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<front>
<journal-meta>
<journal-id>2518-4431</journal-id>
<journal-title><![CDATA[Investigación & Desarrollo]]></journal-title>
<abbrev-journal-title><![CDATA[Inv. y Des.]]></abbrev-journal-title>
<issn>2518-4431</issn>
<publisher>
<publisher-name><![CDATA[UNIVERSIDAD PRIVADA BOLIVIANA]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2518-44312020000200004</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[LIQUIDITY RISK AND STOCK RETURN IN LATIN AMERICAN EMERGING MARKETS]]></article-title>
<article-title xml:lang="es"><![CDATA[RIESGO DE LIQUIDEZ Y RENTABILIDAD DE LAS ACCIONES EN LOS MERCADOS EMERGENTES DE AMÉRICA LATINA]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vasquez-Tejos]]></surname>
<given-names><![CDATA[Francisco Javier]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lamothe Fernandez]]></surname>
<given-names><![CDATA[Prosper]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Universidad Mayor de Chile Escuela de Negocios ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Chile</country>
</aff>
<aff id="A02">
<institution><![CDATA[,Universidad Autónoma de Madrid Departamento de Financiación e Investigación Comercial ]]></institution>
<addr-line><![CDATA[Madrid ]]></addr-line>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2020</year>
</pub-date>
<volume>20</volume>
<numero>2</numero>
<fpage>57</fpage>
<lpage>74</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.bo/scielo.php?script=sci_arttext&amp;pid=S2518-44312020000200004&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.bo/scielo.php?script=sci_abstract&amp;pid=S2518-44312020000200004&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.bo/scielo.php?script=sci_pdf&amp;pid=S2518-44312020000200004&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[This study analyzes the impact of liquidity risk on stock returns in four Latin American markets (Chile, Columbia, Mexico, and Peru) between January 1998 and July 2018. Several previous studies have focused on measuring this effect in developed markets and a few in emerging markets, such as Latin American stock markets. In the present study, five liquidity risk measures with a multiple regression model; three have been widely used in previous studies and two were from recently proposed measures. We found evidence of an inverse relationship between liquidity risk and stock performance, which indicates that there exist rewards for investing in less liquid positions and therefore originate new investment strategies. In general, lesser developed or smaller markets have a disadvantage for this type of study, due to lack of access to historical information on stock purchase and sales.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Este estudio analiza el impacto del riesgo de liquidez y la rentabilidad de las acciones en cuatro mercados latinoamericanos (Chile, Colombia, México y Perú), entre enero de 1998 y julio de 2018. Varios estudios anteriores se han centrado en la medición de este efecto en los mercados desarrollados y unos pocos en los mercados emergentes, como lo son mercados de valores de América Latina. En el presente estudio se utiliza un modelo de regresión, el cual incorpora cinco medidas de riesgo de liquidez; tres se han utilizado ampliamente en estudios anteriores y dos proceden de medidas propuestas recientemente. Se encontraron pruebas de una relación inversa entre el riesgo de liquidez y el rendimiento de las acciones, lo que indica que existen recompensas por invertir en posiciones menos líquidas y por tanto originar nuevas estrategias de inversión. En general, los mercados menos desarrollados o más pequeños tienen una desventaja para este tipo de estudio, debido a la falta de acceso a la información histórica sobre la compra y venta de acciones.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Liquidity Risk]]></kwd>
<kwd lng="en"><![CDATA[Stock Returns]]></kwd>
<kwd lng="en"><![CDATA[Emerging Markets]]></kwd>
<kwd lng="en"><![CDATA[Latin America]]></kwd>
<kwd lng="en"><![CDATA[Liquidity Risk Measurements]]></kwd>
<kwd lng="es"><![CDATA[Riesgo de Liquidez]]></kwd>
<kwd lng="es"><![CDATA[Rentabilidad de las Acciones]]></kwd>
<kwd lng="es"><![CDATA[Mercados Emergentes]]></kwd>
<kwd lng="es"><![CDATA[América Latina]]></kwd>
<kwd lng="es"><![CDATA[Medidas del Riesgo de Liquidez]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p align=left><font color="#800000" size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>DOI:</b> 10.23881/idupbo.020.2-4e</font></p>     <p align=right><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>ART&Iacute;CULOS - ECONOM&Iacute;A, EMPRESA Y SOCIEDAD</b></font></p>     <p align=right>&nbsp;</p>     <p align=center><font size="4" face="Verdana, Arial, Helvetica, sans-serif"><b>LIQUIDITY RISK AND STOCK RETURN IN LATIN AMERICAN EMERGING   MARKETS</b></font></p>     <p align=center>&nbsp;</p>     <p align=center><font size="3" face="Verdana, Arial, Helvetica, sans-serif"><b>RIESGO   DE LIQUIDEZ Y RENTABILIDAD DE LAS ACCIONES EN LOS MERCADOS EMERGENTES DE   AM&Eacute;RICA LATINA</b></font></p>     <p align=center>&nbsp;</p>     <p align=center>&nbsp;</p>     <p align=center><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>Francisco   Javier Vasquez-Tejos<sup>1</sup> y     Prosper Lamothe Fernandez<sup>2</sup></b></font></p>     <p align=center><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><sup>1</sup><i>Escuela de Negocios, Universidad Mayor de Chile</i></font>    ]]></body>
