LIQUIDITY OF AUCTION AND SPECIALIST MARKET STRUCTURES: EVIDENCE FROM THE BORSA ITALIANA

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1 LIQUIDITY OF AUCTION AND SPECIALIST MARKET STRUCTURES: EVIDENCE FROM THE BORSA ITALIANA ALEX FRINO a, DIONIGI GERACE b AND ANDREW LEPONE a, a Finance Discipline, Faculty of Economics and Business, University of Sydney, NSW, 2006, Australia. b School of Finance, Faculty of Commerce, University of Wollongong, NSW, 2522, Australia. Abstract Several studies find that bid-ask spreads for stocks listed on the NYSE are lower than for stocks listed on Nasdaq. While prima facie consistent with the proposition that specialist market structures such as the NYSE provide greater liquidity than competing dealer markets such as NASDAQ, the nature of trading on the NYSE, which comprises a specialist competing with a limit order book, 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 has monopoly control of order flow. Results confirm that bid-ask spreads tighten and quoted depth increases when stocks move to the specialist market. This reduction in bid-ask spreads and increase in quoted depth is robust to differences in market capitalization, industry affiliation and the event window around the structural change. This evidence is consistent with the proposition that specialists enhance the liquidity of markets. JEL Classification: G12, G14, G21 Keywords: Bid-ask spreads, liquidity. Corresponding Author. Finance Discipline, School of Business, University of Sydney, NSW, 2006, Australia. Tel: Fax: a.lepone@econ.usyd.edu.au.the authors would like to thank participants at the EFMA 2006 Madrid meetings, seminar participants at the University of Sydney and University of Wollongong Seminar series, as well as Achille Basile, Marco Pagano, Luke Bortoli, Teddy Oetomo and two anonymous referee s for useful comments.

2 1. Introduction Stock exchanges worldwide implement various methods for trading equity securities. Each exchange has a set of rules which dictate how orders are submitted, who handles and processes these orders, and ultimately how prices are set (O Hara, 1995). The organisation of trading directly affects the provision of liquidity to market participants. Individual and institutional investors both prefer liquid markets that offer low trading costs, and which can absorb large orders without severe price penalties. The provision of liquidity has attracted considerable attention from both academics and market regulators. In particular, a large number of studies have compared specialist markets (such as the NYSE) with other market structures (such as the dealer structure of Nasdaq) to determine which facilitates the greatest liquidity: an important practical issue. This paper investigates the change in liquidity associated with a shift from an auction market to a specialist market on the Borsa Italiana. Almost all research comparing the liquidity of specialist and non-specialist markets is US based. The overwhelming majority of studies find that a specialist market results in lower costs of trading compared to a dealer market. Affleck-Graves, Hedge and Miller (1994), Huang and Stoll (1996) and Bessembinder and Kaufman (1997) compare the magnitude of bid-ask spread components for NYSE / AMEX stocks to Nasdaq stocks. They show that execution costs are lower for NYSE / AMEX listed companies, regardless of capitalization. They also find that adverse selection is not causing the wider bid-ask spreads on Nasdaq. 1 Christie and Huang (1994) and Barclay (1997) examine if structurally induced changes in trading costs occur when firms relocate from a dealer market to a specialist 1 Neal (1992) compares the bid-ask spread for options on AMEX, which operate a specialist structure and the Chicago Board of Exchange (CBOE), which operate a competitive market maker structure. He finds that when trading volume is low, the specialist structure provides more liquidity, although the benefit decreases when trading volume increases. 2

3 market. Their results confirm that the move away from Nasdaq leads to a significant reduction in bid-ask spreads. 2 Amidst these studies finding lower costs on the NYSE (and AMEX), several studies find that execution costs are lower on Nasdaq. Dubofsky and Groth (1984) and Cooper, Groth and Avera (1985) find that the highest liquidity exists for Nasdaq stocks. Chan and Lakonishok (1997) show that the cost of trading in small firms is lower on Nasdaq, while the NYSE provides better execution for larger firms. While these studies are comparing liquidity across exchanges, the exact nature of the comparison is unclear. Nasdaq is a competitive dealer market, employing several market makers for each security. The NYSE, however, is ambiguous. Brock and Kleidon (1992) describe specialists on the NYSE as monopolistic market makers. Huang and Stoll (1996) describe the NYSE as an auction market that employs a specialist for each security. Affleck-Graves, Hedge and Miller (1994, p1473) describe the specialist as enjoying an exclusive franchise to make a market in a listed stock and to manage the book of public limit orders. The adoption of a limit order book to provide additional liquidity is considered as competition to the specialist (Glosten, 1994). Overall, the exact nature of trading on the NYSE cannot be classified as a single, definitive market structure. Demsetz (1997) argues that the limit order book alongside the specialist makes comparisons using the NYSE difficult. In particular, customer limit orders can obscure the link between observed bid-ask spreads and the costs of market making. Bid and ask quotes could reflect supply and demand conditions of investors rather than the inventory, order processing and adverse selection components of professional market makers. This is confirmed by Kavajecz (1999) who finds that public limit 2 Nimalendran and Petrella (2003) find that specialist intervention improves liquidity for the most illiquid stocks on the Italian Stock Exchange. 3

