Ownership structure and stock market liquidity

Ownership structure and stock market liquidity: evidence from Tunisia Nadia Belkhir Boujelbéne and Abdelfatteh Bouri Research Unit Corporate Finance Financial Theory – COFFIT, Faculty of Economics Sciences and Management, University of Sfax, 3018 Sfax, Tunisia Email: n.belkhirlaposte.net Email: abdelfettah.bourifsegs.rnu.tn Corresponding author JeanLuc Prigent Research Unit THéorie Economique, Modélisation et Applications – THEMA, University of Cergy, Pontoise. 33, boulevard du Port, F95011 CergyPontoise Cedex, France Email: JeanLuc.Prigentucergy.fr Abstract: The aim of this paper is to identify and analyse the influence of ownership concentration on stock market liquidity in general, and the adverse selection component of the spread in particular for a panel of Tunisian firms from 2001 to 2007. We document that firms with greater insider ownership display significantly lower liquidity. The negative relation between liquidity and insider ownership is attributable to adverse selection. We also find that the only negative correlation between blockholders and liquidity persists is that with turnover. Thus, it appears that blockholders decrease liquidity. We find that ownership effect depends on the owner identity. Our results suggest that state ownership is negatively related to spread, and positively related to market depth. Foreign ownership has no significant effect on liquidity measures. Keywords: insider ownership; INSID; institutional ownership; INST; foreign ownership; FORG; state ownership; STATE; liquidity; bidask spread; depth; turnover; price impact; PIMP; adverse selection costs; Tunisia. Reference to this paper should be made as follows: Boujelbéne, N.B., Bouri, A. and Prigent, JL. (2011) ‘Ownership structure and stock market liquidity: evidence from Tunisia’, Int. J. Managerial and Financial Accounting, Vol. 3, No. 1, pp.91–109. Biographical notes: Nadia Belkhir Boujelbéne is a PhD student in Corporate Finance Financial Theory (COFFIT) at the University of Economics and Management in SfaxTunisia. Abdelfatteh Bouri is a Professor in Corporate Finance Financial Theory (COFFIT) at the University of Economics and Management in SfaxTunisia. JeanLuc Prigent is a Professor in Théorie Economique, Modélisation et Applications (THEMA) at the University of Cergy, Pontoise.

Int J Managerial and Financial Accounting, Vol 3, No 1, 2011 Ownership structure and stock market liquidity: evidence from Tunisia Nadia Belkhir Boujelbéne* and Abdelfatteh Bouri Research Unit Corporate Finance Financial Theory – COFFIT, Faculty of Economics Sciences and Management, University of Sfax, 3018 Sfax, Tunisia E-mail: n.belkhir@laposte.net E-mail: abdelfettah.bouri@fsegs.rnu.tn *Corresponding author Jean-Luc Prigent Research Unit THéorie Economique, Modélisation et Applications – THEMA, University of Cergy, Pontoise 33, boulevard du Port, F-95011 Cergy-Pontoise Cedex, France E-mail: Jean-Luc.Prigent@u-cergy.fr Abstract: The aim of this paper is to identify and analyse the influence of ownership concentration on stock market liquidity in general, and the adverse selection component of the spread in particular for a panel of Tunisian firms from 2001 to 2007 We document that firms with greater insider ownership display significantly lower liquidity The negative relation between liquidity and insider ownership is attributable to adverse selection We also find that the only negative correlation between blockholders and liquidity persists is that with turnover Thus, it appears that blockholders decrease liquidity We find that ownership effect depends on the owner identity Our results suggest that state ownership is negatively related to spread, and positively related to market depth Foreign ownership has no significant effect on liquidity measures Keywords: insider ownership; INSID; institutional ownership; INST; foreign ownership; FORG; state ownership; STATE; liquidity; bid-ask spread; depth; turnover; price impact; PIMP; adverse selection costs; Tunisia Reference to this paper should be made as follows: Boujelbéne, N.B., Bouri, A and Prigent, J-L (2011) ‘Ownership structure and stock market liquidity: evidence from Tunisia’, Int J Managerial and Financial Accounting, Vol 3, No 1, pp.91–109 Biographical notes: Nadia Belkhir Boujelbéne is a PhD student in Corporate Finance Financial Theory (COFFIT) at the University of Economics and Management in Sfax-Tunisia Abdelfatteh Bouri is a Professor in Corporate Finance Financial Theory (COFFIT) at the University of Economics and Management in Sfax-Tunisia Jean-Luc Prigent is a Professor in Théorie Economique, Modélisation et Applications (THEMA) at the University of Cergy, Pontoise Copyright © 2011 Inderscience Enterprises Ltd 91 92 N.B Boujelbéne et al Introduction Stock market liquidity is one of the fundamental components of market microstructure and has been viewed as an issue of interest in the financial literature The adverse selection component of bid-ask spreads, which is due to information asymmetry between dealers and informed traders, is well founded in the financial literature A fundamental objective of the present study is to explore how ownership level affects the stock market liquidity and the adverse selection component in emerging stocks markets This study has three distinct features that differentiate it from existing studies First, we enlarge the market-level database from emerging market economies Second, we gather transaction data from pure order driven market, while previous studies are collected transaction data from quote-driven markets The third feature of our study is that we introduce a set of better measures of liquidity such as quoted spread, effective spread, market depth, turnover, and price impact (PIMP) Tunisia corresponds to an ideal setting to examine these issues In fact, Tunisian listed companies have similar ownership characteristics to publicly traded companies in most countries around the world They are characterised by a high degree of ownership in general and are predominantly family-controlled The Tunisian Financial system is fragmented, dominated by banks Besides, financial institutions, including insurance, investment and securities companies own important proportions of the shares in listed companies and are often among the five largest block holders The main characteristic of ownership is that it is highly concentrated According to the study of Omri (2001), the percentage of shares held by top five shareholders, in Tunisia, should exceed 88% A lot of theoretical studies argue that the market liquidity will facilitate the exit of large shareholders and thus reduce the intervention from those shareholders (Bolton and Thadden, 1998) Holmström and Tirole (1993) derive a theoretical model for investigating the negative relationship between ownership concentration and market liquidity The model suggests that the liquidity increased when the ownership by a large owner decreased However, Maug (1998) and Kahn and Winton (1998) argue that the large shareholders tend to increase their holdings in a more liquid stock market Previous studies are instigated for developed capital markets, those are quote-driven markets and most liquid in the world as the USA (Brockman et al 2009; Rubin, 2007; Heflin and Shaw, 2000), where the institutional environments differ greatly from that in Tunisia It is well identified that emerging financial markets are not as liquid as those of developed economies The lack of liquidity is considered as a key factor for the high volatility in emerging markets and an important obstacle to financial market development This study combines corporate governance research with market microstructure research by examining a link between a corporate governance variable, ownership structure, and a market microstructure variable, stock market liquidity We divide our empirical analysis into two main sections In the first section, we investigate the effect of ownership structure on the firm’s market liquidity, including bid-ask spread, depths, turnover and PIMP We find that insider ownership (INSID) Ownership structure and stock market liquidity 93 significantly increases the firm’s quoted and effective bid-ask spread and PIMP measure INSID also significantly decreases the depth The block ownership significantly reduces the turnover Thus, our results suggest that blockholder ownership (BLC) is associated with reduced market liquidity In our second section, we examine the relation between the ownership structure and adverse selection component We construct estimates of the portion of the spread due to adverse selection using the Lin et al (1995) decomposition model, and find that the information component of bid-ask spread increases as the level of ownership by insiders increases The remainder of the paper is organised as follows The next section gives a brief review of the literature Section of the paper describes the data and the methodology The following Section presents the main results and their interpretation The article ends, in a last section with a brief summary of conclusions Literature review The relation between liquidity and ownership has received considerable attention in financial economics from a variety of perspective Researchers have considered both the effect of block ownership on liquidity as well as the effect of owner identity on liquidity Previous studies have proposed two hypotheses to investigate the relation between ownership structure and market liquidity: the adverse selection hypothesis and the trading hypothesis The first hypothesis suggests that while informed shareholders have private information about firm value, a level of information asymmetry increases, which reduces liquidity (Grossman and Stiglitz, 1980; Glosten and Milgrom, 1985; Kyle, 1985) The trading hypothesis posits that when a firm’s ownership is concentrated, the free float is limited, there are fewer trades, and therefore the liquidity is decreased (Demsetz, 1968; Merton, 1987) Given these two hypotheses, examining the empirical relationship between liquidity and ownership is complicated as various ownership proxies may differ in their suitability for detaining these two costs with adverse selection costs on the one side, and trading frictions on the other Most of empirical studies were conducted on developed markets; particularly in the American market show that block ownership impairs the firm’s market liquidity (Brockman et al., 2009; Rubin, 2007; Heflin and Shaw, 2000) The large blockholders have access to private information and consequently they acquire superior information about firm value thus potential benefits from blockholder monitoring might be partially compensate by reduced liquidity attributable to wider spreads Heflin and Shaw (2000) examine the relation between block ownership and market liquidity They find that both relative and effective spreads are larger in the firm with higher BLC They also find adverse selection component estimates increase as the ownership by blockholders increases These results show that blockholders increase liquidity costs because of their access to private information However, Brockman et al (2009) find that the reduced trading activity has a real friction effect on the firm’s liquidity After controlling for this real friction effect, they find little evidence that block ownership has a negative impact on informational friction Their findings show that block ownership affects market liquidity essentially through its effect on real