Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/de-gruyter/stock-returns-and-liquidity-after-listing-switch-on-the-warsaw-stock-zesRuS14aU
References
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
- Publisher
- de Gruyter
- Copyright
- © 2022 Dorota Podedworna-Tarnowska et al., published by Sciendo
- eISSN
- 2450-0097
- DOI
- 10.18559/ebr.2022.4.6
- Publisher site
- See Article on Publisher Site
Abstract
Economics and Business Review, Vol. 8 (22), No. 4, 2022: 111-135 DOI: 10.18559/ebr.2022.4.6 Stock returns and liquidity ae ft r listing switch on the Warsaw Stock Exchange 2 3 Dorota Podedworna-Tarnowska , Daniel Kaszyński Abstract: e a Th im of the article is to evaluate the market reaction to the change of list - ing venue of companies moving from the alternative market to the regulated market of the Warsaw Stock Exchange. To do so, we investigated 71 switches, and their ee ff ct on market returns and liquidity. While the transfer itself creates a negative market reaction, the announcement of the transfer of a company and the institutional conr fi mation by the supervision of the company’s readiness for this transfer resulting from the approval of the prospectus creates positive market reactions. As a result of the transfer of com- panies there is an improvement in the liquidity of the shares. The empirical findings of the study could assist managers and investors in understanding the impact of stock ex- change migration on returns and the liquidity of shares in the shorter and longer term. Keywords: alternative market, main market, listing change, stock liquidity. JEL codes: G10, G14, G18, G30, G32. Introduction e Th re is a wide range of research findings in the finance literature related to the process of going public including theoretical and empirical studies indi- cating abnormally high returns obtained by investors during the Initial Public Oe ff r (i.e., the phenomenon of undervaluation in the short term) and on av - erage negative returns obtained by investors in the long term (i.e., overvalu- ation in the long term). These phenomena were analysed from the perspec - tive of a company’s direct debut on the stock exchange. In the authors’ opinion relatively little attention has been paid to companies that are already listed on Article received 25 October 2022, accepted 16 December 2022. Institute of Value Management, Axiology and Value Measurement Unit, SGH Warsaw School of Economics, al. Niepodległości 162, 02-554 Warszawa, Poland, corresponding author: dpoded@sgh.waw.pl, https://orcid.org/0000-0001-5945-403X. Institute of Econometrics, Decision Analysis and Support Unit, SGH Warsaw School of Economics, al. Niepodległości 162, 02-554 Warszawa, Poland, dkaszy@sgh.waw.pl, https://orcid. org/0000-0002-0865-0732. 112 Economics and Business Review, Vol. 8 (22), No. 4, 2022 an alternative market or a segment of the regular stock market designed for smaller companies and which then decided to change the place of quotation. Accordingly, an intriguing research issue in the presented perspective is the assessment of demand for the shares of such a company in the pre- and post- transfer period and its market valuation. It is essential to verify whether there is an investor-positive ee ff ct of the transfer to a regulated market meaning that investors achieve above-average returns, as it has been repeatedly demon- strated in many studies of companies debuting directly on regulated markets (e.g., Ritter, 1984; Ljungqvist, 2007; Loughran & Ritter, 2005; Welch & Ritter, 2002; Mizerka & Lizińska, 2017; Sieradzki, 2016; Zarzecki & Wołoszyn, 2013, 2016; Lizińska & Czapiewski, 2014, 2015; Pomykalski & Domagalski, 2015; Podedworna-Tarnowska, 2018), or alternative ones (Vismara, Paleari, & Ritter, 2012; Hadro & Pauka, 2019; Podedworna-Tarnowska, 2020). Research on the market reaction when announcing a change of listing ven- ue has been conr fi med by studies mainly based on the US market (Sanger & McConnell, 1986; Kadlec & McConnell, 1994; Jain & Kim, 2006; Dang, Michayluk, & Pham, 2018) and on the UK market (Campbell & Tabner, 2011; Vismara et al., 2012; Mortazian 2021). Such studies are also conducted on the basis of data coming from other stock exchanges including, the following mar- kets: French (Bacmann, Dubois, & Ertur, 2002), German (Bessler, Beyenbach, Rapp & Vendrasco, 2021, 2022), Korean (Park, Binh, & Eom, 2016), Indian (Ahmed, Aney, & Banerji, 2019), Brazilian (De Carvalho & Pennacchi, 2012), Chinese (Kwok, 2020). On the Polish market this topic is addressed extremely rarely. Kordela (2011) conducted a case study of five companies that changed their trading floor between 2007 and 