4 orders are represented in about 64 percent of NYSE specialists quotes, and Ross, Shapiro and Smith (1996) who report that limit orders account for 65 percent of all executed orders. This, as Demsetz clearly states, must yield an average NYSE bid-ask spread that, for similar stocks, is smaller than on the Nasdaq (1997, p92). Thus comparing bid-ask spreads on the NYSE and Nasdaq can be misleading as bidask spreads on the NYSE do not accurately represent the costs of making a market. This hybrid nature of trading on the NYSE makes comparing liquidity across dealer and specialist markets ambiguous. In this paper, we have access to a dataset that allows an accurate comparison between two market structures. On April 2, 2001, a specialist segment was introduced on the Italian Bourse. Stocks that originally traded in an auction market commenced trading in a specialist market. This specialist, rather than competing with the limit order book, receives all orders and decides whether to execute these against his / her own inventory, or to post them in a limit order book which he / she controls. In addition to this clean experimental design, we directly test for the advantages of a specialist market over an auction market. Madhavan and Smidt (1993) show that quote revisions are related to order imbalances. The increased volume at the close of trading leads to greater order imbalances, and thus higher expected specialist bid-ask spreads. Brock and Kleidon (1992) consider specialists as monopolistic market makers. As fund managers and institutional investors concentrate the majority of their trading at the close, the specialist can discriminate during these periods and widen bid-ask spreads. Pagano and Roell (1996) argue that the transparency of the market is important, with an auction market more transparent than a specialist market in that more information can be made available to all participants. In particular, 4

5 market participants are able to see what price incoming orders can be executed at, leading to reduced risk and thus tighter bid-ask spreads. However, an empirical analysis by Chung, Van Ness and Van Ness (1999) shows that, after separating quotes that reflect the trading interest of the specialist from quotes that reflect the trading interest of limit order traders, quotes driven by specialists are tighter in the final 30 minutes of trading on the NYSE. The authors argue that this is primarily driven by inventory management by specialists. Based on this conflicting evidence, we hypothesize that the bid-ask spread (and quoted depth) will change when stocks commence trading in the Star specialist market. Our results indicate that there is a significant reduction in bid-ask spreads and an increase in quoted depth when stocks move to a specialist market. After controlling for changes in price, volume and volatility, the reduction in bid-ask spreads and increase in quoted depth remains. Over the transition period, the control market segment shows minimal variation, indicating that reduced bid-ask spreads and increased quoted depth are directly attributable to changes in market structure. Our results also indicate that the liquidity benefits are robust to market capitalization and industry affiliation, as well as the time period around the structural change. Finally, by allowing price improvement within quotes, the specialist is further reducing the cost of trading. The remainder of this paper is structured as follows. The following section describes the institutional details of the Italian Bourse. Section 3 describes the data and empirical results, while Section 4 provides several additional tests. Section 5 summarizes the paper. 5

6 2. Institutional detail The Italian Bourse operates a segmented market structure. Prior to 1991, all trading took place by means of an open outcry auction system on ten regional stock exchanges. Since April 1994, all trading has been centralized through an electronic auction market. The market is supported by a network linking all authorized securities firms throughout Italy and abroad (Handbook of World Stock Exchanges, 2001). It enables trading in real time of all securities, independently of physical location. With this system, liquid equity securities trade continuously over an entire trading day, while a parallel system for less liquid securities trade continuously for approximately half the trading day. On April 2, 2001, the two categories of shares (liquid and less liquid) were replaced by three new segments, primarily based on market capitalization. Financial instruments above a pre-defined level set by the Exchange were classified as Blue- Chip. Trading for these securities continues as for the auction market described. For financial instruments below the level, the issuer decided to be included in one of two market segments. The first is the ordinary segment of the market, known as SBO. Trading in this segment continues as for the auction market described. Alternatively, the issuer could be included in the Star segment. 3 The Star segment differs in that each security is assigned a specialist to control trading. All orders originally sent to the electronic order book are now channeled to the specialist. Rather than competing with the limit order book (like NYSE specialists), the Star specialist controls the limit order book. Thus the specialist can execute the order against his / her own inventory. Alternatively, the specialist can post the order in the electronic order book visible to other participants. 3 All three segments trade continuously over the entire trading day. 6

7 Additional to these three primary segments, the Italian Bourse also has the Nuovo Mercato (herein New Market), a market designed to handle high-growth companies. Trading in the New Market commenced in June Companies in this segment are also appointed a specialist to sustain liquidity. These specialists must expose all orders until a minimum daily quantity is transacted. However, the specialist has monopolistic powers for institutional block orders, where he / she can hold the order for five minutes before deciding to either transact the order, or post it in the electronic limit order book (Handbook of World Stock Exchanges, 2001). 3. Data and empirical results To test the effect of moving from an auction market to a specialist market, we identify firms that were listed on the original market structure (liquid and less liquid securities), and moved to one of the three new segments (Blue Chip, SBO or Star). To control for major differences in liquidity and market characteristics, both illiquid and foreign listed companies are excluded from the sample. 4 From the remaining stocks, we select all stocks that could have moved to the Star specialist market on April 2, This leaves a total of 71 stocks. Of these 71 stocks, 57 continued trading in the ordinary auction market (SBO market), while 14 commenced trading in the new Star market. We also include stocks that trade in the MIB30 (Blue Chip stocks) as a further control. For these stocks, daily closing bid, ask and transaction prices, both one year before and after the April 2, 2001 structural change are collected. Also collected are 4 On April 2, 2001, less liquid securities commenced trading in a call auction market comprising of two separate calls per trading day. These illiquid stocks do not trade in a continuous market, so are fundamentally different (in addition to their significantly lower liquidity) to the Star, SBO and Blue Chip stocks included in the analysis. 5 The robustness of this event-window is tested later in the paper. 7