<body><![CDATA[<br>   <font size="2" face="Verdana, Arial, Helvetica, sans-serif"><sup>2</sup><i>Departamento de Financiaci&oacute;n e Investigaci&oacute;n Comercial, Universidad Aut&oacute;noma de Madrid</i></font></p>     <p align=center><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><a href="mailto:francisco.vasquez@umayor.cl">francisco.vasquez@umayor.cl</a></font></p>     <p align="center"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">(Recibido   el 14 de septiembre 2020, aceptado para publicaci&oacute;n el 26 de noviembre 2020) </font></p>     <p align="center">&nbsp;</p>     <p align="center">&nbsp;</p> <hr align="JUSTIFY" noshade>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>ABSTRACT</b></font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">This   study analyzes the impact of liquidity risk on stock returns in four Latin   American markets (Chile, Columbia, Mexico, and Peru) between January 1998 and   July 2018. Several previous studies have focused on measuring this effect in   developed markets and a few in emerging markets, such   as Latin American stock markets. In the present study, five liquidity risk   measures with a multiple regression model; three have been widely used in   previous studies and two were from recently proposed measures. We found evidence of an inverse relationship between liquidity risk   and stock performance, which indicates that there exist rewards for investing in less liquid positions and therefore originate new investment   strategies. In general,   lesser developed or smaller markets have a   disadvantage for this type of study, due to lack of access to historical   information on stock purchase and sales.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>Keywords:</b> Liquidity Risk, Stock Returns, Emerging Markets, Latin   America, Liquidity Risk Measurements. </font></p> <hr align="JUSTIFY" noshade> <font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>RESUMEN</b></font>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Este   estudio analiza el impacto del riesgo de liquidez y la rentabilidad de las   acciones en cuatro mercados latinoamericanos (Chile, Colombia, M&eacute;xico y Per&uacute;),   entre enero de 1998 y julio de 2018. Varios estudios anteriores se han centrado   en la medici&oacute;n de este efecto en los mercados   desarrollados y unos pocos en los mercados emergentes, como lo son mercados de   valores de Am&eacute;rica Latina. En el presente estudio se utiliza un modelo de regresi&oacute;n, el cual incorpora cinco medidas de   riesgo de liquidez; tres se han utilizado ampliamente   en estudios anteriores y dos proceden de medidas propuestas recientemente. Se   encontraron pruebas de una relaci&oacute;n inversa entre el riesgo de liquidez y el   rendimiento de las acciones, lo que indica que existen recompensas por invertir en posiciones menos l&iacute;quidas y por tanto originar nuevas estrategias de inversi&oacute;n. En general, los   mercados menos desarrollados o m&aacute;s peque&ntilde;os tienen una desventaja para este   tipo de estudio, debido a la falta de acceso a la informaci&oacute;n hist&oacute;rica sobre la compra y venta de acciones.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>Palabras   Clave:</b> Riesgo de Liquidez, Rentabilidad de las Acciones, Mercados Emergentes, Am&eacute;rica Latina, Medidas del Riesgo de Liquidez.</font></p> <hr align="JUSTIFY" noshade>     ]]></body>
<body><![CDATA[<p align="justify">&nbsp;</p>     <p align="justify">&nbsp;</p>     <p align="justify"><font size="3" face="Verdana, Arial, Helvetica, sans-serif"><b>1.   INTRODUCTION</b></font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Liquidity risk has become an important   element for investors since it allows them to assess the speed with which an   investment can be offered to the market and convert into cash, as well as the   cost associated with accelerating this transition. The first liquid market concepts were introduced by Black [1], who indicated that a stock market should   contain constant supply and demand of shares, minor differences in the range of   prices (Bid-ask spreads), and sale and/or purchase of large   quantities of shares with a low impact on the price. Another specification of a liquid market was given by Kyle [2], who maintains that the market must be in a constant   equilibrium of auctions, which must contain the possibility of taking and   closing positions in a short time, market depth and price resilience.   Subsequently, based on the seminal article by Amihud and Mendelson [3] on the relationship between stock return and liquidity   risk, several studies were initiated in developed   markets on this subject, and more recently in emerging markets as well. The importance for investors of a liquid market has become   more relevant since the crisis of 2008, since these markets present a necessary   condition for efficiency [4].</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Financial   and liquidity risks are defined respectively as losses produced by adverse   movements in market prices, and as the cost or inopportunity of undoing a position [5].   