Factors affecting the liquidity of stocks listed on the Vietnamese stock market

of that stock increased. This result may be the reason to explain the increased trading activity on the NYSE due to lower trading costs.

Two views emerged after Demsetz's (1968) study on the spread between bid and offer prices: the first view is based on the relationship between the spread and the cost of holding shares. Ho and Stoll's (1980) study added and added the reason from the competition among market makers. The second view is based on the information asymmetry between the group of investors with inside information advantage who will estimate more accurately about the future stock price and the group of investors who do not know this information. Copeland and Galai's (1983) study on the spread between bid and offer prices was based on (Demsetz, 1968) but assumed that: market makers will maximize their benefits by setting the spread between bid and offer prices. This price difference has also been studied by (Black and Scholes, 1973) with the aim of building a formula to calculate the value of stock call and put options and assuming the following about the stock market:

 Short-term interest rates are fixed;

 During continuous order matching, stock prices fluctuate randomly and expected profits are fixed;

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 No stock transaction costs;

 Stocks that do not pay dividends;

 “European” style options can only be exercised at expiration;

 Can short sell stocks or borrow at short-term interest rates to buy stocks;

 There is no additional cost to sell shares immediately, information is perfect between buyers and sellers of shares.

The market maker's valuation calculated in the study of (Copeland and Galai, 1983) is based on the assumption that if the dealer conducts a transaction with insiders, he will definitely lose due to information differences, but on the contrary, he will receive income if he transacts with ordinary investors. This assumption makes the dealer set the spread between the bid and ask prices as a trade-off between the expected loss and profit when trading with the two groups of investors with inside information and the remaining group of investors. The expected loss - profit is estimated with the following formula:

ஶ ୏ ా

p ୍ቊන (S − K ୅ ) f(S)dS + න (K ୆− S)f(S)dSቋ

୏ ఽ ଴

With 𝑃 ூis the probability that the investor has inside information, 0< 𝑃 ூ<1; 𝐾 ஺offering price; 𝐾 ஻bid price; S is the stock price, the function f(S) follows a random distribution. The research results

Research shows that, with the goal of maximizing the expected profit, the agent will set a suitable price difference to trade off between the loss when trading with investors with inside information and the expected profit when trading with ordinary investors. Because if the price difference is large, the agent will reduce the loss when trading with investors with inside information but will also reduce the profit when trading with ordinary investors. On the contrary, if the price difference is narrowed, the expected loss - profit will increase together. In addition, research proves that in both perfect competitive and imperfect competitive markets, the result is that: the coefficient P i is higher in the case of stocks with low trading frequency. That is, due to the asymmetric information of investor groups, the price difference has a negative correlation with trading activities and reduces the competitiveness of the market.

From the overview of studies on the stock market by (Demsetz, 1968), (Black, 1971), or (Ho and Stoll, 1980), (Stoll, 1989), (Copeland and Galai, 1983), (Kyle, 1985), (French and Roll, 1986), these are pioneering studies that laid the theoretical foundation for TKCCP. The authors have proven that TKCCP comes from the influence of asymmetric information between investor groups and stock trading activities on the stock market. Firstly, when trading activities on the market are low, the cost of conducting stock transactions will increase such as: time to process orders, cost of holding stocks (considered as inventory) and this causes TKCCP to decrease. Secondly, asymmetric information increases the risk of stock trading. When investors lack information about the business, they will tend to set a low purchase price and a higher selling price to reduce the probability of loss. On the contrary, investors with information advantages will be able to more accurately assess the stock price, so their transactions will not follow the law of supply and demand in the market, making the market less competitive and reducing TKCCP. To supplement the evidence for the theoretical model of measuring TKCCP, the author will continue to review empirical studies on TKCCP.