8 daily high and low prices and daily volume for each stock. Market capitalization of all 101 firms is also available. The data is sourced from a Bloomberg database. To examine the impact on liquidity of the change from an auction market to a specialist market, three measures are examined. 6 The first is the quoted bid-ask spread (in ), defined as 7 Quoted Spread = Ask Bid To control for stock price variations, both over time and across stocks, we also examine the proportional quoted bid-ask spread, defined as Proportional Spread = (Ask Bid) / [(Ask + Bid) / 2] As suggested by Harris (2004), quoted depth is an essential component of liquidity. The third measure examined is the average quoted depth at the best bid and ask quotes, defined as Quoted Depth = (Best Ask Depth + Best Bid Depth) / Univariate results Table 1 provides descriptive statistics for the bid-ask spread and quoted depth measures, as well as other stock characteristics, for stocks that moved from the auction market to the Star market, for stocks remaining in the auction (SBO) market and for the MIB30 Blue Chip stocks. Statistics are calculated using data from six months prior to and after the structural change. For the 14 stocks that switched to the specialist Star market, the quoted bidask spread falls from to 0.031, a significant reduction of After 6 Prior literature also examines the effective bid-ask spread, which takes into account trading within the bid and ask quotes. As the pre-period in our experiment utilized only an auction market, no trading occurred within the best quotes. Thus, the effective bid-ask spread is equal to the quoted bid-ask spread. However, for stocks that moved to the Star market, trading inside the bid-ask spread can be facilitated by the specialist. To examine this possibility, an additional test comparing the quoted and effective bid-ask spreads for the Star stocks after the structural change is reported later in the paper. 7 The minimum tick for stocks included in the sample is

9 adjusting for the stock price, the proportional bid-ask spread falls from percent to percent, a significant reduction of percent. The quoted depth at the best quotes over the same period fell from 9,203 to 7,336, a significant decrease of 1,867 shares. Over the same period, stocks which remained under the ordinary SBO auction system show a reduction in quoted bid-ask spread of However, the proportional bid-ask spread increased by the significant amount of percent. Proportional bid-ask spreads for Blue Chip stocks fell by the insignificant amount of percent. Overall, univariate results indicate a reduction in bid-ask spreads and quoted depth when stocks move from an auction market to a specialist market. 8 This reduction is also evident in Figure 1. The reduction in proportional bid-ask spreads occurs on the day of the structural change (day zero) for Star stocks, after which a new equilibrium bid-ask spread level is attained (the bid-ask spread for SBO stocks remains unchanged). <INSERT TABLE 1> <INSERT FIGURE 1> Table 1 also presents descriptive statistics for several stock characteristics. Closing prices for stocks that switched to the Star market have fallen. Prior to the move, the average closing price is 4.17, whilst after the move the average falls to The average daily volume also falls by 98,855 shares. Given the reduction in stock price and volume, euro volume falls, from an average of 518,569 in the six months prior, to an average of 309,201 in the six months after the switch. However, stock price volatility is significantly reduced under the specialist system, with a significant reduction of 0.48 percent. 9 8 Differences of median values around the structural change are also tested using the non-parametric Wilcoxon Signed Rank test. Results of this, which are reported in Table 1, are consistent with t-statistic results. 9 Volatility is calculated as the natural log difference between high and low prices on the trading day. 9

10 Over the same period, stocks remaining in the auction market (SBO stocks) and Blue Chip market also exhibit variation. The average SBO (Blue Chip) stock price falls from 3.92 to 3.45 ( to 9.91), whilst average volume falls from 150,203 to 102,370 to (6,698,734 to 6,112,987). Together, this leads to a significant reduction in euro volume of 143,716 ( 7,535,331), similar to the Star market. However, the volatility of the SBO and Blue Chip stocks is higher after the structural change. Overall, trading activity for Star, SBO and Blue Chip stocks falls after the switch, although the reduction in bid-ask spreads is localized to Star stocks Regression results Univariate results indicate a significant reduction in bid-ask spreads and decrease in quoted depth when stocks move to a specialist market. Other stock factors, including volume and volatility also vary with the switch for Star, SBO and Blue Chip markets. Changes in these other factors could be driving the reduction in bid-ask spreads. To control for the impact that these additional factors have on bid-ask spreads and quoted depth, several regressions are estimated using pooled (crosssectional and time-series) data. The first three control for variation (both over time and across stocks) in the bid-ask spreads and quoted depth of stocks that remain in the auction market segment. 11 Specifically, the following three regressions are estimated, Star_QS t = β 0 + β 1 Change t + β 2 SBO_QS t + ε t (1) Star_PS t = β 0 + β 1 Change t + β 2 SBO_PS t + ε t, (2) Star_QD t = β 0 + β 1 Change t + β 2 SBO_QD t + ε t, (3) 10 We also calculated Amihud s (2002) Illiquidity Measure for the Star and SBO stocks before and after the April 2, 2001 structural change. Results from this confirm that liquidity for Star stocks improved after the change, while there is a decrease in liquidity for SBO stocks. Results from this test are available upon request. 11 The use of the SBO_QS variable is consistent with Chordia, Roll and Subrahmanyam (2000) and captures market-wide factors that affect bid-ask spreads. 10

