MARKET STRUCTURE AND REPORTED TRADING VOLUME: NASDAQ VERSUS THE NYSE

Trading volume for common stocks is of interest to financial economists, investors, and securities lawyers. NASDAQ is a dealer market where trades with dealers are included in reported trading volume. This procedure does not accurately measure the trading volume by public buyers and sellers. Trading volume reported on the NYSE, which is primarily an auction market, provides a much closer measure of trades by public investors. We examine a sample of firms whose stock traded on the NASDAQ/NMS and subsequently on the NYSE. When trading switches to the NYSE, the firms' trading volume drops to about 50 percent of the volume previously reported on NASDAQ. A control group of firms that switched from the AMEX to the NYSE shows a small, but statistically insignificant, increase in trading volume.     

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.     

The role of trades in price convergence: A study of dual-listed Canadian stocks

We examine the role of trades in restoring price parity for equities trading in multiple markets. Using a sample of stocks trading on the Toronto Stock Exchange and on the NYSE, AMEX or NASDAQ, we contrast price convergence when market makers (a) observe only lagged quotes from both markets and (b) also observe local order flow. Traditional error correction model estimates show that prices in the two markets adjust towards parity in response to quoted price discrepancies, meaning that observation of the cross-market quote helps restore parity. Including order flow in an augmented error correction model, we find that incremental price convergence occurs when trades are routed to the market with the better price, and the importance of quotes in the price convergence process is reduced. Cross-sectional analysis reveals that the importance of order flow in each market is decreasing in firm size and increasing in measures of liquidity. Our findings point to an important, and hitherto unexamined, role for trades in promoting inter-market price convergence.     

Competition For Order Flow, Market Quality, And Price Discovery In The Nasdaq 100 Index Tracking Stock

We investigate competition for order flow, market quality, and price discovery in the Nasdaq 100 Index Tracking Stock (QQQ). The QQQ, an AMEX‐listed, exchange‐traded fund, is the most actively traded security in the U.S. equities market. On July 31, 2001, the NYSE began trading the QQQ, marking the first time it traded securities of companies it does not list. The greatest volume of trading takes place on electronic communication networks (ECNs), following by trading on the AMEX and the NYSE. Most of the block trades are executed on the AMEX, where the bid‐ask spreads are narrower. We find that ECNs contribute the most to the price‐discovery process. The spreads on all trading platforms have decreased and market quality and price discovery have improved since QQQ shares have traded on the NYSE.     

Post-listing underperformance: Is it really bad to move trading locations?

We reexamine the post-listing puzzle by studying the stock performance of 2103 firms that moved from NASDAQ to NYSE or AMEX, or from AMEX to NYSE during 1973–1999. The matched four-factor regressions demonstrate that the listing firms do not underperform. Size-and-book-to-market matched factor regression finds that the “post-listing drift” is confined to the small set of firms moving from NASDAQ to AMEX during 1981–1990, within size deciles 3–6 and book-to-market quintiles 1–3. A further control of the industry effect is able to resolve the remaining abnormal returns. Our results are consistent with the pseudo market timing hypothesis in Schultz, (2003) [Schultz, P., 2003. Pseudo market timing and the long-run underperformance of IPOs. J. Fin. 58, 483–517.].     

The valuation effects of the 1977 Community Reinvestment Act and its enforcement

We examine the wealth effects of the passage of the Community Reinvestment Act (CRA) of 1977 for commercial banks and savings and loan associations. we find significantly negative average excess returns for small NYSE/AMEX banks and S&Ls to certain events concerned with the passage of the CRA; in contrast, there is no evidence that large NYSE/AMEX institutions or NASDAQ institutions experience wealth losses. We also study the effects of individual CRA protests against institutions and find they produce significantly negative excess returns which are not reversed when the protests are resolved. Our results have implications for proposed changes to CRA and for the future consolidation of the financial services industry. The results also demonstrate the difficulties associated with studying returns from the early years of the NASDAQ market.     

The Operating Performance of Firms that Switch Their Stock Listings

In this article we examine the operating performance of stocks that switch from NASDAQ to the American Stock Exchange (AMEX) or the New Stock Exchange (NYSE) and from AMEX to the NYSE. Specifically, we investigate whether post‐listing operating performance is consistent with the reported negative long‐term drift of post‐listing stock returns and whether there is evidence of self‐selection of the listing time. We find evidence of negative post‐listing changes in operating return on assets and sales, which, on a match‐adjusted basis, are significant for the relatively small NASDAQ stocks switching to AMEX. We also find evidence that firms self‐select the time of listing changes.     

Estimating bid-ask spread components: Specialist versus multiple market maker systems

This paper tests two competing hypotheses concerning the relationship between adverse selection costs on NASDAQ versus specialist-dominated exchanges. We reject the hypothesis that specialist-dominated exchanges have smaller adverse selection costs than exchanges with multiple market makers. We provide direct evidence on the timing differences between closing transactions and quotes as well as evidence on the extent of nontrading on the AMEX and NYSE but cannot reject the hypothesis that adverse selection costs are a function of average transaction size (which is generally larger on the AMEX and NYSE). We also provide insight into institutional differences across exchanges and the ISSM data base.     