Three other definitions of liquidity risk can be highlighted: i) the ability to   convert shares into cash (or vice versa) with the lowest transaction cost [6]. ii)   the impossibility of being able to undo a position or investment at a   competitive market price and with sufficient speed   after the decision was made [7].   iii) the risk involved when selling the assets to   meet financial obligations, which are minor and may be caused by various   factors, such as the ability to make certain assets liquid or turn them into   cash, delays in the sale process or having to accept prices below the market value of said assets [8].</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">On   the other hand, six factors are identified that influence   the liquidity of shares [9]:   transaction costs, asymmetric information, demand, financial market   development, investment horizon, and dividend payment date. Many of these factors leave their mark on historical   transaction data, such as return, volume, number of businesses, and transaction   days. Historical transaction data is easier to obtain in emerging markets,   which is why this study focuses on them.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Therefore, the questions posed by this study (hypothesis) are the   following: Do the different liquidity risk indicators measure   their relationship with the return of shares the same way in different Latin   American countries? What is the relationship between liquidity and return?</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">This   investigation is organized as follows: in section 2, there is a bibliographic   review including emerging and developed markets; in section 3, the data and   methodology; in section 4, the results; and finally, in section 5, the conclusions.</font></p>     <p align="justify">&nbsp;</p>     <p align="justify"><font size="3" face="Verdana, Arial, Helvetica, sans-serif"><b>2.   BIBLIOGRAPHIC REVIEW</b></font></p>     ]]></body>
<body><![CDATA[<p align="justify"><b><font size="2" face="Verdana, Arial, Helvetica, sans-serif">2.1   Studies focused on an emerging market from a single   country</font></b></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Using the liquidity adjusted capital   asset pricing model (LCAPM) developed by Acharya and Pederson [10] in the Portuguese market, authors Miralles, Miralles, and   Oliveira [11] found evidence that the most liquid assets, such as those   with higher transaction levels, showed higher returns. The latter is contrary   to evidence that has been found in other markets, i.e., a negative liquidity risk premium. In the Jordanian market, a study by   Bataineh, Mohamad Ali and Hanna Alrabadi [12] found that the Amihud illiquidity measure [13] and the turnover ratio proposed by Datar, Naik, and Radcliffe [14] are the methods that produce the best results and provide evidence of an effect of liquidity on shareholder   returns.Another study   by Leirvik, Fiskerstrand, &amp; Fjellvikas [15] found   no evidence of a relationship between stock returns and liquidity in the   Norwegian market. The authors used three liquidity measures, including the turnover rate, and none yielded significant   results.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">A study of the Indian market in the year   2016 on trading activity and liquidity risk concluded that there is a liquidity   risk premium in the Indian stock market [16].</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Studies performed on the Chilean market   have found evidence of a positive relationship between liquidity risk and stock   returns in the period from 2000-2008 [17] and during the period from 2000-2018 [18].</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>2.2   Studies that focus on   emerging markets in a group of countries</b></font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The   work of Gniadkowska-Szyma&#324;ska [9] uses a methodology similar to what was described by Datar,   Naik, and Radcliffe [14], but modified for emerging markets, using monthly returns   from companies listed on the Polish and Baltic stock exchanges between the   periods of January 2006 and October 2015, and found significance between the   number of transactions and stock returns, but not   with the turnover   ratio. In another study of the seven emerging   markets of Argentina, Brazil, Indonesia, Mexico, Russia, South Korea, and   Thailand, Levy Yeyati, Schmukler, &amp; Van Horen [19] used Amihud ratio indices, bid-ask spread, and weekly   volume logarithms to study liquidity in two periods,   pre- and post-crisis from 1994-2004. The methodology used was twofold. First,   they compared their pre- and post-crisis deviations and then an econometric   analysis was performed. The authors concluded that the discouragements of the market are positively correlated with volume and   negatively correlated with transaction costs. There is also a strong   relationship between liquidity measures and periods of crisis, and no evidence   was found of market paralysis with the onset of the crisis. Another study to consider was performed on stock markets in Croatia,   Slovenia, Hungary, Serbia, Bulgaria, Poland and Germany, in which two groups of   liquidity measures were used: one-dimensional (Size of the firm-related liquidity   measures, volume-related liquidity measures,   time-related liquidity measures, and spread-related liquidity measures) and