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.     

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.     

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.     

LIQUIDITY AND QUOTE CLUSTERING IN A MARKET WITH MULTIPLE TICK SIZES

We analyze market liquidity (i.e., spreads and depths) and quote clustering using data from the Kuala Lumpur Stock Exchange (KLSE), where the tick size increases with share price in a stepwise fashion. We find that stocks that are subject to larger mandatory tick sizes have wider spreads and less quote clustering. We also find that liquidity providers on the KLSE do not always quote larger depths for stocks with larger tick sizes. Overall, our results suggest that larger tick sizes for higher priced stocks are detrimental to market liquidity, although the adverse effect of larger tick sizes is mitigated by lower negotiation costs (i.e., less quote clustering).     

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.     

Liquidity in auction and specialist market structures: Evidence from the Italian bourse

Several studies find that bid-ask spreads for stocks listed on the NYSE are lower than for stocks listed on NASDAQ. While this suggests that specialist market structures provide greater liquidity than competing dealer markets, the nature of trading on the NYSE, which comprises a specialist competing with limit order flow, obfuscates the comparison. In 2001, a structural change was implemented on the Italian Bourse. Many stocks that traded in an auction market switched to a specialist market, where the specialist controls order flow. Results confirm that liquidity is significantly improved when stocks commence trading in the specialist market. Analysis of the components of the bid-ask spread reveal that the adverse selection component of the spread is significantly reduced. This evidence suggests that specialist market structures provide greater liquidity to market participants.     

Removing biases in computed returns

This paper presents a straightforward method for asymptotically removing the well-known upward bias in observed returns of equally-weighted portfolios. Our method removes all of the bias due to any random transient errors such as bid-ask bounce and allows for the estimation of short horizon returns. We apply our method to the CRSP equally-weighted monthly return indexes for the NYSE, Amex, and NASDAQ and show that the bias is cumulative. In particular, a NASDAQ index (with a base of 100 in 1973) grows to the level of 17,975 by 2006, but nearly half of the increase is due to cumulative bias. We also conduct a simulation in which we simulate true prices and set spreads according to a discrete pricing grid. True prices are then not necessarily at the midpoint of the spread. In the simulation we compare our method to calculating returns based on observed closing quote midpoints and find that the returns from our method are statistically indistinguishable from the (simulated) true returns. While the mid-quote method results in an improvement over using closing transaction prices, it still results in a statistically significant amount of upward bias. We demonstrate that applying our methodology results in a reversal of the relative performance of NASDAQ stocks versus NYSE stocks over a 25 year window.     

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.     

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.     

Tick size,market structure,and market quality

Large tick sizes imposed on high-priced stocks on the Korea Stock Exchange (KSE) are significant binding constraints on bid-ask spreads. Nearly 60% of quoted spreads are equal to the tick size for stocks with the largest tick size and more than 87% of quoted spreads are equal to the tick size for stocks in the largest size portfolio. We also show that the average spread of KSE stocks with large tick sizes is greater than that of matched NYSE stocks, whereas the average spread of KSE stocks with the smallest tick size is smaller than the corresponding figure for the matched NYSE stocks. We interpret these results as evidence that traders on the KSE are paying large trading costs because of the artificially imposed large tick sizes.     

Adverse selection costs for NASDAQ and NYSE after decimalization

NYSE and NASDAQ completed their decimalization on January 29, 2001 and on April 9, 2001 respectively. In this paper, we compare adverse selection component of the bid–ask spread for NASDAQ and NYSE stocks after decimalization using the data from May 2001 and July 2001. We find that the adverse selection component of the bid–ask spread is significantly lower on NASDAQ than on NYSE, and these differences cannot be attributed to the differences in the characteristics of the stocks traded in the two markets. In addition, we find that the adverse selection costs increase with trade size on NYSE, however there is no monotonic pattern observed for NASDAQ stocks. Lastly, we report that although the order flows arrived in the two markets are significantly different, they can at best explain a small portion of the observed differences in adverse selection costs.     

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.     

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.     

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.     

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."     

The competitive effects of US decimalization: Evidence from the US-listed Canadian stocks

This paper analyzes the impact of US decimalization on the Canadian stocks listed on the Toronto Stock Exchange (TSE) and either the New York Stock Exchange (NYSE) or National Association of Securities Dealers Automated Quotation System (Nasdaq) in the US. Using a sample of 126 firms, we find that the US trading of these stocks increases after decimalization, but this increase is not at the expense of TSE volume. Indeed, the TSE volume increases substantially for those securities that are traded on Nasdaq and increases marginally for those securities that are traded on the NYSE. Most of the increase in volume is in retail-sized trades. The bid–ask spreads and the quote depths decline on all exchanges, but by a greater amount in the US than in Canada. The depths on the NYSE decline from being above the TSE depths to well below the TSE depths. We also find that the decline in the TSE spread is directly related to the size of the firm and to the decline in the US spread, and is inversely related to the pre-decimalization ratio of spreads on the US exchange and the TSE. Overall, our results indicate that the US decimalization had the desired positive impact on trading in both the US and Canada, with a decrease in spreads and an increase in retail-sized trading.     

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.     

TRADING OF NASDAQ STOCKS ON THE CHICAGO STOCK EXCHANGE

We use a linear programming model to form two portfolios with approximately equal levels of attributes such as financial leverage. One portfolio comprises stocks that trade exclusively on NASDAQ and the other, stocks that trade on both the Chicago Stock Exchange (CSE) and NASDAQ (CSE/NASDAQ). We find that spreads are lower for the CSE/NASDAQ portfolio, but so is the percentage of quotes at spreads of $0.125. In fact, the lower spreads observed for the CSE/NASDAQ portfolio arise from fewer quotes with spreads of more than $0.25.     

Dealer attention,the speed of quote adjustment to information,and net dealer revenue

Using trade and quote data from the NYSE, we examine the relation between dealer attention, dealer revenue, and the probability of informed trade. We find that dealer revenue net of losses to better-informed traders in NYSE stocks is positively related to the speed at which quotes adjust to full information levels. The speed of quote adjustment is faster for stocks with greater dealer attention, as measured by a stock’s relative prominence at its post and panel location on the NYSE floor. The level of dealer attention in turn is positively related to a stock’s probability of information-based trading. The results are consistent with a theoretical model we derive in which dealers trade multiple securities and must optimally allocate their limited attention to monitoring order flow to minimize losses to better-informed traders.     

Reversal of 3‐day losers and continuation of 3‐day winners on the NASDAQ

Using only the 200 large-cap securities that make up the NYSE 100 and NASDAQ 100, this study investigates 130 randomly selected formation periods from January 2000 through December 2012. During these formation periods, the three worst and three best performing stocks (based on excess return) are flagged. Once flagged, the subsequent 10-day holding period excess returns are calculated. Results indicate that NYSE securities demonstrate significant return reversal, but not return momentum. Conversely, the worst performing NASDAQ securities demonstrate return reversal, whereas the best performing NASDAQ securities demonstrate return momentum. Results are robust to the number of best and worst stocks that are flagged. Results are also robust to other combinations of formation and holding period lengths.