In line with the research of (Kyle, 1985) and (French and Roll, 1986), the empirical research on TKCCP was determined by Admati and Pfleiderer (1988) based on the time and cost to sell stocks when observing price changes in a short period of time on the US stock market. Liquidity is determined based on the change in stock price when impacted by changes in trading volume. Costs incurred can be due to price changes or transaction costs. The model structure of Admati and Pfleiderer (1988) is built on the model of (Kyle, 1985) but is simpler due to the assumption that investors have the same type of private information and only use it in one period. Investors trade according to their needs but only trade once to limit costs. However,

If the quantity and content of private information are accurate and constant over time, then the result in equilibrium stock prices also does not change. The stock price in period t is determined as follows: with the expectation of the information disclosure condition - F in the same period and plus the reflection of information on the order flows -  t of investors:

୲

P ෩ ୲ ൫Δ ෩ ୲ ,  ෩ ୲ ൯ = F ത + ෍ δ ෩ த+ λ ୲ ω෥ ୲

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The stock price set by market makers will follow a linear distribution with expectation  ෩ ௧and variance ∆ ෨ ௧𝛿 ሚ ௧ ାଵ + 𝜀 ௧ ̃ ; Coefficient  t measures market depth

୲

was inspired by the research of (Kyle, 1985). In the equilibrium state of the market, when investors with information advantage place orders in period t with value x෤ ୧=

β ୧൫δ ෨ + ε෤ ൯ ; has β ୧= ටஏ ౪With  tis the total variance of the transactions

୲ ୲ାଵ ୲

୲ ୬ ౪ ൫୴ୟ୰൫ஔ ෩ ౪ శభ ൯ାம ౪ ൯

t is the liquidity in period t (trading from ordinary investors); n t is the number of informed investors; 𝑣𝑎𝑟(𝜀 ௧ ̃ ) = 𝜙 . The depth of the market is determined by

recipe:

var൫δ ෨ ୲ ାଵ ൯ n ୲

λ ୲=

n ୲+ 1 ඨ Ψ ୲ ൫var൫δ ෨

number

൯ + ϕ ୲ ൯

The result  t decreases as  t decreases, that is, the market depth is greater when there are more liquid transactions.  t decreases as n t increases, the market maker's income decreases as the number of investors with informational advantages increases, but when all investors with informational advantages observe the same information and invest at the same time, it will increase the competition among investors in this group, causing the coefficient  t to decrease. When deciding to invest in any type of asset, investors consider the possibility of reselling them in the future, how much it will cost, or what selling price the market can accept. Therefore, instead of holding stocks for the long term, investors will be willing to sell when they see that demand for that stock is increasing. This affects the stock price in the short term.

Previously, Amihud and Mendelson (1986) studied the impact of bid-ask spread on asset valuation. The spread was calculated based on the bid and ask prices of the last trading session of the year. Therefore, this measure is controversial because the cost is only determined at one point in time. Because, transaction costs need to be determined throughout the process. Campbell et al.

(1997) (cited in (Fehle, 2004)) identified three components in the spread measure: order processing costs, securities holding costs and adverse selection costs. Another study conducted on the US stock market by the group (Chordia et al., 2000; Chordia et al., 2001a) measured the relationship between liquidity, asymmetric information and transaction costs. The research group proposed a number of measures

about TKCCP as follows: Price difference (QSPR) = P ୅ − P ୆ ;

Relative Price Difference (PQSPR) = ୔ ఽ ି୔ ా ; Depth of Market (DEP) =

୔ ౉

୅

ଵ (Q ଶ

+ Q ୆

) ; Order price spread (ESPR) = 2 ∗ |P ୲

− P ୑

| and

Percentage order price spread (PESPR) = ଶ | ୔ ౪ ି ୔ ౉ | .

୔ ౪

With, P A : Ask price, P B : Buy price, P T : Matched transaction price, P M = P B - P A, Q A is the offer volume and Q B is the buy volume. The study was conducted with securities that had at least 10 trading days in 1992, the research team collected 1169 securities in 254 trading days. The measures QSPR, PQSPR, DEP, ESPR, PESPR were calculated for each trading day according to the stock code and then applied

formula for calculating rate of change: DL ୲

=Previous Next

(L t are the factors QSDR, PQSPR, respectively)

DEP, ESPR, PESPR). DL t is taken as absolute value and averaged to get representative results for 1992 for each stock. This study has overcome the shortcomings of Amihud and Mendelson's (1986) measurement, but the study is limited in time, and does not show the comprehensiveness of the US stock market. The results of this study indicate that asymmetric information and transaction costs have an impact on TKCCP. If the stock has good liquidity, transaction costs will be lower, the difference between the bid price and the offer price will be small. On the contrary, average transaction costs will increase for stocks with insider information or information asymmetry causing TKCCP to decrease.