multi-dimensional (Amivest ratio and Amihud&rsquo;s illiquidity   ratio, ILLIQ). This study   found that the countries of Germany, Poland, and Hungary had a high level of liquidity, while Croatia, Slovenia, Serbia, and   Bulgaria had a high level of illiquidity compared with the first group. They   conclude that the Amihud Illiquidity (ILLIQ)   is not an appropriate measure for emerging markets [20]. They also consider that   liquidity is impossible to capture with a single index, given its   multi-dimensional characteristics. The study by Vidovi&#263;, Poklepovi&#263;, &amp;   Aljinovi&#263; [21] tested two measures of illiquidity in emerging markets of   Europe, in addition to a new proposed measure, Relative Change in Volume (RCV), which used 12 continuously   listed shares in seven markets (Poland, Czech Republic, Hungary, Bulgaria,   Romania, Croatia, and Germany). They found that the ILLIQ and Turnover measures   are not appropriate since the return of these shares   did not increase with rises in illiquidity.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"> The study by Bekaert, Harvey &amp;   Lundblad [22], which considers 18 emerging   markets, including 5 Latin American markets (Argentina, Brazil, Chile,   Colombia, and Mexico), concludes that the Zero Rate Return (ZRR) Index as a   monthly ratio, is a good predictor of profitability. In addition, the ZRR index   is negatively related to turnover. They find that the   ZRR measure captures an aspect of liquidity that is not present in turnover.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The work of Perobelli, Fam&aacute;, &amp; Sacramento [23], found a positive relationship between market risk and   turnover, this along other results indicates a negative premium for market   liquidity in the Brazilian market</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Ahn, Cai, &amp; Yang [24] studied 21 emerging markets, including 6 Latin American   markets (Argentina, Brazil, Chile, Mexico, Peru, and Venezuela). They used two   groups of liquidity indices: one with a spread and the other with a price   impact. The latter used the ILLIQ indices, Amivest   and the Pastor index proposed by Pastor and Stambaugh [25]. The results show that these three indices are close   substitutes and that the ILLIQ index is the most effective in some cases.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>2.3   Studies focused on developed   markets</b></font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Several classic studies show that   liquidity risk is a factor in stock returns [26], [14], [25].   In a study on the liquidity of the German market from 2006-2010, in which   Amihud's ILLIQ index was used, as well as a study based on the prices of quoted   funds, it was concluded that periods of illiquidity were compensated with   returns, as also confirmed by the relationship   between illiquidity and market return [27].</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Between 2006-2014, a study using the   LCAPM methodology proposed by Acharya &amp; Pedersen [10], which considered a sample of more than 2500 shares listed   on NASDAQ, concluded that liquidity risk and liquidity level are not always positively correlated. A negative   relationship was also found between return and market illiquidity [28]. Another study based on the Japanese market between 1983   and 2016, which analyzed the LCAPM using different illiquidity proxies: Amihud's ILLIQ, the turnover ratio and &quot;y&quot; developed by Pastor and Stambaugh [25], concludes that the results support the use of LCAPM and   that, to a certain extent, liquidity risk is quoted on the Tokyo Stock Exchange [29].A study of the Chinese market performed from 1995-2016   shows that market liquidity and trading activity increase over time [30]. </font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Among the recent studies in developed   markets that found evidence of a relationship between   return and liquidity risk on 7 developed markets (USA, Japan, Canada, France,   Germany, Italy, and United Kingdom), liquidity risk, and abnormal returns [31].</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Studies   of the North American market for shares listed on the   FTSE 100 Index from 2005-2007 found a relationship between the frictions of   liquidity risk and share returns [32]. Of shares listed on the New York Stock Exchange from   1993-2005, those who used a new index that even exceeds Amihud&rsquo;s ILLIQ also   showed evidence of a relationship between return and   liquidity risk [33].Finally, a study on a group of 45 international markets,   19 emerging markets, and 26 developed markets over a period   of 22 years, found that the premium for illiquidity is higher in emerging   markets than in developed markets, concluding a positive significance of return   on liquidity premium in international markets [34].</font></p>     <p align="justify">&nbsp;</p>     <p align="justify"><font size="3" face="Verdana, Arial, Helvetica, sans-serif"><b>3. DATA AND METHODOLOGY</b></font></p>     <p align="justify"><b><font size="2" face="Verdana, Arial, Helvetica, sans-serif">3.1 Sample construction</font></b></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">This   data was obtained from Economatica and considered   shares that had an average presence equal to or greater than 70% from July 1998   to July 2018 in the stock markets of Chile, Mexico, and Peru. For Colombia, the   period from August 2002 to July 2018 was considered. Monthly statistics were obtained from this data and are summarized in <a href="#t1">tables 1</a> and <a href="#t2">2</a>.   