2010, assessing their capitalisation, turn - over rate and return on investment at six-month intervals but the results are inconclusive. A broader study was conducted by Asyngier (2015) based on 29 companies that changed listing floor from 2008 to August 2014. His results show that there were abnormal positive stock returns before the change of list- ing market and clearly negative ones ae ft r the transfer of listing to the regulated market with the downward trend being strongest in the first dozen days ae ft r the debut on the main market. e a Th im of the article is to evaluate the market reaction to the change of list - ing venue of companies moving from the alternative market to the regulated market of the Warsaw Stock Exchange. First, the market reaction by assessing prices and liquidity of the shares of companies that have transferred from the alternative market to the main market was examined. Then, the analysis was extended by assessing the impact on the prices and liquidity of shares of inter- mediate events preceding the transfer and occuring before the company starts its listing on the target exchange, i.e., the announcement of the decision of the General Shareholders Meeting to list the company on the regulated market and the announcement of the approval of the prospectus by the Polish Financial Supervision Authority. There is a lack of research in the literature concern - D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 113 ing broader analysis for transfers taking place on the Warsaw Stock Exchange. Including both the impact of stock exchange shifting on market returns and liquidity of shares which is covered in the research and which fills this gap. e r Th est of the article is organised as follows. Section 1 contains a review of existing literature related to the studies concerning the listing changes and hypothesis development. Section 2 presents the methodology of the study and data collection. Sections 3 includes the results of the research regarding the con- sequences of the listing change on the Warsaw Stock Exchange and is divided into two paragraphs: the first one concerns on the rates of return and the sec - ond concerns liquidity. The last section covers the final conclusions. 1. Literature review and hypothesis development Each stock exchange or the market segments within it has specic f fi ormal re - quirements that must be fulfilled by a company seeking to have its shares au - thorized for listing and trading. He, Huang, and Zhang (2022) show on a the- oretical model that a carefully designed market microstructure, listing stand- ards, disclosure requirements, trading mechanism, and market governance, can play an important role to reduce investor ambiguity. On the more reputa- ble stock exchanges or the regulated segments of a particular exchange, these requirements tend to be more stringent and the need to meet them is a chal- lenge for companies entering these markets. The alternative markets, such as NewConnect in Poland, Alternative Investment Market (AIM) in the UK or NASDAQ in the US, have been designed to enable smaller entities to oper- ate on the public listing markets. Their characteristics are widely described in Pastusiak (2011), Vismara and others (2012), Panfil (2013), Asyngier (2013), Tomaszewski (2013), Kordela (2013), Zygmanowski (2017), Radke (2020). Although fewer regulatory restrictions characterize alternative markets they remain institutionalized stock markets. Shifting between markets and changing the exchanges is not a common phenomenon both in the US and Europe. As reported by Dang and others (2018) 196 companies made the switch from NADAQ to NYSE over the period 2000–2015. At the same time a voluntary change of listing location from NYSE to NASDAQ was made by only 53 companies. Research by Vismara and oth- ers (2012) shows that in the UK since the start of the Alternative Investment Market, i.e., from 1996 to 2009, only 90 companies have moved to the London Stock Exchange’s regulated market. Shareholder interest, greater visibility, and growth opportunities were cited as reasons for it. However, research by Campbell and Tabner (2011) shows that the majority of companies do not give a rationale for the transition. On the London Stock Exchange transfers of companies in the other direction, i.e., from the main floor of the stock ex - change to the alternative market are more common—there were as many as 114 Economics and Business Review, Vol. 8 (22), No. 4, 2022 282 such companies in the period under review. In both Vismara and others (2012) and Campbell and Tabner (2011) the most common motive for moving to a smaller stock exchange