Related securities and price discovery: Evidence from NYSE-listed Non-U.S. stocks

In this paper we analyze whether handling related securities improves a market maker's information environment and helps to incorporate new information in stock prices. Our empirical tests are focused on New York Stock Exchange specialists and the U.S. share in price discovery of 64 British and French companies cross-listed on the NYSE. We define related securities as stocks from the same country, the same region, or other foreign stocks. We find strong evidence that a higher prominence of related stocks in the specialist portfolio is associated with a higher U.S. share in price discovery of our sample firms. We interpret our findings as evidence that concentrating market makers in similar stocks reduces information asymmetries and improves the information environment as market makers can extract information relevant to a stock from order flow to related securities. To support our argument, we show that the adverse selection component of the bid–ask spread is negatively related to the prominence of other foreign stocks in the specialist portfolio.     

Regulation Fair Disclosure and the Cost of Adverse Selection

Regulation Fair Disclosure (FD), imposed by the Securities and Exchange Commission in October 2000, was designed to prohibit disclosure of material private information to selected market participants. The informational advantage such select participants gain is unclear. If multiple “insiders” receive identical information, private information is immediately incorporated in price and each insider has zero expected profit. If, on the other hand, Regulation FD has curtailed the flow of information from firms, private information becomes longer‐lived and more valuable. Hence, market makers will demand increased compensation by widening the adverse selection component of the bid‐ask spread. We identify the cost components of the bid‐ask spread for a sample of NASDAQ stocks surrounding the implementation of Regulation FD. Controlling for other factors affecting the spread, we find that adverse selection costs increase approximately 36% after Regulation FD. We interpret our finding as Regulation FD failing to achieve one of its desired objectives.     

The liquidity effects associated with addition of a stock to the S&P 500 index: evidence from bid/ask spreads

This study examines changes in stock liquidity, as measured by the bid/ask spread, when a stock is added to the S&P 500 Index. The paper presents evidence of a significant decrease in the bid/ask spread upon S&P 500 addition, however, this effect is limited to only those stocks that were not trading listed options. Further, the decrease in the bid/ask spread for nonoptioned stocks is accompanied by a significant and permanent increase in share price and trading volume. While optioned stocks experience a permanent increase in trading volume, they experience only a temporary increase in share price. The findings for optioned stocks support the hypothesis that the price and volume effects associated with S&P 500 addition derive from temporary price pressure. Findings pertaining to the nonoptioned stocks indicate that the price and volume effects associated with S&P addition reflect enhanced stock liquidity. The decrease in the bid/ask spread for nonoptioned stocks is attributed to informational efficiencies achieved via index arbitrage trading, and it is argued that this effect is mitigated for optioned stocks due to the pre-existence of arbitrage trading between the option and the underlying stock.     

Market Response to Liquidity Improvements: Evidence from Exchange Listings

The study examines a sample of 895 stocks that moved from Nasdaq to the New York Stock Exchange or to the American Stock Exchange (Amex) between 1971 and 1994. We show how various measures of liquidity such as the bid‐ask spread, trading volume, and stock price precision improve in somewhat different ways upon transfer to NYSE (Amex). We also find that reductions in trading costs (percentage spread) and in pricing error volatility (Hasbrouck's σ₅) can explain most of stock market's positive response to exchange listing. Thus, liquidity has many facets and cannot be represented by the bid‐ask spread alone.     

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.     

Minimum price variations, discrete bid-ask spreads, and quotation sizes

Exchange minimum price variation regulation's create discretebid-ask spreads. If the minimum quotable spread exceeds thespread that otherwise would be quoted, spreads will be wideand the number of shares offered at the bid and ask may be large.A cross-sectional discrete spread model is estimated by usingintraday stock quotation spread frequencies. The results areused to project 1/16 spread usage frequencies given a 1/16-tick.Projected changes in quotation sizes and in trade volumes areobtained from regression models. For stocks priced under 10,the models predict spreads would decrease 38 percent, quotationsizes would decrease 16 percent, and daily volume would increase34 percent.     