frictions and not informational frictions 94 N.B Boujelbéne et al Naes (2004) argue that the ownership concentration, measured by the aggregate holdings of the five largest owners, increases the spread This result is in conformity with the theoretical predictions Comerton-Forde and Rydge (2006) report, on a sample of firm listed on the Australian Stock Exchange, a positive effect between ownership concentration and illiquidity Market microstructure theory predicts a negative relationship between stock market liquidity and INSID The insiders have access to privileged information about the firm, and they trade based on this information The empirical evidence on the relation between stock market liquidity and INSID is inconclusive Sarin et al (2000) argue that the presence of insiders increase the probability of informed trading and the cost of transaction Thus, this contributes to higher level of information asymmetry and reduces liquidity Using a simultaneous equations approach, Sarin et al (2000) find that INSID is positively related to bid-ask spreads and negatively related to depth But, Dennis and Weston (2001) find that spread is negatively related to the level of INSID Kini and Mian (1995), who examine whether ownership structure affects the specialist’s choice of bid-ask spread on the NYSE, document a no positive relation between bid-ask spread and INSID The relation between liquidity and INSID in Norwegian market is studied in Naes (2004) A significant positive relationship is found between the spread measures and the holdings of the primary insiders Primary insiders comprise company managers and members of the Board of Directors Rubin (2007) finds that insider’s ownership of US firms is negatively associated with trade-based measures (volume and turnover), but positively associated with order-driven liquidity measures The predicted impact of institutional ownership (INST) on liquidity is not clear On the one hand, institutional investors obtain private information about the firm because they have resources to make any analyses on the firm and acquire information The market makers are brought to widen spreads Thus, increased INST should lead to wider spreads and higher adverse selection costs On the other hand, institutional investors are heterogeneous and hold diversified portfolios Many studies focus on the negative relation between liquidity and INST (Sarin et al., 2000; Fehle 2004); however other studies have noted positive effect of INST on liquidity (Dennis and Weston, 2001) Sarin et al (2000) treat both ownership structure and spreads as endogenous and they show that greater INST leads to larger spreads, the adverse selection components of the spread, and smaller quoted depths These results contradict those obtained by Dennis and Weston (2001), who find that the relative spread is negatively associated to the INST They suggest that institutional investors prefer stocks with narrower spreads since they are more liquid The results corroborate those obtained by Tinic (1972) and Hamilton (1978) These authors found a relation negative between INST and spread for a sample of NYSE and NASDAQ stocks, respectively Fehle (2004) examines the relation between bid-ask spread, measured both as effective and specialist spreads and INST He found that spreads are negatively related to INST share Barabanov and Mc Namara (2002) show that the relative bid-ask spreads are negatively related to the level of INST Rubin (2007) finds a two-sided relation between INST and liquidity On the one hand, liquidity is positively related with the level of INST; on the other hand, liquidity is negatively related with the concentration of INST Agarwal (2007) proves that market liquidity increases with INST but begins to decline once it arrives at to 40% Ownership structure and stock market liquidity 95 Foreign investors invest to acquire gains from diversification; so they have an informational disadvantage vis-a-vis domestic investors There are various potential reasons for the negative liquidity effect from foreign institutions Many studies demonstrate that institutional trading is more possible information-driven (e.g., Ali et al., 2004; Bushee and Goodman, 2007), and INST rises the degree of information asymmetry (e.g., Dennis and Weston, 2001; Agarwal, 2007; Rubin, 2007) In emerging markets, foreign investors are better traders since they are better informed (Grinblatt and Keloharju, 2000; Seasholes, 2004) Using a sample of Indonesian firms, Rhee and Wang (2009) find that foreign ownership (FORG) has a negative impact on liquidity They show that a 10% increase in FORG is associated with approximately 2% increase in the bid-ask spread, 3% decrease in depth, and 4% rise in price sensitivity Naes (2004) show that FORG is negatively related to spreads and positively related to depth The inefficiency of state ownership (STATE) is claimed to follow from factors such as a slow decision making process and conflicts between the dual role of being an owner and the governing authority Therefore a negative effect from inefficient STATE should perhaps influence performance directly But, it may also be reflected in the liquidity Attig et al (2003, 2006) find that government is associated with a lower spread Naes (2004) finds that STATE is positively associated with adverse selection cost and negatively associated with market depth Data and methods of analysis 3.1 Data and sample description Our data are kindly provided by the Tunisian Stock Exchange (BVMT) The trading system on the BVMT is an electronic limit order market The orders are submitted by brokers on the behalf of investors and executed through an automated trading system, using a computerised limit-order book, known as SUPERCAC Trading is executed from 8:30 am to 