is indicated to be growth appropriate to the size of the company, the implementation of mergers and acquisitions, more flex - ible AIM environment, simplified reporting, cost savings and less regulation. Also for the German market the fact is notable that companies start listing on the primary segment and then move to the lower segments of Deutsche Börse (Bessler et al., 2021, 2022). Some studies present the results of two-way migra- tion (Vismara et al., 2012; Campbell & Tabner, 2011; Jenkinson & Ramadorai, 2013; Dang et al., 2018). Research using different approaches and time periods mostly indicate that the market reaction to the announcement of a company’s migration to a more highly regulated exchange is significantly positive, while the announcement of a transfer in the other direction tends to be poorly perceived by the mar- ket (Sanger & McConnell, 1986; Kadlec & McConell, 1994; Jain & Kim, 2006). Increases in CAR returns following the announcement of a change of listing o fl or from NASDAQ to NYSE immediately following a change of listing were shown by Jain and Kim (2006), noting that while the increases during the pe- riod of the actual transfer are positive, most of the increases occur around the date of the announcement, and the highest CARs were observed in the period between the announcement of the change of listing o fl or and the actual transfer. Campbell and Tabner (2011) showed that firms switching from the less-regu - lated AIM to the more regulated main section of the London Stock Exchange show positive returns on the day of the decision announcement while for firms switching in the opposite direction both the returns on the announcement date and the transfer date are negative. Conversely, ae ft r the implementation of the decision, the pattern of returns is inverted for both categories of firms. This is consistent with the results of Dharan and Ikenberry (1995), who observed a negative return performance measured by CARs over three years ae ft r the change in listing location of –12.39% that move from NASDAQ to NYSE or to AMEX and from AMEX to NYSE. Jenkinson and Ramadorai (2013) showed that while companies switching from the AIM market to the regulated market experienced on average positive returns of around 5% one year ae ft r the event the CAR is around –11%. In contrast and as a result of the transition from the regulated market to AIM companies have experienced average negative returns of around 5% on the results of the transition followed by positive returns with a CAR of around 25% one year ae ft r the event. The positive ee ff ct of positive cumulative returns following the NYSE listing move further helped companies to broaden their investor base and increase their recognition among investors (Kadlec & McConnell, 1994; Jain & Kim, 2006). Transfer of the company from the alternative market to the regulated mar- ket requires issuers to comply with a much higher regulatory, information and communication regime with the market. A diligent information policy D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 115 on the part of issuers reduces the asymmetry of information between those with strong ties to the company and other outside investors resulting in in- creased investor confidence and reduced risk. Consequently, the market re - actions for company’s transfer should be positive. These assumptions lead to the following hypothesis: H1: As a company transfers from the alternative to the regulated market its investors achieve above-average returns. In the context of the previously mentioned diversity of the information en- vironment in stock exchanges with die ff rent information standards it should be taken into account that quantifying the quality of the information environ- ment is extremely dic ffi ult, but there are some attempts in the empirical stud - ies trying to do so. Leuz and Verrecchia (2000) list those economic quantities that can be measures of information asymmetry between a company and its shareholders: the bid-ask spread which is de facto the measure of trading costs, liquidity and price volatility. Liquidity is one of the factors shaping investment returns achieved by inves- tors because of its link to transaction costs. It can be understood as the ease of entering and exiting the market which encourages investment in securities and at the same time increases market security. Liquidity is a multi-dimensional and complex concept. Sarr and Lybek (2002) argue that liquidity has five dimen - sions: tightness, immediacy, depth, breadth, resiliency, but indicate these char- acteristics as overlapping to some extent and therefore most of the data do not