In this paper, we use the high frequency trading data of New York Stock Exchange to analyze the bid-ask spread components. It is found that there is an exponential relationship between the log returns of quoted midpoints and the trade volume. We also observe a negative linear correlation between the changes of quoted depth and the trade volume. Furthermore, changes of the quoted ask depth and the quoted bid depth are asymmetric due to the trading direction. Furthermore, statistical quality control charts, p-charts, are built for fixed number of trades to monitor unusual trades entering the market. Finally, logistic regression models are established to predict the probabilities of unusual trades entering the market based on the quotes and the quoted depth adjustments of the market makers.

Previous studies (e.g. Benston and Hagerman, 1974, Bagehot, 1971 and Stoll, 1978) suggest that the bid-ask spread consists of three components: asymmetric information cost, inventory holding cost, and order processing cost. Other literature (e.g. Brock and Kleidon, 1992, Hef-lin et al, 2007, and McInish and Van Ness, 2002) reports that the bid-ask spread varies during a trading day following a U-shaped pattern. One explanation for this observation is that it is the result of changes in information asymmetry costs over the trading hours, assuming the other costs are fixed. However, no empirical study directly measures how information asym-metry changes over the trading day. We explore how this measure relates to the spread as well as the quote depth.<p> Our research divides a trading day into 13 half-hour trading intervals and measures in-formation asymmetry during each interval following the model developed by Madhavan and Smidt (1991) and Noronha et al (1996). Their model can directly estimate the level of infor-mation asymmetry in each interval. This enables us to observe the intraday pattern of infor-mation asymmetry directly and compare it to the patterns of the spread and the quote depth. Furthermore, we test the relationship between the spread and the information asymmetry and the relationship between the depth and the information asymmetry in a dynamic context to see how market makers manage information risk over trading hours.<p> We find that the risk of information asymmetry varies significantly during the trading day. There is a large drop over the first interval, and another large drop over the last interval, with smaller fluctuations over the remaining intervals. Moreover, we show that the spread is consistent with an L-shaped pattern as opposed to the U-shaped pattern proposed by previous studies while the depth is increasing throughout the 13 trading intervals. Furthermore, we ob-serve that the variations of the spread and the depth are respectively positively and negatively related to the intraday variations in the degree of information asymmetry across the trading intervals. In particular, a large decline in information asymmetry at the beginning of the day is associated with a large reduction in the spread, whereas a large decline in information asymmetry at the end of the day is associated with a large increase in the quote depth. This emphasises the importance of studying both measures of liquidity simultaneously.

Previous studies (e.g. Benston and Hagerman, 1974, Bagehot, 1971 and Stoll, 1978) suggest that the bid-ask spread consists of three components: asymmetric information cost, inventory holding cost, and order processing cost. Other literature (e.g. Brock and Kleidon, 1992, Hef-lin et al, 2007, and McInish and Van Ness, 2002) reports that the bid-ask spread varies during a trading day following a U-shaped pattern. One explanation for this observation is that it is the result of changes in information asymmetry costs over the trading hours, assuming the other costs are fixed. However, no empirical study directly measures how information asym-metry changes over the trading day. We explore how this measure relates to the spread as well as the quote depth.<p> Our research divides a trading day into 13 half-hour trading intervals and measures in-formation asymmetry during each interval following the model developed by Madhavan and Smidt (1991) and Noronha et al (1996). Their model can directly estimate the level of infor-mation asymmetry in each interval. This enables us to observe the intraday pattern of infor-mation asymmetry directly and compare it to the patterns of the spread and the quote depth. Furthermore, we test the relationship between the spread and the information asymmetry and the relationship between the depth and the information asymmetry in a dynamic context to see how market makers manage information risk over trading hours.<p> We find that the risk of information asymmetry varies significantly during the trading day. There is a large drop over the first interval, and another large drop over the last interval, with smaller fluctuations over the remaining intervals. Moreover, we show that the spread is consistent with an L-shaped pattern as opposed to the U-shaped pattern proposed by previous studies while the depth is increasing throughout the 13 trading intervals. Furthermore, we ob-serve that the variations of the spread and the depth are respectively positively and negatively related to the intraday variations in the degree of information asymmetry across the trading intervals. In particular, a large decline in information asymmetry at the beginning of the day is associated with a large reduction in the spread, whereas a large decline in information asymmetry at the end of the day is associated with a large increase in the quote depth. This emphasises the importance of studying both measures of liquidity simultaneously.

The bid-ask spread costs consist of three components, which include order processing costs, inventory-holding costs, and adverse selection costs. In this paper, we model the inventory-holding costs of the bid-ask spread by option hedging. Theinventory-holding costs are hedged by call or put option positions. Since trades deal with the adverse selection traders are unobservable. We treat it as a latent variable, and Expected-Maximization (EM) algorithm are applied to estimate the related parameters of the model. Simulation studies are performed for several different models. Empirical results of NYSE high frequency data show that the proposed model are obtain appropriate parameter estimation when the returns satisfied normality assumption.

Using the intraday data on the Taiwan Stock Exchange (TWSE), we address the issue of the informativeness of the limit order book in the periodic call market. We find that the pre-call information variables, i.e., the market order and the radius of the order book, have significant impacts on the trade variables, i.e., trading volume, the post-call bid-ask spread, and the trader surplus. Furthermore, we are able to show that the radius, as well as the market order, contains two differential forces in impacting these trade variables.

Univ., Diss.--Frankfurt, 2004.