11:30 am from Monday to Friday It commenced by a pre-opening session (from 9:00 am to 10:00 am) through which investors can deposit, change or cancel orders but no trades are permitted A theoretical opening price is displayed in real time to show the market tendency There are two main trading methods: call auction and continuous trading The market opens by a call auction for all stocks at some point of time during the first five-minute opening period For the more actively traded stocks, this is followed by a continuous market until 11:30 am but, for illiquid stocks, a second call is set at 10:15 am for securities not traded at the open call and a last call takes place at 11:00 am The BVMT is a pure order driven market where investors can choose between market and limit orders, so as liquidity is only provided by limit order traders Market orders have no limit on prices and look for immediate execution while limit orders specify a price either above the current asks or below the current bid and offer price improvement relative to market orders A market order is matched with the best opposite quote of the order book Limit orders are held in the limit order book until they are matched with incoming market orders to produce trades; otherwise, they are annulled or modified 96 N.B Boujelbéne et al A limit order faces the risk of non-execution whereas a market order executes with certainty At the end of each month, all orders are purged from the limit order book Table Number of companies listed on Tunisian Stock Exchange 2001 2002 2003 2004 2005 2006 2007 45 46 45 44 45 48 51 6,527 5,490 3,840 3,085 2,976 2,842 3,275 Number of companies Market capitalisation MD* Notes: *MD: millions de dinars This table presents the number of companies listed on the Tunisian Stock Exchange (BVMT) at year-end and the market capitalisation values Our sample includes the 6-year period beginning in 2001 and ending in 2007 Table shows the number of companies listed on the Tunisian Stock Exchange (BVMT) at year-end and the market capitalisation values The sample period is from January 2001 to 31 December 2007 The first dataset is the proportion of shares held by different types of investors There is no electronic database on Tunisian firm ownership including relevant information on corporate governance characteristics Data of ownership are collected manually from firm’s annual reports available on the Tunisian Stock Exchange, from the leaflets of issue of shares and from financial statements published in the official bulletins of the Tunisian Stock Exchange (BVMT) for seven years The ownership structures are those available on the 31st December of each year Our second dataset is the daily stock trading summary, including high, low, closing prices, trading volumes, end-of-day best bid prices, volume available at bid, end-of-day best ask price, volume available at ask for each stock and market capitalisation These data are obtained from the Tunisian Stock Exchange (BVMT) and are used to construct a variety of liquidity measures We exclude firms for which trading and liquidity data are not available 3.2 Variable construction The final sample consists of 210 firm-year observations Table present the variable definitions for the main variables used in the study 3.2.1 Ownership structure The ownership structure of a firm in our sample is defined in terms of five variables: blockholdings, INSID, INST, STATE and FORG Our measure for ownership by blockholders (BLC) is the percentage of shares held by the large blockholders, whose own more than 5% INSID is defined as the percentage of the firm’s shares held by officers, directors and all other investors who may be related to the management We compute the total number of shares held by institutional investors as a percentage of shares by INST We considered as institutional investors, the banks, the investment firms, the insurance companies, pension funds, and mutual funds STATE is the percentage of shares held by the government FORG is defined as the percentage of shares held by the foreign investors Ownership structure and stock market liquidity Table 97 Variable definitions Variable Definition BLC The percentage of the firm’s shares held by the large blockholders, whose own more than 5% INSID The percentage of the firm’s shares held by officers, directors and all other investors who may be related to the management INST The percentage of the firm’s shares held by the institutional investors (the banks, the investment firms, the insurance companies, pension funds, and mutual funds) STATE The percentage of the firm’s shares held by the government FORG The percentage of the firm’s shares held by the foreign investors AQS The absolute quoted bid-ask spread is defined as the quoted ask price minus the quoted bid price RQS The relative quoted bid-ask spread is defined as the quoted ask price minus the quoted bid price scaled by their midpoint AES The absolute effective bid-ask spread is defined as two times the absolute value of the difference between the transaction price and the quoted midpoint RES The relative effective bid-ask spread is defined as two times the absolute value of the difference between the transaction price and the quoted midpoint, scaled by the quoted midpoint DEPTH The quoted depth is calculated as the number of shares at quoted bid and ask multiplied by their respective prices TURN The turnover is defined as the number of shares traded divided by the number of shares outstanding PIMP The price impact is the ratio of the daily absolute return to the daily dinar volume PRICE The price is as the average of daily closing price VOLUME The trading volume is defined as total trading volume divided by of trading days VOL The volatility is measured as the standard deviation