From these shares, the variables of daily closing price, volume, number of   businesses, number of daily securities traded, and number of shares   outstanding were selected.</font></p>     <p align="center"><a name="t1"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_01.gif" width="489" height="162"></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">We chose a total amount of 96   stocks, which met the stock market presence requirements of at least 70% during   the analysis period of this investigation.</font></p>     ]]></body>
<body><![CDATA[<p align="center"><a name="t2"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_02.gif" width="772" height="954"></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><b>3.2 Liquidity Measures</b></font></p> <table width="100%" border="0" cellpadding="0">   <tr>     <td width="2%" valign="top"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">(1)</font></td>     <td width="98%"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">There are countless liquidity measures   that have appeared in the literature over the past 30 years. They can be   separated into three main groups: transaction cost, trading activity and price   impact. One of the classifications of liquidity indices is proposed by Aitken and Comerton-Forde [6], who separate the indices into two groups: one based on trading activity and the other on transaction orders   .This research was based on measures constructed with transaction data, since   good quality price range data was difficult to find or unavailable for emerging   markets. Four widely used measures were analyzed as   well as two that were recently proposed by V&aacute;squez, Pape, and Ireta [18]:Turnover Ratio, proposed by Datar, Naik, and Radcliffe [14], corresponds to an index that estimates the value of the   shares traded, divided by the market capitalization value for the period   analyzed. It is also known as asset rotation.</font></td>   </tr>   <tr>     <td valign="top"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">(2)</font></td>     <td>    <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Amihud&rsquo;s measure of illiquidity (ILLIQ) [35] is a measure of approximation to liquidity that represents       the price variation of a traded currency unit. The illiquidity ratio of an       asset <i>i</i> in month <i>t</i> can be calculated:</font></p>           <p align="center"><img src="/img/revistas/riyd/v20n2/a04_ecuacion_01.gif" width="706" height="66"></p>           <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">where <i>R<sub>itd</sub></i> and <i>V<sub>itd</sub></i> are the return and trading volume of         asset i on day d of month t respectively, and <i>D<sub>it</sub></i> is the number of days the share is         negotiated within month <i>t</i>.         This index or measure is multiplied by 10<sup>6</sup>. The economic significance of this measure is based on the         fact that an asset is illiquid and therefore its measure reaches a high value         if the price of the the asset experiences a high fluctuation in response to a     reduced volume [36].</font></p></td>   </tr>   <tr>     <td valign="top"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">(3)</font></td>     <td>    <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The illiquidity ratio by turnover ratio       proposed by V&aacute;squez, Pape and Ireta [18], represents the absolute return of the price produced by a turnover ratio percentage. The       illiquidity ratio of an asset <i>i</i> in month t can be calculated:</font></p>           <p align=center><img src="/img/revistas/riyd/v20n2/a04_ecuacion_02.gif" width="707" height="51"></p>           <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">where <i>R<sub>itd</sub></i> and <i>TRN<sub>itd</sub></i> are         the return and turnover ratio of asset <i>i</i> on         day d of month <i>t</i> respectively,         and <i>D<sub>it</sub></i> is         the number of days the share is negotiated within month <i>t</i>. In         other words, the higher the ratio, the less liquid the asset must be, since a         change in the TRN results in a greater change in return. This proposal is based         on the measure proposed by Amihud [13] and         the conclusion of the Gniadkowska-Szymansca [9]         study that the turnover measure does not affect         return in the Polish market.</font></p>           <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The         illiquidity ratio for the number of businesses (<i>NN</i>)         proposed by V&aacute;squez, Pape and Ireta [18],         represents the absolute return of the price it produces for a business (a         transaction). The illiquidity ratio of an asset <i>i</i> in         month t can be calculated:</font></p>           <p align=center><img src="/img/revistas/riyd/v20n2/a04_ecuacion_03.gif" width="708" height="49"></p>           ]]></body>