fully correspond to them. The different dimensions of the liquidity are widely described in the literature (e.g., Kyle, 1985; Engle & Lang, 2001; Doman, 2011; Amihud & Mendelson, 2012; Włosik, 2017; Le & Gregoriou, 2020). Liquidity is consequently an important factor in asset pricing. The greater the liquidity of a n fi ancial instrument, the higher the price at which it can be sold. Therefore, investors prefer more liquid investments that are traded quickly and at a lower cost. Less liquid investments imply higher transaction costs and should there- fore oe ff r correspondingly higher expected returns to be as attractive as more liquid investments (Amihud & Mendelson, 1991). Indeed, with limited liquid- ity comes higher risk, so investors faced with the potential dic ffi ulty of resell - ing shares at the market price will demand a liquidity premium in the form of higher rates of return. e Th refore, in a more liquid market trades are more likely to be concluded by investors, which is conducive to liquidity enhance- ment. According to research by Ang, Shtauber and Tetlock (2013) over-the- counter stocks are far less liquid, disclose less information and exhibit lower institutional holdings than do listed stocks. Moreover, compared with premi- ums in listed markets the OTC illiquidity premium is several times higher, the size, value, and volatility premiums are similar, and the momentum premium is three times lower. Therefore, it is not surprising that some researchers, such 116 Economics and Business Review, Vol. 8 (22), No. 4, 2022 as Pagano, Panetta and Zingales (1998) argue that the main reason for a com- pany to go public is that shareholders want their shares to be liquid. Amihud and Mendelson (1986) presented a theoretical model describing the impact of liquidity on asset prices. They used the ratio of total daily volume to total absolute return as an indicator of liquidity. The market-observed expected return is an increasing and concave function of the spread. Less liquid assets with higher transaction costs are held by investors for longer periods and vice versa. The length of investors’ holding periods is related to the bid-ask spread. Atkins and Dyl (1997) empirically conr fi med a strong positive relationship for various stocks between the bid-ask spread and the inverse of the turnover ratio, which measures the holding period of a stock. They showed that the re - lationship between holding periods and bid-ask spreads is much stronger on the NASDAQ, where spreads are wider, than on the NYSE, where spreads are smaller. According to model of Acharya and Pedersen (2005), investors should be concerned about the performance and marketability of a security both in a market downturn and when liquidity ‘dries up’. Their model shows that the required return on a security increases with the covariance between its illiquid- ity and market illiquidity, decreasing with the covariance between the security’s return and market illiquidity, and decreasing with the covariance between its illiquidity and market return. e e Th e ff cts of moving from one exchange to another in the context of stock liquidity (and transaction costs) are also studied in the literature. Amihud and Mendelson (1986), Sanger and McConnell (1986), Kadlec and McConnell (1994), Jain and Kim (2006) argue that trading liquidity improves when shares start to be traded on an organised exchange. Most oe ft n it is emphasized that such r fi ms experience higher trading volumes and lower trading costs (usually measured by the bid-ask spread). However, some studies indicate that liquidity deteriorated (Park et al., 2016). Mortazian (2021) showed that companies mov- ing from the main market of the London Stock Exchange to AIM worsen their information environment as measured by the liquidity and volatility of their shares upon entering AIM. The move from the main market to AIM results in a significant reduction in liquidity (measured by an increase in illiquidity of the Amihud index), bid-ask spread, and a reduction in the volatility of stock returns. According to Kwok (2020), market reactions to the announcement of a listing o fl or switch depend on liquidity—highly liquid firms do not show a signic fi ant market reaction around the announcement, but a much larger positive market reaction occurs for a low liquidity firm. According to Vismara and others (2012), most of the oe ff rings carried out on the alternative markets set up by stock exchanges in Europe are oe ff red only to institutional investors and are the equivalent of private placements having little impact on the development of liquid trading. The specificity of the alter - native market in Poland lies in its rather distinctive shareholding structure, which oe ft n consists of persons closely related to the company, i.e., founders, D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 117 employees, acquaintances, investors participating in previous private place- ments. On the alternative market, domestic individual investors account for the turnover of the vast majority of shares. On the NewConnect in Poland their average share of turnover between 2007 and 2020 was close to 81%, and in the second half of 2020 alone it was 91%. Hence, it is relatively more dif- ficult to attract the interest of institutional investors on this market (share of turnover just over 14%) and foreign investors (around 5%), who largely focus their attention on the regulated market (own calculations based on https:// www.gpw.pl/analizy, accessed 21st November 2021). Taking into considera- tion these details and given the availability of data it is assumed that compa- nies moving from the alternative market to the regulated market of the WSE improve their information environment which can be measured by liquidity of stocks. It is hypothesised that: H2: As a company transfers from the alternative to the regulated market there is an increase in liquidity of its shares. e Th re are other strands of research in the context of changes in listing markets which are worth emphasizing: the context of the operational per- formance of companies (Papaioannou, Travlos, & Viswanathan, 2003, 2009; Bessler et al., 2021, 2022), the achievement of important corporate goals (Kedia & Panchapagesan, 2011), the microstructure of the stock market (Brennan & Subrahmanyam, 1996; Amihud, Mendelson, & Lauterbach, 1997; Muscarella & Piwowar, 2001; Bennett & Wei, 2006). 2. Research methods and sample selection e m Th ethod used in the research is based on the event study method, which aims to measure the impact of various events on the market value of shares (Gurgul, 2006; Perepeczo, 2010). Three signic fi ant events related to the change of listing markets were identie fi d as the announcement of the transfer (decision of the General Shareholders Meeting—GSM), the announcement of the approval of the prospectus by the supervisory authority (approval of the Polish Financial Supervision Authority—PFSA) and the change of listing floor (first listing on the regulated market of the Warsaw Stock Exchange—WSE). e c Th ompanies that changed their listing floor from the alternative market to the regulated market of the Warsaw Stock Exchange are the subject of the analysis. The research period covers 2007–2020. It is worth emphasising that this is the period beginning in 2007, i.e., the year in which the alternative mar- ket (NewConnect) was established on the Polish capital market and the r fi st debuts took place there. However, the first transfer of a company to the regu - lated market of the WSE took place in 2008. In the case of two companies, for 118 Economics and Business Review, Vol. 8 (22), No. 4, 2022 which the transfer announcement dates were unavailable, the announcement of the prospectus submission to the supervisory authority was accepted. e r Th esearch sample included 71 companies, i.e., all companies that have changed listing floor between the establishment of the NewConnect and 2020. a Th t accounted for approximately 11.5% out of the 620 debuts on this market between 2007 and 2020, and at the same time accounted for 20% of the debuts on the regulated market. Only 23 companies transferring from the alternative market to the regulated market made a new share issue at the same time, two of which additionally oe ff red to sell existing shares. In most cases (48 compa - nies) the value of the oe ff ring during the transfer is null. In creating the research sample the authors were inspired by the research of Jenkinson and Ramadorai (2013) who noted that with the announcement of a company’s intention to relocate to the main market other news is announced in parallel, which falls into four main categories: the announcement of financial or trading results, share issues or capital restructuring, acquisitions and dispos- als, and breaches of one or more listing rules. In earlier research, Campbell and Tabner (2011) hypothesised that a promotion to the main market from AIM is likely to be associated with positive news, while a move from the main market to AIM is likely to be associated with less favourable news ree fl cting the pos - sibility that a change in listing may be a symptom rather than a cause of com- pany performance. Jenkinson and Ramadorai (2013) tested the robustness of the results to the rejection of