SECURITY RETURN DISTRIBUTIONS AND MARKET STRUCTURE: EVIDENCE FROM THE NYSE/AMEX AND THE NASDAQ MARKETS

This paper documents significant and persistent deviations from normality in security return distributions for the NYSE, AMEX, and NASDAQ from 1974 to 1988. Controlling for January and size effects, we find that the deviations of security return distributions from normality decline with increasing portfolio size and investment horizon for the NYSE and AMEX, especially for daily returns. Deviations appear to be greater for the NASDAQ than for the two exchanges even for firms of the same size. Ratios of monthly to daily variances are also larger for the NASDAQ. These results suggest that nonparametric or other robust statistical techniques should be used when valuing equity options and other derivatives, especially when examining NASDAQ security returns. They further imply that trading strategies based on market inefficiencies are more likely to succeed on the NASDAQ.     

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.     

MARKET STRUCTURE AND TRADING VOLUME

Historically, trading volume reported for NASDAQ stocks has been overstated vis‐à‐vis New York Stock Exchange (NYSE) stocks, both because of the dealer's participation in trades as a market maker and because of interdealer trading. Beginning in 1997, the Securities and Exchange Commission changed order‐handling rules and trade‐reporting rules, which may have reduced or eliminated the overstatement of NASDAQ trading. We examine trading volumes of firms changing from NASDAQ to the NYSE since 1997 and document that reported trading volume for NASDAQ stocks continues to be overstated. Moreover, the degree of overstatement is much larger for firms with high trading volume.     

THE EFFECT OF THE 1986 TAX REFORM ACT ON EX-DIVIDEND DAY RETURN BEHAVIOR

In this study I examine whether the Tax Reform Act of 1986 has an effect on ex-date stock return behavior. Results indicate that the tax reform has a significant effect on ex-date returns for NASDAQ stocks, but not for NYSE/AMEX stocks. Further analysis suggests that the ex-date returns on NASDAQ stocks are primarily determined by the tax premium. However, the ex-date returns on NYSE/AMEX stocks are more influenced by short-term trading.     

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.     

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).     

Determinants of the components of bid-ask spreads on stocks

In this paper we show that George et al. (GKN, 1991) estimators of the adverse selection and order processing cost components of the bid-ask spread are biased due to intertemporal variations in the bid-ask spread. We use alternative estimators that correct this bias and that are applicable to individual securities, and estimate these cost components empirically using data on NYSE/AMEX stocks. As expected, our results indicate that on average adverse selection costs account for approximately 50% of the bid-ask spread, sharply higher than the estimates of 8-10% obtained by GKN for NASDAQ stocks and 21% that we obtain for NYSE/AMEX stocks using GKN's estimators. We then conduct cross-sectional regressions designed primarily to determine whether adverse selection costs vary across specialists after controlling for firm size and other factors. Consistent with previously established hypotheses, we find that adverse-selection costs vary across specialists, and that this variation is related to the number of securities that the specialist handles.     

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.     

Volume autocorrelation,information, and investor trading

This study investigates whether the widely documented daily correlated trading volume of stocks is driven by individual investor trading, institutional trading, or both. We find that at least 95% of NYSE and AMEX stocks exhibit statistically significant, positive serial correlation. Volume autocorrelation decreases with the level of institutional ownership of a stock. We also show that the rate of arrivals of new information to the market contributes to the clustering of trades. When there is high information flow to the market, institutional trading generates a more pronounced effect on volume autocorrelation than individual investor trading. Our results are broadly consistent with the predictions of trading volume patterns suggested by most theoretical models of stock trading and by empirical research on investor trading.     

LIQUIDITY AND ASSET PRICING UNDER THE THREE‐MOMENT CAPM PARADIGM

We examine whether the use of the three‐moment capital asset pricing model can account for liquidity risk. We also make a comparative analysis of a four‐factor model based on Fama–French and Pástor–Stambaugh factors versus a model based solely on stock characteristics. Our findings suggest that neither of the models captures the liquidity premium nor do stock characteristics serve as proxies for liquidity. We also find that sensitivities of stock return to fluctuations in market liquidity do not subsume the effect of characteristic liquidity. Furthermore, our empirical findings are robust to differences in market microstructure or trading protocols between NYSE/AMEX and NASDAQ.     

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.     

Order dynamics: Recent evidence from the NYSE

We examine investor order choices using evidence from a recent period when the NYSE trades in decimals and allows automatic executions. We analyze the decision to submit or cancel an order or to take no action. For submitted orders, we distinguish order type (market vs. limit), order side (buy vs. sell), execution method (auction vs. automatic), and pricing aggressiveness. We find that the NYSE exhibits positive serial correlation in order type on an order-by-order basis, which suggests that follow-on order strategies dominate adverse selection or liquidity considerations at a moment in time. Aggregated levels of order flow also exhibit positive serial correlation in order type, but appear to be non-stationary processes. Overall, changes in aggregated order flow have an order-type serial correlation that is close to zero at short aggregation intervals, but becomes increasingly negative at longer intervals. This implies a liquidity exhaustion–replenishment cycle. We find that small orders routed to the NYSE's floor auction process are sensitive to the quoted spread, but that small orders routed to the automatic execution system are not. Thus, in addition to foregoing price improvement, traders selecting the speed of automatic executions on the NYSE do so with little regard for the quoted cost of immediacy. As quoted depth increases, traders respond by competing on price via limit orders that undercut existing bid and ask prices. Limit orders are more likely and market sells are less likely late in the trading day. These results are helpful in understanding the order arrival process at the NYSE and have potential applications in academics and industry for optimizing order submission strategies.