11 where Change t is a dummy variable that takes the value of one after the structural change, zero otherwise. Star_QS t is the quoted bid-ask spread (in euros), Star_PS t is the proportional quoted bid-ask spread and Star_QD t is the average quoted depth at the best bid and ask quotes for stocks that moved to the specialist Star market. SBO_QS t (BC_QS t ) is the quoted bid-ask spread (in euros), SBO_PS t (BC_PS t ) is the proportional quoted bid-ask spread, and SBO_QD t (BC_QD t ) is the average quoted depth at the best bid and ask quotes for SBO (Blue Chip) auction market stocks. As the bid-ask spread and quoted depth are dependant on several factors including volume and volatility, and both have shown variation after the structural change, we also control for these factors. The next three regressions examine the change in bid-ask spreads and quoted depth for Star stocks after controlling for changes in euro volume and volatility in the Star, SBO and Blue Chip markets. Specifically, the following three regressions are estimated, Star_QS t = β 0 + β 1 Change t + β 2 ln(sbo_volume t ) + β 3 SBO_Vol t + β 4 ln(star_volume t ) + β 5 Star_Vol t + β 6 [Change t x ln(star_volume t )] + β 7 [Change t x Star_Vol t ] + ε t (4) Star_PS t = β 0 + β 1 Change t + β 2 ln(sbo_volume) + β 3 SBO_Vol t + β 4 ln(star_volume) + β 5 Star_Vol t + β 6 [Change t x ln(star_volume t )] + β 7 [Change t x Star_Vol t ] + ε t (5) Star_QD t = β 0 + β 1 Change t + β 2 ln(sbo_volume) + β 3 SBO_Vol t + β 4 ln(star_volume) + β 5 Star_Vol t + β 6 [Change t x ln(star_volume t )] + β 7 [Change t x Star_Vol t ] + ε t (6) where ln(star_volume) is calculated as the natural logarithm of daily euro volume for SBO stocks and Star_Vol t is the daily volatility, calculated as the natural logarithm of the daily high price / low price for Star stocks. Both ln(sbo_volume) and SBO_Vol t 11

12 and ln(bc_volume) and BC_Vol t are calculated similarly for SBO and Blue Chip stocks, respectively. Change t is again a dummy variable that takes the value of one after the structural change, zero otherwise. 12 All variables are calculated using data from six months prior to and after the structural change. Table 2 presents coefficient estimates and adjusted R-squared values for all regressions. Panel A presents results with SBO explanatory variables, while Panel B presents results with Blue Chip explanatory variables. The first two regressions indicate that after controlling for variation in SBO (Blue Chip) bid-ask spreads (which have a positive effect on Star bid-ask spreads), both the quoted and proportional bidask spreads are reduced after the structural change. Both dummy variables have negative coefficients which are significant at all conventional levels. The third regression indicates that after controlling for variation in SBO (Blue Chip) quoted depth, Star quoted depth is lower after the structural change (dummy variable has a significantly negative coefficient). The next three regressions, after controlling for euro volume and volatility in the Star and SBO (Blue Chip) markets, indicate that both the quoted and proportional bid-ask spreads decline, and the quoted depth increases, after the structural change. The coefficients for the dummy variables are significantly negative for the bid-ask spread regressions and positive for the quoted depth regression. Coefficient estimates for the explanatory variables are as expected. The coefficients on all interaction terms are insignificantly different from zero, indicating that the change to a specialist market is not driving the change in volume and volatility for Star stocks. Overall, after controlling for bid-ask spreads and quoted depth in the SBO and Blue Chip markets, and other factors affecting bid-ask spreads and quoted depth in the Star, SBO and 12 Dependant variables are as described for the first two regressions. 12

13 Blue Chip markets, both quoted and proportional bid-ask spreads are significantly tighter, and quoted depth greater, under a specialist rather than auction market structure. 13 These findings are consistent with Chung et al. (1999) who show that bidask spreads are tighter in the final 30 minutes of trading on the NYSE. <INSERT TABLE 2> 4. Additional Tests This section provides several additional tests to examine the robustness of the reduction in bid-ask spreads and increase in quoted depth for the specialist market stocks. 4.1 Effect of firm size and industry affiliation Much of the literature has suggested that although specialist markets provide lower bid-ask spreads than dealer markets, the benefit from shifting to a specialist market is greater for smaller firms. As the Italian Bourse already has a segment for large firms in excess of 800 million, known as Blue Chip, which have been examined in the paper, the stocks remaining in the SBO and Star markets are medium to small capitalization stocks. To examine the impact of firm size, we divide the samples of SBO and Star stocks into two groups. As the average market capitalization of both the Star and SBO samples is approximately 300 million, all stocks with market capitalizations greater than 300 million are considered medium capitalization stocks, while all stocks less than 300 million in capitalization are considered small capitalization stocks. Analysis around the structural change is then completed separately for small and medium capitalization stocks. The results are presented in 13 Results from Dickie-Fuller tests, which are available upon request, indicate that all time-series variables are stationary. 13