specic fi fi rms from the sample and found that the exclusion of firms publishing additional information alongside the news of a change in listing floor would not signic fi antly alter the results and con - sequently the inference. e Th refore, in this study companies with any of these types of simultaneous announcements were left in the sample in order to have a more representative set of companies changing listing floor. The observed stock splits or consolidations occurred outside the accepted estimation window. er Th e are different approaches to assessing investment performance in the literature and a description of the approaches and measures can be found among others in Perepeczo (2010), Kujawa and Ostrowska (2016), among others. In the event-driven approach, long-term performance for a particular stock is com- monly measured by additional returns expressed by the Cumulative Abnormal Return (CAR) measure, which stands for cumulative additional return, or buy- and-hold returns (BHR). However, a portfolio of companies uses an aggregate approach for the study population in assessing long-term performance, meas- uring additional rates with the CAAR (Cumulative Average Abnormal Return) measure denoting the cumulative average abnormal return on the shares’ port- folio achieved over the observation period. An important issue related to the CAAR model is the relation of the returns of a given company to the returns achieved on the benchmark. Thus, companies, which may have had their debut in diametrically die ff rent economic conditions, can still be compared with each other, as the measured value is the return excess over the benchmark. Because D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 119 each company has unique characteristics (i.e., different sectors, different finan - cial situations, die ff rent motives for the IPO), the CAAR value was used in the analysis, which is expressed by the formula: CAAR = AAR (1) iT ∑ it t=1 CAAR – cumulative average abnormal returns on the portfolio of shares in it the observation period T, T – observation period, time interval measured in trading days, N – number of companies in the analysed portfolio, AAR – the average abnormal rate of return on stock i over the period t cal- it culated as: AAR = AR (2) it ∑ it i=1 AR – the abnormal rate of return on stock i achieved in period t: it • for companies listed on the WSE is calculated according to the formula: P − P WIG −WIG it it−1 t t−1 AR = − (3) it P WIG it−1 t−1 • for companies listed on NewConnect is calculated according to the for- mula: P − P NCI − NCI it it−1 t t−1 AR = − (4) it P NCI it−1 t−1 P – the price of stock i in period t, it WIG – WIG Index in period t, it NCI – NCI Index in period t. it e CAAR w Th as estimated over a period of 45 days preceding and follow - ing the event. In addition, the analysis generated a CAAR curve for the period from the time of the event (i.e., event date t = 0) to 120 days ae ft r the event. This analysis is intended to indicate the results of an investment strategy in which an investor opens a long position in a particular company at the time of a par- ticular event. The point t = 0 den fi es the date of the event: – GMS: the announcement of the decision of the General Shareholders Meeting to list the company on the regulated market. – PFSA: the announcement of the approval of the prospectus by the Polish Financial Supervision Authority. – WSE: change of trading floor, i.e., first listing on the regulated market of the Warsaw Stock Exchange. 120 Economics and Business Review, Vol. 8 (22), No. 4, 2022 Points on the t-axis with negative values indicate days before and days to the right ae ft r the event. This reduces the analysis to a cohort approach, in which, despite the die ff rent event dates of these companies (i.e., die ff rent IPO dates), the same x-axis is adopted for all companies analysed. As the calculation is done on the sample of stocks it was possible to also de- rive the Standard Error measure and further provide the Cond fi ence Interval for the CAAR. Moreover, the Student’s t-test for means and the Mood’s test for medians were carried out to statistically verify the die ff rences between the CAAR obtained from analysed events. For the normality testing the Shapiro- Wilk test was conducted. Liquidity is related to the amount of demand and supply in the market and therefore to the relationship between buyers and sellers of securities. Trading activity in the market is measured by the number of transactions in a given period, the number of shares sold, the value of shares sold, the relative value of shares sold, the quotient of shares sold and put