of daily close-to-close returns SIZE The firm size is the natural logarithm of the market value of the firm’s equity, calculated at the end of each trading day and averaged over the year AS The adverse selection component of spread is estimated follow the method of Lin, Sanger and Booth (LSB, 1995) Notes: Table reports variable definitions for the variables used in the study Our sample includes the 6-year period beginning in 2001 and ending in 2007 Our sample included stocks traded on the Tunisian Stock Exchange (BVMT) 3.2.2 Liquidity measures In addition to the ownership data, we construct various dependent variables from the Tunisian Stock Exchange (BVMT) Because liquidity has many dimensions, we use seven liquidity measures that are usual in the literature (see, e.g., Aitken and Comerton-Forbe, 2003; Goyenko et al., 2009; Fang et al., 2009) The first measure is the absolute quoted bid ask spread (AQS) defined as the quoted ask price minus the quoted bid price, AQSt = Askt − Bidt The second measure is the relative quoted bid-ask spread (RQS) defined as the quoted ask price minus the quoted bid price scaled by their 98 N.B Boujelbéne et al Askt − Bidt The third measure is the absolute effective bid-ask ⎛ Askt + Bidt ⎞ ⎜ ⎟ ⎝ ⎠ spread (AES) defined as two times the absolute value of the difference between the Askt + Bidt The fourth transaction price and the quoted midpoint, AESt = pt − measure is the relative effective bid-ask spread (RES) It is defined as two times the absolute value of the difference between the transaction price and the quoted midpoint, Askt + Bidt pt − Our fifth measure is the scaled by the quoted midpoint, RESt = Askt + Bidt quoted depths (DEPTH) calculated as the number of shares at quoted bid and ask Pt ask ⋅ Qt ask + Ptbid ⋅ Qtbid The sixth multiplied by their respective prices, DEPTH t = measure is the turnover (TURN), defined as the number of shares traded divided by the number of shares outstanding The seventh measure is the PIMP is the measure developed by Amihud (2002) and later used by Acharya and Pedersen (2005) It is the Rt ratio of the daily absolute return to the daily dinar volume,1 PIMPt = VOLUMEt We identify the impact of liquidity measures while controlling other factors that may affect ownership structure Stoll (1978) shows that relative spreads are negatively related with trading volume and share price, and positively related with returns volatility In addition, Glosten and Harris (1988) suggest that spreads may be influenced by factors such as share price, trading volume, return volatility and firm size We use a number of control variables defined in the pervious literature to account for any effects of external factors in our analysis Our control variables include share price, trading volume, volatility, and firm size Price (PRICE) is the average of daily closing price, trading volume (VOLUME) is defined as total trading volume divided by of trading days, volatility (VOL) (Heflin and Shaw, 2000) is measured as the standard deviation of daily close-to-close returns, and firm size2 (SIZE) is the logarithm of the market value of the firm’s equity, calculated at the end of each trading day and averaged over the year We use log transformation of market capitalisation values to reduce skewness This variable was also used by Rubin (2007) and Comerton-Forde and Rydge (2006) We anticipate spreads to be negatively associated to price, trading volume, and firm size, and positively associated to volatility If little spreads are accompanied by high depth and vice versa, we would anticipate depth to be positively associated to trading volume, and firm size, and negatively associated to volatility We define and present spread decomposition model in the next section midpoint, RQSt = 3.2.3 Adverse selection model We compute an estimate of adverse selection component following the method introduced by Lin et al (1995) Ownership structure and stock market liquidity 99 We obtain adverse selection spread component estimates from estimating the following regression for each firm using ordinary least squares: Qt +1 − Qt = λ zt + et +1 (1) where Qt = (At + Bt)/2 is the quoted bid-ask spread midpoint at time t, zt = Pt – Qt, Pt is the transaction price prior to quoted spread at time t The coefficient λ is the LSB adverse selection component of the bid-ask spread attributable to informed trading, and et + is a normally distributed error term Empirical results 4.1 Descriptive statistics and univariate tests After having defined the different variables, we suggest to present the descriptive statistics of ownership, liquidity, and other variables in the following table Table reports the summary statistics for liquidity measures and control variables relating to dimensions of the liquidity and the asymmetry of information selected, with the explanatory variables namely those concerning the ownership structure [Blockholdings (BLC), INSID, INST, STATE, FORG] like those concerning the variables of control (price, volume, volatility and size) over the period 2001–2007 In Table 3, we report summary statistics (mean, standard deviation, minimum value, maximum value, the coefficient of skewness, the coefficient of kurtosis, the Jarque and Bera statistics) for the variables used in our analysis Since our sample consists of 30 Tunisian companies, the distribution of ownership shows that the block ownership varies from a low of 7.48% to a maximum of 80.15% The mean proportion of shares outstanding held by blockholders is 37.292% The level of INSID varies between 0% and 74.5% with an average value of 6.193% The descriptive statistics also show that of institutional investors consists of banks, investment firms, insurance companies, pension funds, and mutual funds, hold on average 23.548% of a