Harris (2003, p.421) mentioned liquidity as an important function of an efficient market. Liquidity is defined as the ability to quickly trade a large amount of shares at low cost. This study emphasizes the cost of stock transactions. Because when trading stocks, the costs incurred are classified as: explicit costs, implicit costs and missed trade opportunity costs. The explicit costs incurred when the transaction is carried out include: brokerage costs, costs paid to securities companies, income tax... In addition, investors will incur additional costs of the difference between bid and ask prices (investors buy at the offer price and sell at the bid price) and price impact costs (because when buying at

Large volume pushes the price up and vice versa, large volume sells push the price down. This expense arises when the stock is illiquid.

In agreement with (Admati and Pfleiderer, 1988), in Dalgaard's (2009) study, it is stated that: Liquidity is the ease of buying and selling assets without reducing the price and without paying transaction fees. Asset liquidity will affect the future cash flows of investors and all these factors will affect the price of the asset. Expensive transaction costs and the possibility of future price reduction are identified as costs arising from lack of liquidity. With this study, Dalgaard (2009) proposed some measures for TKCCP: the difference between the bid and ask prices, the sensitivity of price to trading volume, and the turnover ratio. The study also showed that the relationship between TKCCP and stock returns is positive. Another study conducted on the German stock market by (Gruning, 2010) also agreed on the use of the difference between the bid and ask prices as a measure of TKCCP Spread - the relative price difference is determined as follows:

Spread =

askprice − bidprice 2 ∗ closingprice

With ask price - asking price, bid price - buying price, closing price - closing price, these prices are determined for each trading day and are averaged by day to represent each stock code. Based on data of 600 enterprises listed on the German Stock Exchange in 2006, the author studies the relationship between liquidity, market value, income, and market share of enterprises that will be changed when information is announced. Using the multivariate regression analysis method (cross-sectional data) with a significance level of 1% shows the inverse impact between the quality of information published through financial statements in 2005 on TKCCP (measured by the difference between the bid price and the selling price). That is, the higher the quality of information disclosure, the lower the gap between the bid price and the selling price, or in other words, the quality of information disclosure of enterprises has a positive impact on TKCCP.

These studies identify another characteristic of liquidity as the loss or cost of selling a security. The lower the spread between the bid and ask prices, the more liquid the stock is.

The ease of trading of stocks is also reflected in their trading value and trading volume on the market. Stocks with high value and trading volume show that the stocks attract the attention of investors on the market.

Market liquidity is expressed by the ease of trading. Value and trading volume are used as measures of liquidity from different research perspectives and are relatively popular in studies such as (Chordia et al., 2001b; Lakhal, 2008; Gopalan et al., 2010; Gruning, 2010) and recent studies such as (Leirvik et al., 2017); (Qiao and Pukthuanthong, 2018), high or low trading volume shows the investment demand of those stocks. Increased trading volume can also be understood that the price of that stock is tending to increase and vice versa. In the study of (Chordia et al., 2000; Chordia et al., 2001b) using trading volume as a measure of TKCCP with Q A being the offer volume and Q B being the bid volume, the formula is determined as follows:

Depth = 2 (Q ୅

− Q ୆ )

The study found that the relationship between trading volume is influenced by both formal and informal information flows and that investors with an advantage in corporate information have a larger trading volume. Datar et al. (1998) also used trading volume but from a different perspective:

Stock turnover ratio ( TO ୧ ୲

VOL ୧ ୲

) =

୧୲

With VOL it is the total trading volume of each stock in the year and N it is the number of outstanding shares in the year. TO (turnover rate) represents the total number of shares traded daily in a year divided by the number of shares outstanding in that year. TO indicates the frequency of trading of stocks in the year or the number of times the ownership of a stock changes during the year. The larger the TO, the higher the TKCCP. The study also shows that the relationship between liquidity and stock investment returns is positive with the control variables of the model such as enterprise size, beta coefficient and book value.

Thus, trading volume represents the demand for stocks in the market. Stocks are bought and sold quickly with large volumes, the market always has buyers and sellers available, which helps reduce transaction time and costs. Large trading volume with unchanged prices also means that stocks have high liquidity.