up for sale, the quotient of the value of shares sold and put up for sale (Lo & Wang, 2000). Various measures of liquidity can be found in the literature and have been discussed in detail by Amihud (2002), Saar and Lybek (2002), Goyenko, Holden and Trzcinka (2009), Olbryś (2013), Ma, Anderson and Marshall (2016), Le and Gregoriou (2020), among others. In the study the illiquidity index proposed by Amihud (2002) was used, which expresses the average daily return per monetary unit of trad- ing volume on that day meaning that the higher its value the lower the liquid- ity of a given stock. It is an increasingly popular ratio used in empirical studies (Karolyi, Lee, & van Dijk, 2012; Lou & Shu, 2017; Aouadi, Arouri, & Roubaud, 2018; Włosik, 2018; Kwok, 2020; Mortazian, 2021). iy iyd ILLIQ = (5) iy ∑ D VOLID iy t=1 iyd whereas: r – rate of return recorded by company i on day d of year y, iyd VOLID – t he value, expressed in PLN, of the trading volume in shares of iyd company i on day d of year y, D – the number of days on which the company was listed during the iy y year. e Th advantages of this measure are aptly summarized by Lou and Shu (2017). First, the Amihud measure has a simple construction that uses the absolute value of the daily return-to-volume ratio to capture price impact. Second, the measure uses daily data and therefore provides a longer time series relative to intra-daily proxies. Third, the measure has a strong positive relationship with expected stock return and thus, it helps in examining and understanding li- quidity measurement and liquidity premium. D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 121 Based on the rate the high and low liquidity pools of companies were se- lected, i.e., the high liquidity sample consists of the companies, which had rate lower than the median for the entire population. The rates were calcu - lated based on the 90 days window (from –45 days before event, to 45 ae ft r a particular event). To test the die ff rences of liquidity for various events, the Student’s t-test for means and Wilcoxon’s test for medians were performed. For the normality test- ing the Shapiro-Wilk test was conducted. 3. Results 3.1. Transfer and rates of return Figure 1 below shows the CAAR curve estimated for 71 companies listed on NewConnect that subsequently migrated to the regulated market of the WSE. e t Th ransfers themselves are followed by a decrease in market returns. It is the announcement of the transfer of a company and the institutional conr fi - mation by the supervision of the company’s readiness for this transfer resulting from the approval of the prospectus that creates positive market reactions. The above data shows that the PFSA acceptance can be seen as a positive signal sent to investors, indicating that the company is developing, but also that prepara- tory processes are underway due to the need to meet the high requirements Figure 1. CAAR curve for –/+ 45 days for all companies Source: Own calculations. 122 Economics and Business Review, Vol. 8 (22), No. 4, 2022 associated with a listing on the main floor. e Th positive reaction of the market is the result of the supervisor’s decision to approve the prospectus, which is an institutional and legal conr fi mation of the company’s compliance with the high regulatory requirements. At the same time it is an authentication by the supervisory institution of the company’s readiness status to be listed on the main floor of the stock exchange. The mere transfer of a company from a less- regulated to more-regulated market results in a decrease in market value ae ft r the change of listing o fl or, as conr fi med by previous results of studies carried out in other markets. e CAAR v Th alues for 0 and 45 days (starting from –45) are presented in Table 1 below. They indicate the statistical signic fi ance only for the GSM event— the average value of CAAR is around 11.2%. The remaining events do not ex - hibit statistically signic fi ant CAAR. Table 1. CAAR values for 0 and 45 days Event Time horizon CAAR (%) t-statistics [–45, 0] 5.6 1.5763 GSM [–45, 45] 11.2 2.1460** [–45, 0] 2.1 0.6526 PFSA [–45, 45] –0.8 0.1117 [–45, 0] 3.4 1.0454 WSE [–45, 45] –6.2 –1.2071 Note: The *, ** and *** symbols indicate signic fi ance at 10, 5 and 1%, respectively. Source: Own calculations. e fi Th ndings can be explained by reports by Diamond and Verrecchia (1991) and Leuz and Verrecchia (2000), according to which companies changing vol- untarily from a lower- to a higher-regulated listing market opt for a higher level of disclosure to reduce information asymmetry and thus experience an increase in liquidity by attracting increased