<body><![CDATA[<p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">where <i>R<sub>itd</sub></i> and <i>NN<sub>itd</sub></i>  are the return and the number of businesses         of asset <i>i</i> on day d of month <i>t</i>, respectively, and <i> D<sub>it</sub></i> is the number of days the share is         negotiated within month t. In other words, the higher the ratio, the less         liquid the asset must be, since a change in the number of businesses results in         a greater change in returns. This index or measure was multiplied by 10<sup>3</sup>. This proposal is based on the measure proposed by Amihud         Y [13] and the conclusion of the Gniadkowska-Szyma&#324;sca [9] study, which         indicates that the number of transactions in Baltic markets and share returns     are statistically significant.</font></p></td>   </tr>   <tr>     <td valign="top"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">(4)</font></td>     <td><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The ZRR was initially introduced by   Lesmond, Ogden, and Trzcinka [37] and in our study, we estimated it as the number of days with zero return divided by the number of days with a transaction during the period.</font></td>   </tr> </table>     <p align="justify"><b><font size="2" face="Verdana, Arial, Helvetica, sans-serif">3.3 Methodology</font></b></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">This   study was descriptive, correlational, non-experimental, and longitudinal,   because it considered data from July 1998 to July 2018 for Chile, Mexico, and   Peru, and from August 2002 to July 2018 for Colombia. The observation variables   were the monthly yields of the shares traded on the   main stock exchanges of Chile, Colombia, Mexico, and Peru and their liquidity   measures.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The   shares are grouped into   three portfolios from higher to lower average returns over the period (<a href="#t3">table   3</a>), with the aim of determining the differences in   the impact of liquidity at different levels of return. To achieve this   objective, the study focused on Portfolio 1 with the highest returns and on   Portfolio 3 with the lowest returns. For the selected portfolios, monthly statistics were estimated and monthly liquidity risk indicators   were constructed from the indices in the previous section. Portfolios 2 with   medium profitability will not be included in the final analysis so as to check   the relationship of a portfolio with a high and   another with low profitability with liquidity risk. Portfolios 1 and 2 will be   made up of 13, 3, 10, and 6 shares respectively for Chile, Colombia, Mexico,   and Peru.</font></p>     <p align="center"><a name="t3"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_03.gif" width="393" height="998"></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The objective of this   study was to determine whether or not there is a relationship between the   liquidity and stock return of the companies listed in these four Latin American   stock markets. According to the available data, a regression model following the methodology of Leirvik, Fiskerstrand, &amp; Fjellvikas [15], who uses this model   to evaluate the relationship between equity profitability and liquidity risk in   Norway, an economy that, despite being developed in size, is very similar to   the Latin American ones. The model contained a dependent   variable that represented the share return and two independent variables: the   monthly return of the market portfolio and the liquidity indicator.</font></p>     <p align=center><img src="/img/revistas/riyd/v20n2/a04_ecuacion_04.gif" width="742" height="36"></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">where <i>r<sub>i,t</sub></i> is   the monthly return of month t of action <i>i</i>, <i>&beta;<sub>1</sub></i> is   the beta of market return, <i>r<sub>m,t</sub></i> is   the return of the market in month <i>t</i>, <i>&beta;<sub>2</sub></i> is   the beta of the liquidity index, <i>LIQ<sub>i,t</sub></i> is   the liquidity index of asset <i>i</i> in   the month <i>t</i> and <i>&epsilon;</i> is   the error of the model. We used a stock index representative of each country as   a proxy for market return; IPSA for Chile, COLPAP for Colombia, MEXBOL   for Mexico and SPBLPGPT for Peru.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">Several tests will be carried out for these   types of regression models, presenting the results in   the results tables. Amongst them to assess the specification of the model,   heteroscedasticity, self-relationship, normality of errors, among others.</font></p>     <p align="justify">&nbsp;</p>     ]]></body>
<body><![CDATA[<p align="justify"><font size="3" face="Verdana, Arial, Helvetica, sans-serif"><b>4. RESULTS</b></font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><a href="#t4">Table   4</a> describes the monthly statistics for the different variables. <a href="#t5">Tables 5</a>, <a href="#t6">6</a>, <a href="#t7">7</a>  and <a href="#t8">8</a> show a good fit for all of the models, the generally high R2s, most of   the Durbin-Watson statistic close to 2, all &quot;F&quot; tests were   significant and the condition indices were less than   30; the latter indicated that there were no autocorrelation or   multicollinearity problems. The above represents a good overall fit of the   models.</font></p>     <p align="center"><a name="t4"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_04.gif" width="632" height="1254"></p>     <p align="center"></p>     <p align="center"><a name="t5"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_05.gif" width="1157" height="571"></p>     <p align="center"></p>     <p align="center"><a name="t6"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_06.gif" width="1149" height="578"></p>     <p align="center"></p>     <p align="center"><a name="t7"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_07.gif" width="1165" height="587"></p>     <p align="center"></p>     ]]></body>