firm Similarly, Jennings et al (2002) found that this value is equal to 23.21% On average, the level of STATE in our sample is 10.511% State is present for only a small portion of the sample We find that foreign investors control 11.670% of company share on average The descriptive statistics for ownership shows the importance of concentration in Tunisia The statistics for the liquidity measures are calculated for each stock, and then averaged across stocks Given that the liquidity measures are highly skewed, we employ the log transformation of some measures The average relative quoted bid-ask spread is 2.0893% The values of skewness and kurtosis of this variable demonstrate that the distribution of spread is leptokurtic (kurtosis > 3) and asymmetric (skewness > 0)3 The average relative effective bid-ask spread is 2.3288% The average quoted depth is 325.901 The average asymmetric information cost is 0.3184 Our sample firms have an average market capitalisation of 1.34108 dinars The mean volatility is 0.0201 Table presents correlation matrix of the variables included in the tests Panel A reports correlation between all ownership structure Panel B exhibits correlation between all liquidity measures: spreads, depth, turnover, PIMP and adverse selection costs Panel C shows correlation between liquidity measures, ownership structure and control variables 100 Table N.B Boujelbéne et al Descriptive statistics for ownership, liquidity and control variables Ownership structure and stock market liquidity Table Correlation matrix 101 102 Table N.B Boujelbéne et al Correlation matrix (continued) Ownership structure and stock market liquidity 103 Table reports correlation matrix Panel A shows that INSID is negatively correlated at the 10% significance level with block ownership and INST In addition, STATE is inversely correlated with FORG and INST Panel B shows that relative quoted spread (RQS) is positively related effective spread and negatively correlated with depths The correlation is strong Panel C provides the correlation structure between liquidity measures, ownership variables and control variables As predicted by the theory, the spread measures are positively correlated with the INSID and FORG, and negatively related to the STATE INST is positively correlated with quoted bid-ask spread The cost of adverse selection is positively correlated to the blockholdings The correlation matrix shows that some variable are highly correlated For this reason, we will present in the following section the regression to examine the true relationship between the independent variables and liquidity 4.2 Impact of ownership on stock liquidity To examine the effect of ownership on stock liquidity while controlling for other factors, we estimate various forms of the following cross-sectional regression: LIQit = β + β1 BLCit + β INSIDit + β INSTit + β STATEit + β FORGit + β PRICEit + β 7VOLUMEit + β8VOLit + β SIZEit + ε it where εit = µi + vit, i = 1, ., N and t = 1, T μi represents a firm-specific effect to be fixed or random, νit is a standard residual term and β0, β1, β2, β3, β4, β5, β6, β7, β8 and β9 are the estimated coefficients of the model LIQ is either absolute quoted bid ask spread, relative quoted bid ask spread, absolute effective bid-ask spread, relative effective bid-ask spread, quoted depths, turnover, or PIMP We use natural logarithms of relative spreads, quoted depths, turnover, and firm size to reduce heteroskedasticity BLC is the percentage of outstanding shares held by the large blockholders INSID is the percentage of the firm’s share held by officers, directors and all other investors who may be related to the management INST is the percentage of shares by institutional investors STATE is the percentage of shares held by the government FORG is the percentage of shares held by the foreign investors From results of earlier research we expect the coefficient on volume and price to be negative, and the coefficient on standard deviation to be positive Our objective in this research paper design is to examine the impact of block ownership and identity of owners on the firm’s market liquidity In Table 5, we present our regression model (1) results for AQS, RQS, absolute effective spread (AES), relative effective spread (RES), quoted depth, turnover and PIMP The block ownership coefficient for spreads is positive and insignificant Results on depth are consistent with those on quoted and effective spreads The only negative correlation between blockholders and liquidity persists is that with turnover Thus, it appears that blockholders decrease liquidity BLC is potentially costly, because their monitoring might provide blockholders with access to private information The coefficients of the INSID are all positive for the spread measures The coefficient estimates on the percentage of shares held by insiders equal 0.0104, 0.0089, 0.0107, and 0.0065 respectively in columns 2, 3, 4, and of Table 4, and each coefficient is positive and significant, implying that INSID lead to wider spreads The INSID coefficient for depth (–0.0056) is negative and significant, this consistent with the notion that insiders decrease the market liquidity 104 Table N.B Boujelbéne et al Regression of liquidity on ownership structure Ownership structure and stock market liquidity 105 INST does not significantly affect spreads The coefficient is positive but it is not significant Our result is not consistent with the findings of Rubin (2007), who find that the relation between INST and spreads is positive and significant Result on PIMP is no consistent with this on spread The INST coefficient for PIMP (0.0237) is positive and significant, suggesting that INST decreases the market liquidity The coefficient of STATE is negative and significant