14 Table 3 (market capitalization details), Table 4 (small capitalization stocks) and Table 5 (medium capitalization stocks). Descriptive market capitalization statistics are presented in Table 3 for all stocks, small capitalization stocks and medium capitalization stocks. The average market capitalization of small stocks is million for Star stocks and million for SBO stocks. The medium capitalization stocks have an average of million for Star stocks and million for SBO stocks. The median results also indicate that within the small and medium groups, there is minimal difference between the market capitalization of Star and SBO stocks. There is minimal difference in the size of firms that moved to the specialist market or remained in the auction market. <INSERT TABLE 3> Descriptive bid-ask spread, quoted depth and stock statistics are presented in Panel A of both Table 4 and Table 5. The reduction in bid-ask spreads for small capitalization stocks averages (proportional bid-ask spread falls by percent), while the reduction averages ( percent in proportional bid-ask spreads) for medium capitalization stocks. falls by 677 shares for small capitalization stocks and 4,988 shares for medium capitalization stocks. Regression results, in Panel B of both tables, are also consistent. All dummy variables are significantly negative across all bid-ask spread regressions (except for the first regression with small capitalization stocks), and positive for the quoted depth regression that controls for changes in trading activity and volatility. The reduction in bid-ask spreads and increase in quoted depth occurs for both small and medium capitalization stocks. <INSERT TABLE 4> 14

15 <INSERT TABLE 5> Extending the role of firm size, a large firm in a particular industry sector may be considered a small firm in another industry sector. To examine if the market capitalization of a firm within a particular industry sector affects bid-ask spreads and quoted depth, we perform a matching procedure. For each Star stock, we find all SBO stocks in the same industry sector. From all possible matches, we select the SBO stock with a market capitalization closest to the capitalization of the Star stock. We do this for all 14 Star stocks. The regression results are presented in Table 6. The results in Table 6 are consistent with the full sample results. After controlling for bid-ask spread and quoted depth changes in the matched SBO stocks, bid-ask spreads are significantly tighter and quoted depth is significantly lower, with dummy variable coefficients significantly negative. The last three regressions, after controlling for euro volume and volatility of both the SBO and Star matched stocks, indicates a decline in bid-ask spreads and an increase in quoted depth. The reduction in bid-ask spreads and increase in quoted depth when stocks move from an auction market to a specialist market is thus robust to both the size and industry affiliation of the firm. <INSERT TABLE 6> 4.2 Length of event window Over time, a stock s characteristics vary. Thus, the event window in which variables are measured is important. To examine the robustness of results to the length of the event window, we calculate all variables for both three and 12 months before 15

16 and after the structural change. We then re-estimate all regressions separately for the three-month and 12-month event windows. The results are presented in Table The three-month results are presented in Panel A. Consistent with earlier findings, all bid-ask spread regressions have negative coefficients for the dummy variable, while all quoted depth regressions have positive coefficients for the dummy variable. The 12-month results are presented in Panel B. As with the three-month results, all dummy variable coefficients are negative (positive) for the bid-ask spread (quoted depth) regressions, indicating a reduction in bid-ask spreads and an increase in quoted depth around the structural change. All explanatory variable coefficients are in their proposed directions. We conclude that our finding of a reduction in bid-ask spreads and an increase in quoted depth when stocks switch to a specialist market is robust to the length of the event window. 4.3 Control with the New Market <INSERT TABLE 7> It is possible that market wide events are narrowing bid-ask spreads and increasing quoted depth. Over the transition period, trading in the New Market continued normally. Although New Market stocks are generally high-growth, highvolatility stocks, if bid-ask spreads, quoted depth and other stock characteristics exhibit systematic changes over the same event window, overall market forces could be driving the change in liquidity for Star stocks. To examine this possibility, we analyze a sample of 13 stocks trading on the New Market over the same time period. The results are presented in Table 8. Descriptive statistics are presented in Panel A of Table 8. Quoted bid-ask spreads increase over the period by After adjusting for the stock price, results 14 For space considerations, we only include regression results. Descriptive statistics similar to those presented earlier in the paper are calculated, and are consistent with our initial results. These results are available upon request. 16

17 indicate an increase in proportional bid-ask spreads of percent. is significantly higher after the structural change, although euro volume is significantly lower after the change. The regressions used previously are estimated with New Market variables replacing SBO variables. The results, presented in Panel B of Table 8, indicate that bid-ask spreads decline, and quoted depth increases for Star stocks after they commence trading in the specialist market. Unlike with the SBO and Blue Chip variables, the New Market euro volume and volatility variables have coefficients insignificantly different from zero for the final two regressions. We thus confidently conclude that factors affecting the market overall are not driving the reduction in bidask spreads and increase in quoted depth for Star stocks. 15 <INSERT TABLE 8> 4.4 The role of effective bid-ask spreads Much of the previous literature calculates effective bid-ask spreads. Effective bid-ask spreads capture the actual cost of executing trades when some transactions occur inside the best bid and ask quotes. Prior to the structural change, all trading took place on an electronic auction market. Thus, no transactions occurred within the best quotes, and the effective bid-ask spread equals the quoted bid-ask spread. Before and after comparisons of the effective bid-ask spread are meaningless. However, results indicate that quoted bid-ask spreads (both euro and proportional) are reduced when stocks move to the specialist market. If the specialist allows trades to occur inside the bid-ask spread, the effective bid-ask spread will be lower than the quoted bid-ask 15 We also test the impact of the New Market over three and 12 month periods around the structural change. With the three month period, 18 stocks are included, whilst there are only six stocks for the 12 month period. Under both alternatives, results are qualitatively similar. There is strong evidence that the quoted and proportional bid-ask spreads decline, and that quoted depth increases, when stocks commence trading in the specialist Star market. These results are available upon request. 17