<body><![CDATA[<p align="center"><a name="t8"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_08.gif" width="1162" height="598"></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The results of the Ramsey reset test show that, in general,   the models are well specified, except for Portfolio 1 in Mexico and Peru. No   autocorrelation is seen in the models using the Durbin Watson and   Breusch-Godfrey tests, except for Mexico in portfolio   3. Several models showed the presence of heteroscedasticity, which is corrected   with White's adjustment (major errors) shown in <a href="#t9">Table 9</a>. We also carried out normality tests of the errors with the Shapiro-Wilk test.</font></p>     <p align=center><a name="t9"></a><img src="/img/revistas/riyd/v20n2/a04_tabla_09.gif" width="1142" height="1206"></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif"><a href="#t5">Table 5</a> and <a href="#t9">9</a> demonstrates that in the case of Chile, the   turnover (TRN) was not significant for portfolio 1 and 3, whereas for both portfolios, the   beta of ILLITRN were negative and significant at 99% and 95%, respectively.   This is consistent with the inverse expected relationship between return and   liquidity risk. In the case of the ILLIQ is only   significant in portfolio 3, while for portfolio 1, the ILLIQNN and ZR measures   were also significant.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">In the case of Colombia (<a href="#t7">Table 7</a>), the turnover was   positive and significant (portafolio 1), which indicates that the Colombian   market rewards greater liquidity of assets. The   ILLIQ, ILLIQTRN, ILLIQNN and ZR were not significant. These results may be   influenced by the low number of shares of each portfolio. The low number of   actions that met the requirements lead us to be cautious with these results.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">In   Mexico (<a href="#t7">Table 7</a>), almost all the indicators were not significant, except in the   most profitable portfolio, the ILLIQNN and ZR indices, which resulted in   negative and significant betas at 99% and 95%, respectively. This shows the   expected relationship between return and liquidity   risk.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The     <a href="#t8">Table 8</a> and <a href="#t9">9</a> shows the results for Peru. In the case of the most profitable   portfolio (1), the ILLIQNN and ZRR measures were negative and significant. In   the case of the least profitable portfolio, only the ZR index had not significant beta. This suggests that the Peruvian   market liquidity risk is relevant in the case of less profitable investments   (portfolios).</font></p>     <p align="justify">&nbsp;</p>     <p align="justify"><font size="3" face="Verdana, Arial, Helvetica, sans-serif"><b>5.   CONCLUSIONS</b></font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">This study analyzed the relationship of   liquidity risk on return in 96 shares of companies that trade on stock   exchanges in Latin America (Chile, Colombia, Mexico, and Peru) within the   period from January 1998 to July 2018. Five liquidity risk measures were used: three of which were widely used in previous studies   and two that were recently proposed. The results with the turnover ratio in   three out of four countries were not significant, with the exception of   Colombia, which is consistent with the conclusion of   Lesmond [38], that it is not a viable method for measuring liquidity in   emerging markets, and Zhao [39], that it does not efficiently measure liquidity in the   Chinese stock market. The foregoing is contrary to what Datar, Naik, &amp; Radcliffe [14] indicated, who found a negative relationship between   return and turnover. </font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The ILLIQ measure [13] does not present good   results, opposite to expectations due to the good results of this measure in   studies in other markets. In relation to the proposed ILLIQTRN and ILLIQNN   measures [18], the former was   significant in the lower-yielding portfolios in Chile   and Peru, it was also significant in Chile's high-profitability portfolio. The   second one (ILLIQNN) was significant in the high-yield portfolios of Chile,   Mexico, and Peru, and the low-yield portfolio of Peru.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The ZR measure turned   out to be significant in the Chilean, Mexico and   Peruvian portfolios in the most profitable portfolio. In both portfolios of   high and low profitability of Peru, this measure was significant. However, the   ZR did not show good results in the other countries under study.