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.     

Measuring abnormal daily trading volume for samples of NYSE/ASE and NASDAQ securities using parametric and nonparametric test statistics

We extend prior research on the empirical properties of daily trading volume and methods to detect abnormal trading volume in two ways. We compare the performance of a nonparametric test statistic with the parametric test statistic used in prior research and we study samples of NASDAQ securities as well as samples of NYSE/ASE securities. Prior research has focused exclusively on NYSE securities. We find the nonparametric test statistic is more powerful in detecting abnormal trading volume than the parametric test statistic in both samples of NYSE/ASE and NASDAQ securities. We also document that abnormal trading volume will be detected more often in samples of NYSE/ASE securities compared to NASDAQ securities.     

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.     

Characteristics and mechanisms of the U.S. stock market spillover effects on the Chinese A-share market: Evidence from 6 A-share broad-based and 31 sector indices

This study investigated the NYSE and NASDAQ composite indices' return and volatility spillover on 37 Chinese A-share indices. We used data from 2010 to 2022 with Multiplicative-Heteroskedasticity-GARCHX and rolling window analysis. We also applied a vector autoregression and impulse response analysis to study the relationship between the spillover effect and market return or volume condition. We found that: (1) the spillover effect of U.S. stocks can be quickly and mostly absorbed by the A-share market in the next trading day; (2) the dissimilarity of constituents among A-share indices contributes to the differences in the NYSE and NASDAQ spillover effects; (3) the spillover becomes more significant and prominent when the market performance is poor or when some special events occurred.     

THE OVER-THE-COUNTER MARKET AND NEW YORK STOCK EXCHANGE TRADING HALTS

This paper examines the over-the-counter (OTC) market activities for stocks temporarily suspended by the New York Stock Exchange (NYSE). Unlike previous studies, we use transaction-to-transaction data on the NASDAQ during NYSE trading halts to investigate the price adjustment process between market equilibria. The evidence indicates that while being halted by the NYSE, the same stocks have exhibited significantly greater volatility in the OTC market. Since the volatile price movement is mainly random and provides no arbitraging opportunities for the OTC market traders, we do not find support for the proposal that trading halts should be mandatory for all trading locations.     

When noise trading fades,volatility rises

We hypothesize and test an inverse relation between liquidity and price volatility derived from microstructure theory. Two important facets of liquidity trading are examined: volume and noisiness. As represented by the expected turnover rate (volume) and realized average commission cost per share (noisiness) of NYSE equity trading, both facets are found negatively associated with the ex post and ex ante return volatilities of the NYSE stock portfolios and the NYSE composite index futures. Furthermore, the inverse association between noisiness and volatility is amplified in times of market crisis. The negative noisiness–volatility relation is also supported by our analysis on the effects of trade size on price volatility. The overall results demonstrate that volatility increases as noise trading declines.     

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.     

Information demand and stock market volatility

We study information demand and supply at the firm and market level using data for 30 of the largest stocks traded on NYSE and NASDAQ. Demand is approximated in a novel manner from weekly internet search volume time series drawn from the recently released Google Trends database. Our paper makes contributions in four main directions. First, although information demand and supply tend to be positively correlated, their dynamic interactions do not allow conclusive inferences about the information discovery process. Second, demand for information at the market level is significantly positively related to historical and implied measures of volatility and to trading volume, even after controlling for market return and information supply. Third, information demand increases significantly during periods of higher returns. Fourth, analysis of the expected variance risk premium confirms for the first time empirically the hypothesis that investors demand more information as their level of risk aversion increases.     

Emerging from Bankruptcy with When‐Issued Trading

We examine the set of firms that emerged from Chapter 11 bankruptcy and traded on a when‐issued basis before their official return to the regular way in NASDAQ, Amex, or NYSE. We find that this when‐issued market is liquid and price efficient. The when‐issued closing price is a good indicator of the first closing price in the regular way market. Emerging firms that have when‐issued trading experience lower regular way volatility and smaller relative spreads than those without when‐issued trading. Our probit regressions show that firm size is an important determinant of the adoption of when‐issued trading.     

Preferenced Trading,Quote Competition,and Market Quality: Evidence from Decimalization on the NYSE

We examine the impact of decimalization on preferenced trading in NYSE‐listed stocks and show a significant decline in preferenced trading around decimalization. For the largest NYSE stocks, the total decline is nearly 22%. We also find a negative correlation between the changes in preferenced trading and the changes in quote competition intensity, and a positive correlation between the changes in preferenced trading and the changes in spreads. Consistent with the cream skimming hypothesis, we find that abnormal changes in information asymmetry cost for NYSE trades are positively correlated with the changes in preferenced trading.