18 spread after the structural change, providing further evidence of the benefits of a specialist market structure. To examine this issue, we calculate the effective quoted half bid-ask spread as [Transaction Price (Ask + Bid) / 2], and compare this to the quoted half bid-ask spread, calculated as (Ask Bid) / 2 for the 14 Star stocks in the six months after the structural change. We also calculate the effective percentage half bid-ask spread as [Transaction Price (Ask + Bid) / 2] / (Ask + Bid) / 2, and compare this to the proportional quoted half bid-ask spread calculated as [(Ask Bid) / 2] / (Ask + Bid) / 2, again for the 14 Star stocks. The results are presented in Table 9. The comparison of the quoted half bid-ask spread with the effective half bidask spread indicates that effective bid-ask spreads are lower than quoted bid-ask spreads. The half bid-ask spread averages 0.024, while the effective bid-ask spread averages The difference of is significantly different from zero. Percentage bid-ask spread results are consistent. The difference between proportional and effective bid-ask spreads of percent is significantly different from zero. 16 The specialist s ability to offer price improvement over the best quotes provides an even lower cost of trading than was attainable in the auction market. 17 <INSERT TABLE 9> 5. Summary Several studies compare the differences in bid-ask spreads for stocks listed on the NYSE and Nasdaq. The majority of these studies show that the cost of executing trades is lower on the NYSE. However, the nature of trading on the NYSE is 16 Median changes are also significantly different from zero. 17 We also compare effective and quoted bid-ask spreads using three and 12 month event windows after the structural change. The results from this are consistent with the six month results, and are available upon request. 18

19 ambiguous, sometimes referred to as an auction market and other times a specialist market. The existence of a limit order book competing with the specialist further complicates the comparison of bid-ask spreads with other market structures. On April 2, 2001, a structural change was implemented on the Italian Bourse. Many stocks that traded in an auction market switched to a specialist market (Star), while other stocks remained in an auction market (SBO). As the Star specialist controls, rather than competes with the limit order book, we have a natural experiment where the impact of a specialist s involvement on the bid-ask spread and quoted depth can be ascertained. Results indicate that bid-ask spreads tighten and quoted depth increases when stocks move from an auction market to a specialist market. After controlling for bidask spreads, quoted depth, euro volume and volatility in the Star, SBO and Blue Chip markets, both quoted and proportional bid-ask spreads exhibit considerable reductions after the structural change, while quoted depth is significantly higher. This reduction in bid-ask spreads and increase in quoted depth is robust to the market capitalization of the stock, the firms industry affiliation and the event window around the structural change. Using the New Market to control for market wide factors, we confirm the reduction in bid-ask spreads and increase in quoted depth for Star stocks. The specialist, in allowing price improvement within the best quotes, is further reducing the cost of executing trades. We conclude that bid-ask spreads are tighter and quoted depth is greater with a specialist. Compared to an auction market, a specialist market proves more advantageous to market participants. 19

20 References Affleck-Graves, J., Hedge, S.P., Miller, R.E., Trading mechanisms and the components of the bid-ask spread. Journal of Finance 44, Amihud, Y., Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets 5, Barclay, M.J., Bid-ask spreads and the avoidance of odd-eighth quotes on Nasdaq: An examination of exchange listings. Journal of Financial Economics 45, Bessembinder, H., Kaufman, H.M., A comparison of trade execution costs for NYSE and Nasdaq-listed stocks. Journal of Financial and Quantitative Analysis 32, Brock, W.A., Kleidon, A.W., Periodic market closure and trading volume: A model of intraday bids and asks. Journal of Economic Dynamics and Control 16, Chan, L., Lakonishok, J., Institutional equity trading costs: NYSE versus Nasdaq. Journal of Finance 52, Chordia, T., Roll, R., Subrahmanyam, A., Commonality in liquidity. Journal of Financial Economics 56, Christie, W.G., Huang, R.D., Market structures and liquidity: A transactions data study of exchange listings. Journal of Financial Intermediation 3, Chung, K.H., Van Ness, B.F., Van Ness, R.A., Limit orders and the bid-ask spread. Journal of Financial Economics 53, Cooper, S.K., Groth, J.C., Avera, W.E., Liquidity, exchange listing and common stock performance. Journal of Economics and Business 17, Demsetz, H., Limit orders and the alleged Nasdaq collusion. Journal of Financial Economics 45, Dubosky, D.A., Groth, J.C., Exchange listing and stock liquidity. Journal of Financial Research 7, Glosten, L.R., Is the electronic open limit order book inevitable? Journal of Finance 44, Harris, L.E., Minimum price variations, discrete bid-ask spreads, and quotation sizes. Review of Financial Studies 7,

