavior in an electronic, order-driven environment

The purpose of this study is to investigate inter-temporal and cross-sectional depth patterns in an electronic, order-driven environment. Although many exchanges operate in this environment, little is known about the liquidity dynamics induced by such trading mechanisms. The findings, based on over six million observations, reveal an inverted U-shaped pattern that mirrors the commonly reported U-shaped spread pattern. An important implication is that earlier spread results understate the strength of inter-temporal liquidity variations. Cross-sectional analysis, based on adverse selection-sorted portfolios, demonstrates that corporate depth is negatively related to information asymmetry. The adverse selection impact on liquidity and cost of capital is stronger than previously believed since information costs are realized through both spreads and depths.     

Estimating the Probability of Informed Trading

Using a new empirical model, I estimate the probability of trades being generated by privately informed traders. Inference is drawn on a trade‐by‐trade basis using data samples from the New York Stock Exchange (NYSE). The modeling setup facilitates in‐depth analysis of the estimated probability of informed trading at the intraday level and for stocks with different levels of trading activity. The most important empirical results are: (a) the intradaily pattern of the inferred probability of informed trading is highly correlated with the intradaily pattern of observed quoted spreads, (b) differences in the magnitude of quoted spreads across volume categories are not exclusively related to differences in the level of informed trading, and (c) private information is incorporated faster in the quotes for high‐volume stocks than in the quotes for low‐volume stocks.     

Earnings Announcements and the Components of the Bid-Ask Spread

This study investigates the behavior of the components of the bid-ask spread around earnings announcements. We find that the adverse selection cost component significantly increases surrounding the announcements, while the inventory holding and order processing components significantly decline during the same periods. Our results suggest that the directional change in the total bid-ask spread depends on the relative magnitudes of the changes in these three components. Specifically, the decreases in inventory holding costs and order processing costs imply that earnings announcements may have an insignificant impact on the total bid-ask spread, even when they result in increased information asymmetry.     

Testing for micro-structure effects of international dual listings using intraday data

This paper examines the impact on the liquidity of NYSE/AMEX listed stocks when they were subsequently listed on the London or the Tokyo Stock Exchanges. It can be argued that the increased competition from foreign market makers will reduce the monopoly rents that specialists can earn, thereby improving their quotes. We find, however, that spreads do not decrease following a dual listing, though the depth of the quotes increases as predicted. The apparent increase in depth disappears once we account for changes in price, volume and return variance. We also find that the level of informed trading increases, which increases the cost to the specialist of providing liquidity, and explains why spreads do not decline in spite of increased competition. Consistent with an increase in informed trading, we also document an increase in trading activity.     

The Effect of Decimalization on Trade Size and Adverse Selection Costs

Abstract:   We examine adverse selection costs around NYSE decimalization. Further, we analyze the relation between adverse selection costs and trade size. We find a significant increase in the percentage adverse selection cost and a reduction in dollar adverse selection cost (percentage adverse selection multiplied by the spread) following complete decimalization on the NYSE. On estimating the adverse selection components by trade size classes, we find a decline in dollar adverse selection costs in trades of all sizes, with the strongest evidence coming from medium size trades, followed by small and large size trades. One implication of our findings is that there appears to be less stealth trading following complete decimalization and less institutional trading overall.     

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.     

A microstructure examination of trading activity following stock splits

In a study of 1,131 stock splits spanning the period 1983–1989 we observe an increase in the number of trades as well as a reduction in the mean trade size following the split. Combined with earlier reported findings of an increase in the number of shareholders postsplit, we conclude that the number of liquidity traders increases after a split. We confirm the previously observed increase in the bid-ask spread following a split, and upon decomposition of the spread find an increase in its adverse selection component in the postsplit period. This is consistent with the finding by Brennan and Hughes (1991) of an increase in the number of analysts following a stock after a split. Further, observing a decrease in market depth following a split we determine that Kyle-type models incorporating diverse private information for informed traders most correctly describe the nature of security trading. Since this decrease in postsplit market depth is not related to the trading volume or the split factor, we reject price correction explanations for stock splits.