for quoted spread and positive and significant for depth Thus, STATE is negatively related to absolute spreads, and positively related to market depth FORG has no significant effect on liquidity measures Our result is not consistent with the findings of Rhee and Wang (2009), who find that foreign holdings have a negative impact on liquidity The control variables are significant and maintain their expected signs (except VOL which measures the volatility) Therefore, price affects positively the AQS and the AES effective and negatively the RQS and the RES This result confirms that obtained by Rubin (2007) but it contradicts the result of Comerton-Forde and Rydge (2006) Trading volume has a negative and statistically significant effect on spreads and PIMP and positive and significant effect on depth and turnover Firm size has a negative and statistically significant effect on relative spreads and positive and significant effect on depth, this result is coherent with the assumptions of the theory of the microstructure of the markets Therefore, large firms have narrower relative spreads These findings are consistent with the theoretical predictions of Stoll (1978), and the empirical evidence reported in Stoll (1978), Chiang and Venkatesh (1988), Heflin and Shaw (2000), Rubin (2007) and Rhee and Wang (2009) The variable VOL which measures the standard deviation of daily returns presents a positive sign for the spreads but it is no significant There is no effect from liquidity measures and volatility 4.3 Additional liquidity measures: adverse selection In this section we investigate the effect of ownership variables on the adverse selection spread component of the bid-ask spread We adapt the methods introduced by Lin et al (1995) to estimate adverse selection spread component To examine the moderating effect of ownership structure on the cost of the adverse selection, we use the following pooled cross-sectional time series model: ASit = β + β1 BLCit + β INSIDit + β INSTit + β STATEit + β FORGit + β PRICEit + β 7VOLUMEit + β8VOLit + β SIZEit + ε it In Table 6, we report the Lin, Sanger and Booth adverse selection component results for ownership structure The block ownership coefficient (0.0110) is positive and statistically significant This result is in conformity with our hypothesis according to which the block ownership has a cost of liquidity, then, the presence of the large shareholders increases the cost of adverse selection Thus when the large shareholders acquire information privileged on the company, the gain of control can be relatively compensated by the decrease of the liquidity The insiders’ ownership coefficient (0.0037) is positive and significant Consistent with our liquidity results in Table 4, INSID increases the adverse selection component of bid-ask spread The negative relation between liquidity and INSID is attributable to adverse selection This suggests then, that the increase on behalf of the leaders generates an opportunist risk of behaviour which increases the costs of asymmetry of information N.B Boujelbéne et al 106 This result is in conformity with Gosnell et al (1992), who show that the insiders use monopolistic information to generate abnormal return from trading in their firms’ shares We find evidence that the proportion of the spread attributable to adverse selection increase as INST increases STATE and FORG does not significantly affect the adverse selection component Table Regression of adverse selection costs on ownership structure Adverse selection (LSB) Intercept –1.5273 (–1.09) BLC 0.0110 (2.43) ** INSID 0.0037 (2.32) ** INST 0.0048 (1.75)* STATE –0.0006 (–0.14) FORG 0.0039 (0.67) PRICE 0.0087 (1.54) VOLU 0.1227 (1.65) RVOL 3.5306 (2.13) ** SIZE –0.0704 (–0.76) R square 0.2757 Notes: This table presents the results on regressions of adverse selection spread component on ownership structure The sample period is from 2001 to 2007 Our sample included stocks traded on the Tunisian stock exchange (BVMT) Blockholdings (BLC) is the percentage of shares held by the large shareholder INSID is defined as the fraction of total shares outstanding held by the firm’s insiders Insiders are defined as officers, directors and all other investors who may be related to the management INST is the proportion of shares outstanding held by institutional investors STATE is the percentage of shares held by the government FORG is defined as the percentage of shares held by the foreign investors Liquidity variables are calculated using data from Tunisian stock exchange Share price (PRICE) is the average of daily closing price Trading volume (VOLUME) is defined as total trading volume divided by of trading days Volatility (VOL) is measured as the standard deviation of daily close-to-close returns Firm size (SIZE) is the logarithm of the market value of the firm’s equity Numbers in parentheses are t-statistics.*Denotes significance at the 10% level, **denotes significance at the 5% level, and ***denotes significance at the 1% level Conclusions This study provides an analysis of structure ownership’s effect on liquidity and on adverse selection component from a sample of 30 Tunisians firms listed in the period from 2001 to 2007 We execute empirical tests to determine whether spreads, quoted depths, turnover and PIMP are associated with the proportion of the firm owned by blockholders, insiders, institutional, state and foreign investors We find that both relative and effective spreads increase and quoted depth decreases as the proportion of the firm owned by insiders’ increases However STATE is negatively associated with spreads, and positively associated with market depth In addition, our results suggest that turnover Ownership structure and stock market liquidity 107 reduces as the level of