21 Huang, R.D., Stoll, H.R., Dealer versus auction markets: A paired comparison of execution costs on NASDAQ and the NYSE. Journal of Financial Economics 41, Kavajecz, K.A., A specialist s quoted depth and the limit order book. Journal of Finance 54, Madhavan, A., Smidt, S., An analysis of changes in specialist inventories and quotations. Journal of Finance 48, Neal, R., A comparison of transaction costs between competitive market maker and specialist market structures. Journal of Business 65, Nimalendran, M., and Petrella, G., Do thinly-traded stocks benefit from specialist intervention? Journal of Banking and Finance 27, O Hara, M., Market microstructure theory. Blackwell Publishers, Cambridge. Pagano, M., Roell, A., Transparency and liquidity: A comparison of auction and dealer markets with informed trading. Journal of Finance 51, Ross, K., Shapiro, J., Smith, K., Price improvement of SuperDot market orders on the NYSE. Working Paper 96-02, New York Stock Exchange. The Compaq Handbook of World Stock, Derivative and Commodity Exchanges, 2001, Mondo Visione. 21

22 Table 1 Descriptive statistics This table reports descriptive statistics (number of stocks, quoted and proportional bid-ask spread, quoted depth, closing price, daily volume, daily euro volume and daily volatility) for the 14 Star, 57 SBO and 30 MIB30 Blue Chip stocks. Volatility is calculated as the natural logarithm of the ratio of daily high to low stock prices. For each variable, the table reports the mean, median, change in mean and change in median for the six months before and after the structural change. A t-test is used to examine the change in mean, while the Wilcoxon Signed Rank test is used to examine the change in median. Star market SBO market Blue Chip market Before After Before After Before After Number of stocks Quoted spread ( ) Mean Median Mean change ** ** Median change ** ** Proportional spread (%) Mean Median Mean change ** * Median change ** * Mean 9,203 7,336 11,769 8,538 34,605 26,649 Median 8,721 6,831 11,626 8,461 33,861 27,702 Mean change -1,867** -3,231** -7,956** Median change -1,890** -3,165** -6,159**

23 Table 1, continued Closing price ( ) Mean Median Mean change -0.72** -0.47* -1.12** Median change -0.60* -0.59* -1.67** Daily volume (shares) Mean 203, , , ,370 6,698,734 6,112,987 Median 172,120 93, ,221 90,234 6,545,322 5,415,786 Mean change -98,855* -47,833** -585,747** Median change -79,016* -42,987** -1,129,536** Daily volume ( ) Mean 518, , , ,155 40,372,988 32,837,657 Median 426, , , ,434 40,902,355 31,699,221 Mean change -209,368** -143,716** -7,535,331** Median change -165,908** -88,991** -9,203,134** Daily volatility (%) Mean Median Mean change -0.48* 0.67* 0.11* Median change -0.50** * ** Indicates statistical significance at the 0.01 level * Indicates statistical significance at the 0.05 level 23

24 Table 2 Multiple regression results This table reports results from the six regressions for the 14 stocks that moved from an auction market to the specialist Star market on April 2, The dependant variable is measured as (i) the quoted euro bid-ask spread in the first and fourth regressions; (ii) the proportional quoted bid-ask spread in the second and fifth regressions; and (iii) the average quoted depth at the best bid and ask quotes in the third and sixth regressions. The change dummy variable takes the value of one after the structural change, zero otherwise. The SBO (BC) variable is the quoted euro bid-ask spread for the first regression, the proportional quoted bid-ask spread for the second regression and the average quoted depth at the best bid and ask quotes for the third regression. The final three regressions include the natural logarithm of the euro volume, as well as the percentage volatility, measured as the log difference between high and low prices on the trading day. Panel A presents results for regressions estimated using SBO control variables, while Panel B presents results for regressions estimated using Blue Chip control variables. All variables are calculated using data from six months prior to and after the structural change. For each regression, coefficient estimates (t-statistics), adjusted R-squared values and the Durbin-Watson statistic are reported. Intercept Change SBO (BC) spread / depth SBO (BC) volume ln( ) SBO (BC) volatility (%) Star volume ln( ) Star volatility (%) (Star volume) * Change (Star volatility) * Change Adj. R 2 (DW) Panel A: SBO control variables Quoted spread ( ) Prop. spread (%) Quoted spread ( ) Prop. spread (%) (5.34) (11.78) (14.81) (4.75) (4.63) (7.73) (-6.81) (-11.96) (-2.75) (-1.94) (-3.07) (0.72) (6.67) (11.64) (1.40) (-0.88) (-1.26) (0.15) (1.77) (3.06) (-1.45) (-3.57) (-3.11) (5.05) (3.69) (6.52) (-3.08) (1.64) (1.29) (-1.63) (-0.70) (0.24) (-0.24) (1.722) (1.715) (1.653) (1.878) (1.855) (1.924) 24