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">All the indices that   were statistically significant in Chile, Mexico, and Peru showed an inverse   relationship with return, which is consistent with the theory. In Colombia on   the other hand, a mostly direct relationship was observed, which indicates the need to perform new tests with a larger sample. </font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">The   new proposal by V&aacute;squez-Tejos et al., [18], ILLIQTRN and ILLIQNN, were the best performers. However,   in terms of which index best captures the relationship between return and   liquidity risk, the results of the present study are   consistent with [17] and [40], which indicate that liquidity is multidimensional, that   it can be measured by different indices, and that they will adapt differently   in markets with different microstructures. Therefore, this question will remain   open for future research. Considering that the ILLIQ   and ILLIQNN measures delivered statistically significant results in several   portfolios in different Latin American countries when applied to the Leirvik,   Fiskerstrand, and Fjellvikas model [15], we can conclude that liquidity risk has an impact on shareholder return in the Latin American market. The original   hypothesis is therefore accepted. This is consistent with other studies in   emerging markets where there is evidence that returns increase with liquidity   risk [12], [11]. In studies on developed markets, similar conclusions can   be found for the German market [28], the American NASDAQ [27], the Indian market [16], and in the market of the G7 countries [31]. A future line of research should construct a price range   using indicators with information from the stock supply and demand book. This study&rsquo;s limitations included restricted   access to databases of this type, so another option for future studies is to   analyze of the resilience of stock prices or portfolios as a proxy for   liquidity.</font></p>     <p align="justify">&nbsp;</p>     <p align="justify"><font size="3" face="Verdana, Arial, Helvetica, sans-serif"><b>6. BIBLIOGRAPHY</b></font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[1] F. Black, &ldquo;Toward a Fully Automated Stock Exchange,&rdquo; <i>Financ.   Anal. J.</i>, vol. 27, no. 4, pp. 28&ndash;35, 1971.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[2] A.   Kyle, &ldquo;Continuous auctions and insider trading,&rdquo; <i>Econometrica</i>, pp.   1315&ndash;1335, 1985.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[3] Y.   Amihud and H. Mendelson, &ldquo;Asset pricing and the   bid-ask spread,&rdquo; <i>J. financ. econ.</i>,   vol. 17, pp. 223&ndash;249, 1986.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[4] C. J.   Garcia, B. Herrero, and A. M. Ibanez, &ldquo;El papel de la liquidez en el efecto de   la nueva informacion. El caso del Latibex. (With English summary.),&rdquo; <i>Trimest. Econ.</i>, vol. 77, no.   3, pp. 651&ndash;682, 2010.</font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[5] J. I.   Pe&ntilde;a, <i>La Gesti&oacute;n de Riesgos Financieros de Mercado y Cr&eacute;dito</i>. Madrid,   2002.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[6] M.   Aitken and C. Comerton-Forde, &ldquo;How should liquidity be measured?,&rdquo; <i>Pacific     Basin Financ. J.</i>, vol. 11, no.   1, pp. 45&ndash;59, 2003.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[7] J. P.   Zorrilla Salgador, &ldquo;Globalizaci&oacute;n, incertidumbre y riesgo,&rdquo; <i>Intang. Cap.</i>, vol. 1, no. 3,   pp. 86&ndash;102, 2005.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[8] R.   Hern&aacute;ndez, &ldquo;Los riesgos de las entidades aseguradoras en el marco del   Enterprise Risk Management ( ERM ) y el control   interno Gesti&oacute;n Financiera y Globalizaci&oacute;n,&rdquo; <i>Innovar J.</i>, vol. 25, pp.   61&ndash;70, 2015.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[9] A.   Gniadkowska-Szyma&#324;ska, &ldquo;The impact of trading liquidity on the rate of return   on emerging markets: the example of Poland and the Baltic countries,&rdquo; <i>e-Finanse</i>, vol. 13, no.   4, pp. 136&ndash;148, 2017.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[10] V.   V. Acharya and L. H. Pedersen, &ldquo;Asset pricing with liquidity risk,&rdquo; <i>J.     financ. econ.</i>, vol. 77, no. 2, pp. 375&ndash;410, 2005.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[11] M.   del M. Miralles-Quir&oacute;s, J. L. Miralles-Quir&oacute;s, and C. Oliveira, &ldquo;The role of   liquidity in asset pricing: the special case of the   Portuguese Stock Market,&rdquo; <i>J. Econ. Financ.     Adm. Sci.</i>, vol. 22, no. 43, pp. 191&ndash;206, 2017.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[12] D.   W. Bataineh, Mohamad Ali; Hanna Alrabadi, &ldquo;he Effect of Liquidity Risk on Stock   Returns: The Case of Amman Stock Exchange during   (2004-2013),&rdquo; <i>Arab J. Adm.</i>,   vol. 37, no. 1, pp. 247&ndash;265, 2017.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[13] Y.   Amihud, &ldquo;Illiquidity and Stock Returns: Cross-Section and Time-Series Effects,&rdquo; <i>J. Financ. Mark.</i>, vol. 5, pp.   31&ndash;56, 2002.</font></p>     <p align="justify"><font size="2" face="Verdana, Arial, Helvetica, sans-serif">[14] V.   T. Datar, N. Y. Naik, and R. Radcliffe, &ldquo;Liquidity   and stock returns: An alternative test,&rdquo; <i>J.     Financ. Mark.</i>, vol. 1, no. 2, pp. 203&ndash;219, 1998.</font></p>     ]]></body>
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