DAY‐END EFFECT ON THE PARIS BOURSE

We study the day‐end effect on the Paris Bourse, a computerized order‐driven market with competing dealers. The day‐end return is approximately double the magnitude found in U.S. data and is nearly four times larger for stocks trading with a registered dealer. However, this is largely explained by the time between trades and the bid‐ask spread. Unlike the U.S. data, the effect does not decline as stock price increases, probably because of a variable tick size in the Paris market. Finally, a change to a closing call auction in May 1996 for a subset of stocks did not reduce the day‐end effect.     

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.     

The relevance of information and trading costs in explaining momentum profits: Evidence from optioned and non-optioned stocks

Considerable evidence from many countries suggests momentum strategies generate profits. These have been difficult to rationalise and evidence on the sources of such profitability is inconclusive. We utilise a sample of optioned stocks, characterised by high liquidity, high market capitalisation and fewer short sales constraints and compare results with control samples of non optioned stocks chosen on the basis of market value, turnover and bid–ask spread. The sample characteristics, and the fact that derivatives improve the impounding of information into prices, enable us to draw conclusions about the causes of momentum profits. While we find that short sales constraints are not the major driver of profitability and that most momentum profits disappear using two transactions costs measures of the bid–ask spread, one not previously used, the persistence of some momentum profits indicates that the market underreacts even to the most publicly available information.     

NUMBER OF TRANSACTIONS AND VOLATILITY: AN EMPIRICAL STUDY USING HIGH‐FREQUENCY DATA FROM NASDAQ STOCKS

Our empirical evidence based on transactions data of a sample of Nasdaq stocks indicates that trades of large firms are related to the proxies of marketwide and firm‐specific information. For large firms, an increase in the number of trades seems to have a beneficial effect on liquidity as measured by bid‐ask spreads. On the other hand, trades of small and medium firms are associated with firm‐specific information and are not related to marketwide information. For small and medium firms, the frequency of trades is positively associated with bid‐ask spreads, apparently because of the adverse information content of trades. JEL classification: G10, G12, G13     

Effects of large shareholding on information asymmetry and stock liquidity

Prior studies, such as Claessens et al.’s [Claessens, S., Djankov, S., Fan, J., Lang, L., 2002. Disentangling the incentive and entrenchment effects of large shareholding. Journal of Finance 57, 2741–2771], suggest that deviation between ultimate control and ownership decreases firm value (due to the entrenchment effects of large shareholding). Using a sample of Canadian firms, we study the relation of ultimate control and ownership with an important dimension of stock liquidity – bid–ask spread. We find that stocks with greater deviations between ultimate control and ownership have a larger information asymmetry component of their bid–ask spread and wider bid–ask spread. Our results are consistent with the notion that the ultimate owners of these stocks may have selfish agendas. To increase the probability of the agendas being implemented, the firms may have poor information disclosure, resulting in poor stock liquidity.     

Short-term market reaction after extreme price changes of liquid stocks

In our empirical study we examine the dynamics of the price evolution of liquid stocks after experiencing a large intra-day price change, using data from the NYSE and the NASDAQ. We find a significant reversal for both intra-day price decreases and increases. Volatility, volume and, in the case of the NYSE, the bid–ask spread, which increase sharply at the event, stay significantly high days afterwards. The decay of the volatility follows a power law in accordance with the `Omori law'. While on the NYSE the large widening of the bid–ask spread eliminates most of the profits that can be achieved by an outside investor, on the NASDAQ the bid–ask spread stays almost constant, yielding significant short-term profits. The results thus give an insight into the size and speed of the realization of an excess return for providing liquidity in a turbulent market.     

Is the Adverse Selection Component Really Higher on the NYSE/Amex than on the Nasdaq?

Affleck–Graves, Hegde and Miller (1994) find that the adverse selection component of the bid–ask spread is higher for NYSE and Amex stocks than for Nasdaq stocks. Using the model of Huang and Stoll (1997), we revisit their study and find the opposite to be true – the adverse selection component is actually higher for Nasdaq stocks than for NYSE and Amex stocks. The economic magnitude of this additional adverse selection cost is very significant. Our results have important implications for the understanding of information production in dealer versus auction markets, and the costs of trading on such markets.     

DOES VOLATILITY DECREASE AFTER REVERSE STOCK SPLITS?