25 Table 2, continued Panel B: Blue Chip control variables Quoted spread ( ) Prop. spread (%) Quoted spread ( ) Prop. spread (%) (5.78) (4.19) (1.43) (3.96) (4.12) (10.16) (-6.08) (-9.46) (1.64) (-1.94) (-2.21) (0.93) (6.57) (8.86) (6.85) (-1.98) (-1.71) (-3.54) (4.06) (4.88) (-1.45) (-3.34) (-3.67) (8.09) (4.32) (7.87) (-3.17) (1.62) (0.32) (-0.55) (-1.64) (0.55) (-1.74) (1.783) (1.562) (1.844) (1.642) (1.685) (1.963) 25

26 Table 3 Market capitalization This table reports descriptive market capitalization statistics for the 14 stocks that moved from an auction market to the Star specialist market on April 2, 2001, and the 57 stocks which remained in the ordinary SBO auction market. Stocks with market capitalizations below the overall mean are moved into the small stock segment, while stocks with market capitalizations above the overall mean are moved into the medium stock segment. For each Star and SBO sample, the table reports the mean, minimum, median and maximum value, calculated on the trading day prior to the structural change. All amounts shown are in millions of euros. All stocks (14 Star, 57 SBO) Small stocks (8 Star, 41 SBO) Medium stocks (6 Star, 16 SBO) Mean Minimum Median Maximum Star SBO Star SBO Star SBO

27 Table 4 Small stock segment This table reports descriptive statistics, including quoted and proportional bid-ask spread, quoted depth, euro volume and volatility (Panel A) and regression results (Panel B) for small Star and SBO stocks, as classified in Table 3. For each variable, the table reports the mean and median (in parentheses) for the six months before and after the structural change, and the change in mean (median) values. In the regressions, the dependant variable is measured as (i) the quoted euro bid-ask spread in the first and fourth regressions; (ii) the proportional quoted bid-ask spread in the second and fifth regressions; and (iii) the average quoted depth at the best bid and ask quotes in the third and sixth regressions. The change dummy variable takes the value of one after the structural change, zero otherwise. The SBO variable is the quoted and proportional euro bid-ask spread for the first two regressions, and the average quoted depth at the best bid and ask quotes for the third regression. The final three regressions include the natural logarithm of the euro volume and percentage volatility. For each regression, coefficient estimates (t-statistics), adjusted R-squared values and the Durbin-Watson statistic are reported. A. Descriptive statistics Mean before (Median before) Mean after (Median after) Mean change (Median change) Quoted spread ( ) (0.028) (-0.024) ** (-0.004*) Proportional spread (%) (0.8324) (0.7941) * ( *) 5,403 (3,306) 4,726 (3,000) -677** (-306*) Volume ( ) 222,603 (-159,243) 128,398 (-80,661) -94,205** (-78,582**) Volatility (%) 3.06 (2.88) 2.84 (2.25) -0.22** (-0.63**) 27

28 Table 4, continued B. Regressions Intercept Change SBO spread / depth SBO volume ln( ) SBO volatility (%) Star volume ln( ) Star volatility (%) (Star volume) * Change (Star volatility) * Change Adj. R 2 (DW) Quoted spread ( ) Prop. spread (%) Quoted spread ( ) Prop. spread (%) (2.34) (3.02) (6.20) (7.23) (3.66) (6.23) (-4.38) (-2.98) (-4.17) (-2.57) (-5.45) (0.61) (4.22) (3.22) (1.79) ** Indicates statistical significance at the 0.01 level * Indicates statistical significance at the 0.05 level (-1.91) (-2.14) (0.22) (3.78) (1.62) (-1.67) (-2.54) (-3.20) (5.46) (3.11) (4.01) (-2.99) (1.61) (1.34) (-1.69) (-0.79) (0.201) (-0.75) (1.421) (1.591) (1.665) (1.931) (1.741) (1.824) 28

29 Table 5 Medium stock segment This table reports descriptive statistics, including quoted and proportional bid-ask spread, quoted depth, euro volume and volatility (Panel A) and regression results (Panel B) for medium Star and SBO stocks, as classified in Table 3. For each variable, the table reports the mean and median (in parentheses) for the six months before and after the structural change, and the change in mean (median) values. In the regressions, the dependant variable is measured as (i) the quoted euro bid-ask spread in the first and fourth regressions; (ii) the proportional quoted bid-ask spread in the second and fifth regressions; and (iii) the average quoted depth at the best bid and ask quotes in the third and sixth regressions. The change dummy variable takes the value of one after the structural change, zero otherwise. The SBO variable is the quoted and proportional euro bid-ask spread for the first two regressions, and the average quoted depth at the best bid and ask quotes for the third regression. The final three regressions include the natural logarithm of the euro volume and percentage volatility. For each regression, coefficient estimates (t-statistics), adjusted R-squared values and the Durbin-Watson statistic are reported. A. Descriptive statistics Mean before (Median before) Mean after (Median after) Mean change (Median change) Quoted spread ( ) (0.031) (0.022) ** (-0.009**) Proportional spread (%) (0.7442) (0.6201) ** ( *) 16,285 (11,742) 11,297 (9,034) -4,988** (-2,708**) Volume ( ) 658,322 (496,571) 442,764 (370,582) -215,558** (-125,989**) Volatility (%) 2.56 (2.95) 2.21 (2.16) -0.35** (-0.79**) 29