Lawrence's (1990) study followed that of (Black, 1971) and considered liquidity as a multidimensional concept expressed through attributes such as: breadth, depth, time and the ability of stocks to recover from shocks. These characteristics are expressed in Liu's (2006) study, which defines liquidity as

the ability to trade quickly, with little price impact and low transaction costs. The measure is defined as follows:

𝐿𝑀 = ቎𝑁𝑜𝑍𝑉

ଵ

+ ௧௨௥௡௢௩௘௥ ೔ೣ቏ ∗ 21_𝑥

௜௫ ௜,௫ିଵ

𝐷𝑒𝑓𝑙𝑎𝑡𝑜𝑟 𝑁𝑜𝑇𝐷 ௫

With: turnover = stock turnover ratio; NoTD (Number of trading daily): total number of days the stock has transactions in month x; NoZV (number of zero daily volumes): number of days with no transactions in month x-1; Deflator is determined by number x.

The higher the LM index, the lower the liquidity of the stock and vice versa. LM focuses specifically on the speed of transactions but also shows many aspects of liquidity. The number of days without transactions is low, along with the frequency of transactions, and the large volume of transactions in a year will make the LM index low or the TKCCP higher. This indicator synthesizes many aspects of liquidity but does not consider the aspect of how the stock price will change when the transaction volume changes.

Following the studies of (Copeland and Galai, 1983; Kyle, 1985; Glosten and Harris, 1988; Hasbrouck, 1991), Amihud (2002) proposed a measure of TKCCP based on the ratio of price change to daily transaction value, the measure is calculated as follows:

ୈ ౟౯

Illiquidity ୧୷

(ILLIQ ୧ ୷ ) =

୧୷

To R

VOLD

෍

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Where, D iy is the number of stock transactions per day in a year R iyd is the daily return of the stock

VOLD ivyd daily trading value ($ million)

This measure shows the relationship between the stock return on the stock trading value. In this measure, the return and trading value are collected daily over a long period of time, so it is highly representative and can be collected across markets. This measure is more suitable for studies on TKCCP when using time series data. The smaller this index is, the less significant the change in stock price is when there is a large trading value in a short period of time. With the price factor measure, Amihud (2002) used daily and monthly data of stocks listed on the NYSE during the period 1963 - 1997 collected from the CRSP database, performing linear regression tests with cross-sectional data and time series data for monthly investment returns, respectively.

The measure of stock illiquidity according to Amihud (2002) has been used by many studies and from different perspectives. With the measure of stock liquidity according to (Amihud, 2002), Bekaert et al. (2007) demonstrated a positive relationship between TKCCP and investment returns especially in emerging stock markets. In addition, the study of Cheung et al. (2014) examined the impact of TKCCP on the value of enterprises and corporate governance activities of real estate companies in the US stock market. The author uses the measure of TKCCP based on the study of (Amihud, 2002) with the following modifications:

𝑎𝑚𝑖ℎ𝑢𝑑 ௜ ௧

𝐷

= log(1 +

௜௧

஽ ೔೟

| 𝑅 ௜ௗ௧ |

௜ௗ௧

෍ 𝐷𝑉𝑜𝑙 )

ௗୀଵ

In which, D it : number of stock transactions per day in a year R idt : Daily return rate of stock

Dvol idt : Daily transaction value (million USD)

This measure shows the relationship between the yield on the value of shares traded. The research results show that there is a positive relationship between TKCCP and the value of the enterprise, especially for enterprises with good corporate governance activities with the participation of institutional investors. This research result is consistent with the research of Maug (1998) which demonstrated that stocks with good liquidity will help corporate governance activities more effectively.

In short, the asymmetric information between investor groups in the market causes the lack of liquidity of stocks and that is one of the reasons why the stock market is imperfect. Stock liquidity is a quantity that cannot be directly observed but must be estimated based on liquidity characteristics. Many liquidity measures have been studied and applied in the stock markets of countries. These measures represent liquidity aspects and are classified into: single-dimensional measures and multi-dimensional measures. However, up to now, no measure has fully reflected all liquidity characteristics. However, based on the theoretical and empirical research of scientists around the world , the ILLIQ it measure of Amihud (2002) is considered suitable and covers most of the characteristics of TKCCP (Aitken and Comerton-Forde, 2003; Goyenko et al. , 2009; Lou and Shu, 2014). In addition, Liu (2006) built the LM it measure based on the multidimensional concept of liquidity (Lawrence, 1990). This measure has the advantage of focusing on transaction speed and showing the continuity of activities.

Factors affecting the liquidity of stocks listed on the Vietnamese stock market - 4

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