Previous research documents that volatility decreases after reverse stock splits. I show that measurement effects bias observed volatility, especially for lower priced stocks. Based on observed returns, volatility decreases 25% after reverse splits. Controlling for bid–ask bounce, volatility still decreases for stocks with prices above $5.00. However, for stocks below $2.00, volatility increases slightly. The portion of observed volatility attributable to measurement effects declines as the stock price increases and as the minimum tick size decreases. Finally, there is a significant and positive cross‐sectional relation between changes in the number of trades and changes in volatility after reverse splits.     

Modeling the bid/ask spread: measuring the inventory-holding premium

The need to understand and measure the determinants of market maker bid/ask spreads is crucial in evaluating the merits of competing market structures and the fairness of market maker rents. This study develops a simple, parsimonious model for the market maker's spread that accounts for the effects of price discreteness induced by minimum tick size, order-processing costs, inventory-holding costs, adverse selection, and competition. The inventory-holding and adverse selection cost components of spread are modeled as an option with a stochastic time to expiration. This inventory-holding premium embedded in the spread represents compensation for the price risk borne by the market maker while the security is held in inventory. The premium is partitioned in such a way that the inventory-holding and adverse selection cost components, as well as the probability of an informed trade, are identified. The model is tested empirically using Nasdaq stocks in three distinct minimum tick size regimes and is shown to perform well both in an absolute sense and relative to competing specifications.     

An Intraday Examination of the Components of the Bid–Ask Spread

Using transactions data for a sample of NYSE stocks, we decompose the bid–ask spread (BAS) into order–processing (OP) and asymmetric information (AI) components using the techniques of George, Kaul, and Nimalendran (1991) and Madhavan, Richardson, and Roomans (1997). McInish and Wood (1992) demonstrate that the intraday behavior of BASs can be explained by variables measuring activity, competition, risk, and information. We investigate whether these variables explain the behavior of the OP and AI components of the spread over the trading day. We conclude that, on balance, the variables that determine the aggregate BAS also determine its intraday components.     

The impact of tick size on intraday stock price behavior: evidence from the Taiwan Stock Exchange

This research examines the impact of tick size on intraday stock price behavior for stocks listed on the Taiwan Stock Exchange over the 2-year period of 1998–1999. The sample involves the same 80 firms that trade under the tick size of (New Taiwan Dollars) NT$0.1 and NT$0.5, respectively. The sample firms display a U-shaped intraday pattern of bid–ask spread, volatility, autocorrelation, and trading volume. The empirical results indicate that a larger tick size is associated with a wider bid–ask spread, larger volatility, and more negative autocorrelation. Moreover, a larger tick size is associated with a higher percentage increase of bid–ask spread and volatility in the middle of the trading period. Finally, the effect of tick size on trading volume is insignificant.     

Explaining the intra-day variation in the bid–ask spread in competitive dealership markets – A research note

There are many possible explanations for variation in the inside bid–ask spread during the trading day, including informed trading, price inelastic market demand, price discovery, statistical artefact and market concentration. Each of these explanations is examined for consistency with respect to both the inside and average bid–ask spread, observed both inside and outside the mandatory quote period in the London Stock Exchange.     

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.     

Microstructure and reverse stock splits

In this paper we show that, similar to NYSE/AMEX stocks, NASDAQ stocks exhibit significant ex date returns for reverse stock splits. Although the 10-day cumulative return after the ex date is close to –10%, this does not violate market efficiency, because the average bid-ask spread for the reverse split stock is at least double this return. We also document that these large negative returns are mostly due to a drop in the ask price while bid prices barely change at all. Furthermore, the ex date returns are negatively related to trading volume.These results suggest that there is abnormal selling and a significant buildup of market makers' inventories near the ex date. To reduce the inventory buildup, market makers lower ask prices to induce buying by investors, resulting in the observed negative returns. Lowering bid prices, an alternative strategy for reducing inventories, is not attractive to market makers due to competitive factors and the reduction of commissions associated with a smaller number of transactions. Notably, selling investors have no incentives to sell their stocks early to avoid the observed negative ex date return, since this return is largely an ask price phenomenon and does not represent realized returns to sellers.