Yes / We study liquidity on the London Stock Exchange. We find that the average bid-ask spread declines, but that the skewness of the spread increases. These results are robust to firm size, trading volume and price level. Our findings hold when the bid-ask spread is estimated utilising high frequency data. We find that the bid-ask spread prior to earnings announcements dates is significantly higher than that of post earnings announcements, suggesting that asymmetric information has driven the increase in liquidity skewness. We also find that the effect of earnings announcements is more pronounced in the 2007 global financial crisis, consistent with the notion that extreme market downturns amplify asymmetric information. Our overall evidence also implies that increased competition and transparent trading environments limit market makers' abilities to cross-subsidize bid-ask spreads between periods of high and low levels of asymmetric information. / National Natural Science Foundation of China (No. 71571197)

The purpose of this paper is to compare the liquidity and the components of the bid-ask spread for thinly traded firms switching from a dealer market (Emerging Stock Market (ESM)) to an order driven market (Taiwan Stock Exchanges (TSE) or GreTai Securities Market (GTSM)). Firstly, we follow Christie and Huang’s (1994) method to measure the liquidity performance. Our finding shows that thinly traded firms could improve their liquidity by switching from a dealer market to an order driven market. Secondly, we apply Huang and Stoll’s (1997) and Lin et al.’s (1995) model to estimate the bid-ask spread components. Our results show that the adverse selection cost is significantly smaller on ESM than TSE or GTSM using both Huang and Stoll’s (1997) and Lin et al.’s (1995) model. The inventory holding cost is lower on ESM than TSE or GTSM estimated by Huang and Stoll’s (1997) model. However, the estimates of order processing cost and the probability of trade reversal do not produce consistent results by applying Huang and Stoll’s (1997) and Lin et al.’s (1995) model.

This thesis aims to investigate the influence of earnings news on stock liquidity and the relationship between information asymmetry cost component and Post Earnings Announcement Drift in different equity markets. The scope of this research includes 1821 firms from three leading countries in capital trading, the United States, United Kingdom, and France. The first part of empirical work, the univariate panel analysis, shows that price reaction, volume response and liquidity effect are profound during short term event window length and reduce over time when the news ceases, The second part, a multivariate regression analysis which uses Generalised Method of Movement to capture both the problems of a likely presence of endogeneity between the explanatory variables and cross-stock heterogeneity,shows that the impact of earnings announcement on stock liquidity can split in two directions. The immediate effect is the shock after the news, causing stock liquidity to decrease immediately by lifting the illiquidity function upward. After the event, from the new increased position of illiquidity function, stock liquidity improves over time due to the trading volume increases and shifts the slope of illiquidity function downward. The overall effects at a point of time will be the total impact of the two side effects. And as shown in the results, the overall impact on the US and UK markets are that stock liquidity decreases and that on Euronext Paris the stock liquidity increases. Given that in accounting there are two types of systems of which common law system includes the US, UK and others, and code law system includes France and the rest, the above results could suggest the difference between the two systems is that the information asymmetry component dominates the bid-ask spread in common law countries as in the US and UK markets while the cost of trading dominates the bid-ask spreads in code law countries such as France. Finally, it is shown that there are several determinants of the PEAD, of which stock liquidity is one. Earnings news changes the stock liquidity, and therefore stock liquidity plays a role in the market response. When earnings news is released, it initially creates a gap between the informed traders and the uninformed traders, increasing the bid ask spread. Over time, this information gap decreases, however in the meantime more information on the market increases trading volume and reduces trading cost, leading to another part of the bid ask spread decreasing or stock liquidity improving. After decomposing bid ask spread into information asymmetry cost and cost of trading components, the final part of empirical analysis shows that information asymmetry cost component provides a partial explanation for PEAD in the London Stock Exchange and Euronext Paris.

The thesis studies aspects of the cost of equity trading in the emerging stock market of Ukraine. The market is quite new (opened in 1997 but started to operate actively only in 2004) and little research on this market has been done so far. The market appears to offer lucrative investment opportunities that attract attention of both Ukrainian and foreign investors but the cost of trading Ukrainian stocks is quite high and can considerably decrease the returns to investors. The empirical part of the thesis is based on the transactions data from the main trade floor in Ukraine, PFTS, for 59 Ukrainian stocks during 2004-2006. The cost of equity trading in Ukraine is found to be quite high compared to many other stock markets, both developed and emerging. An in-depth study has shown that the medium-sized trades are the cheapest to execute, followed by large and then small trades. The reason for the pattern is seen in the price improvement suggested by brokers to the larger, more valued customers in order to keep the business with them and is in line with the findings in other literature for dealership markets (Reiss and Werner (1996), Hansch et. al (1999), and Huang and Stoll (1996)). The average cost of institutional sale trades exceeds the average cost of institutional buy trades at any market condition (falling, neutral, or rising), which is a puzzling result given that sales are often found in the literature to be more expensive in falling market, while purchases are more expensive in rising market. The efficacy of a number of measures of liquidity is studied. In line with findings for other emerging markets, it is shown that the proportion of zero daily returns (Lesmond (1999)) and the proportion of no-trading days are the most reliable liquidity measures for the Ukrainian stock market. Turnover, a measure widely applied in literature for developed stock markets, has a very small power for measuring liquidity in Ukraine. The spread components are estimated by applying three spread decomposition models most frequently referred to in literature: Stoll (1989), Glosten and Harris (1988), and Huang and Stoll (1997). The estimation results show a low importance of the asymmetric information component, which is surprising given that insider trading is considered a serious risk in Ukraine. To present the importance of incorporating the transactions costs into portfolio return analysis, a momentum trading strategy is examined. It is shown that momentum portfolio returns decrease considerably when the cost of trading is taken into account.