ownership by blockholders rises We also find PIMP is positively related to INST Further, we determine estimates of the portion of bid-ask spread due to adverse selection adapting the methods introduced by Lin et al (1995), and find the presence of the large shareholders increases the cost of adverse selection Thus, this relation proposes that blockholders have an informational advantage Our empirical results show that block ownership impairs the firm’s market liquidity by increasing its asymmetric information costs Our results reveal that both INSID and INST are found to increase the adverse selection component STATE and FORG does not significantly affect the adverse selection component This study also corresponds to a natural starting point for some further work and suggests a future research to address the question of the effect of corporate ownership on market microstructure References Acharya, V and Pedersen, L (2005) ‘Asset pricing with liquidity risk’, Journal of Financial Economics, Vol 77, pp.375–410 Agarwal, P (2007) ‘Institutional ownership and stock liquidity’, Working Paper, Cornell University Aitken, M and Comerton-Forbe, C (2003) ‘How should liquidity be measured?’, Pacific-Basin Finance Journal, Vol 11, pp.45–59 Ali, A., Durtchi, C., Lev, B and Trombley, M (2004) ‘Changes institutional ownership and subsequent earnings announcement abnormal returns’, Journal of Accounting, Auditing, and Finance, Vol 19, pp.221–248 Amihud, Y (2002) ‘Illiquidity and stock returns: cross-section and time-series results’, Journal of Financial Markets, Vol 5, pp.31–56 Attig, N., Fong, L and Gadhoum, Y (2006) ‘Effects 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Rhee, S.G and Wang, J (2009) ‘Foreign institutional ownership and stock market liquidity: evidence from Indonesia’, Journal of Banking & Finance, doi:10.1016/j.jbankfin.2009.01.008 Rubin, A (2007) Ownership level, ownership concentration and liquidity , Journal of Financial Markets, Vol 10, No 3, pp.219–248 Sarin, A., Shastri, K.A and Shastri, K (2000) Ownership structure and stock market liquidity ,.. .Ownership structure and stock market liquidity Table 4 Correlation matrix 101 102 Table 4 N.B Boujelbéne et al Correlation matrix (continued) Ownership structure and stock market liquidity 103 Table 4 reports correlation matrix Panel A shows that INSID is negatively correlated at the 10% significance level with block ownership and INST In addition, STATE is inversely correlated with FORG and INST... efficient markets’, American Economic Review, Vol 70, No 3, pp.393–408 Hamilton, J.L (1978) ‘Marketplace organisation and marketability: NASDAQ, the stock exchange and the National Market System’, Journal of finance, Vol 33, pp.487–503 Heflin, F and Shaw, W.K (2000) ‘Blockholder ownership and market liquidity , Journal of Financial and Quantitative Analysis, Vol 35, pp.621–633 Holmström, B and Tirole,... P.J and Weston, J.P (2001) Who’s Informed? An Analysis of Stock Ownership and Informed Trading, AFA 2002 Fang, V.W., Noe, T.H and Tice, S (2009) Stock market liquidity and firm value’, Journal of Financial Economics, Vol 94, pp.150–169 Fehle, F (2004) ‘Bid-ask spreads and institutional ownership , Review of Quantitative Finance and Accounting, Vol 22, pp.275–292 Ginglinger, E and Hamon, J (2007) Ownership, ... Holmström, B and Tirole, J (1993) Market liquidity and performance monitoring’, Journal of Political Economy, Vol 101, No 4, pp.678–709 Jennings, W., Schnatterly, K and Seguin, P (2002) ‘Institutional ownership, information and liquidity , Innovation in Investments and Corporate Finance, Vol 7, pp.41–71 Kahn, C and Winton, A (1998) Ownership structure, speculation and shareholder intervention’, Journal... 0.0107, and 0.0065 respectively in columns 2, 3, 4, and 5 of Table 4, and each coefficient is positive and significant, implying that INSID lead to wider spreads The INSID coefficient for depth (–0.0056) is negative and significant, this consistent with the notion that insiders decrease the market liquidity 104 Table 5 N.B Boujelbéne et al Regression of liquidity on ownership structure Ownership structure. .. address the question of the effect of corporate ownership on market microstructure References Acharya, V and Pedersen, L (2005) ‘Asset pricing with liquidity risk’, Journal of Financial Economics, Vol 77, pp.375–410 Agarwal, P (2007) ‘Institutional ownership and stock liquidity , Working Paper, Cornell University Aitken, M and Comerton-Forbe, C (2003) ‘How should liquidity be measured?’, Pacific-Basin Finance... Bolton, P and Von Thadden, E.L (1998) ‘Blocks, liquidity and corporate control’, Journal of Finance, Vol 53 Brockman, P., Chung, D.Y and Yan, X (2009) ‘Block ownership, trading activity and market liquidity , Journal of Financial and Quantitative Analysis, Vol 44, No 6, pp.1403–1426 Bushee, B.J and Goodman, T.H (2007) ‘Which institutional investors trade based on private information about earnings and returns’,... asymmetry and stock liquidity , Journal of Banking & Finance, Vol 30, No 10, pp.2875–2892 Attig, N., Gadhoum, Y and Lang, L.H.P (2003) Bid-Ask Spread, Asymmetric Information and Ultimate Ownership, European Financial Management Association (EFMA) Meeting, Helsinki Barabanov, S and McNamara, M (2002) Market perception of information asymmetry: concentration of ownership by different types of institutions and. .. pp.45–59 Ali, A., Durtchi, C., Lev, B and Trombley, M (2004) ‘Changes institutional ownership and subsequent earnings announcement abnormal returns’, Journal of Accounting, Auditing, and Finance, Vol 19, pp.221–248 Amihud, Y (2002) ‘Illiquidity and stock returns: cross-section and time-series results’, Journal of Financial Markets, Vol 5, pp.31–56 Attig, N., Fong, L and Gadhoum, Y (2006) ‘Effects of large