demand. Consequently, this leads to a reduction in the cost of raising capital, and from the point of view of the investor providing the capital to a reduction in returns. This therefore conr fi ms the idea that information uncertainty is a cross-cutting risk factor and is os ff et by higher stock returns. Another interesting explanation is the concept of Zhang (2006), accord- ing to whom the likely source of temporary price and return increases is the lack of full information flow to share prices resulting from higher information uncertainty, as investors tend to underreact to new information when there is greater uncertainty about its impact on the value of the company. A rational explanation for the post-IPO declines can be substantiated by the concept of D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 123 Loughran and Ritter (1997). They suggest that the decision of companies to conduct a share oe ff ring usually follows a period of good operational perfor - mance, which then deteriorates. They explain that companies usually improve their operational performance in the last period before the issue. The market seems to overestimate this improvement and underestimate long-term, mod- erately reversible trends in operating performance. Consequently, at the time of debut, market prices ree fl ct the capitalisation of this temporary operational improvement, and when this specici fi ty of the tem - porariness of improved operational performance becomes evident, the shares underperform. The collapse of the share price on transfer to a more challeng - ing trading floor indicates that this is not a good time for shareholders to exit. In the authors’ opinion, shareholders intending to divest are aware of this fact, Figure 2. CAAR curves for –/+ 45 days for all companies along with confidence interval Source: Own calculations 124 Economics and Business Review, Vol. 8 (22), No. 4, 2022 which is conr fi med by the fact that out of 71 transfers in the analysed period only two companies oe ff red to sell existing shares. At the same time, as many as 43 companies did not carry out an oe ff r at all at the time of the transfer. As part of the analysis a comparison of the ranges of variation for each curve was also carried out. Figure 2 presents the CAAR curves along with the cond fi ence interval. e M Th ood’s test and Student’s t-test of equality of respectively medians and means were carried out with the aim of verifying the hypothesis H , indicat- ing the equality of the median/mean CAAR at the end of the analysed period (t = 45), for the respective pairs of events: GSM and PFSA, GSM and WSE, and PFSA and WSE. The p-values for the respective pairs of events are presented in Table 2. Table 2. The tests for the respective pairs of events all companies, –/+ 45 days Median Mean Pair statistics p-value statistics p-value GSM-PFSA 1.08 0.2980 1.60 0.1130 GSM-WSE 6.43 0.0112 2.38 0.0194 PFSA-WSE 1.41 0.2354 1.00 0.3173 Note: The Shapiro-Wilk test for normality has been performed. The CAAR measures are normally distributed for all events with a 1% signic fi ance level. The Shapiro-Wilk test statistics ( p-values) for GSM, PFSA, and WSE respectively: 0.9431 (0.0215), 0.9845 (0.6107), 0.9774 (0.3509). Source: Own calculations. Figure 3. CAAR curve for 0–120 days for all companies Source: Own calculations. D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 125 According to the results in Table 2, at the 5% signic fi ance level the hypothesis of equality of means (median) can be rejected only for the pair of GSM and WSE events. That is at 45 days ae ft r the event the expected (median) returns for the GSM and WSE events indicate statistical die ff rences. For the other pairs of events the hypothesis of the die ff rence of these averages (medians) cannot be rejected. In addition, the analysis involved the construction of a CAAR curve for the period from the event to 120 days ae ft r the event presented on Figure 3. e c Th orresponding tests have been also carried out to verify hypothesis H , indicating equality of the median–/–means CAAR at the end of the period analysed (t = 120), for the relevant pairs of events: GSM and PFSA, GSM and WSE, and PFSA and WSE. e Th tests’ results for the respective pairs of events are presented in Table 3. Table 3. The tests for the respective pairs of events all companies, 0–120 days Median Means Pair statistics p-value statistics p-value GSM-PFSA 4.80 0.0285 2.40 0.0180 GSM-WSE 4.61 0.0318 3.79 0.0002 PFSA-WSE 0.01 0.9245 1.74 0.0844 Note: The Shapiro-Wilk test for normality was performed. The CAAR measures are normally distributed for all events with a 1% signic fi ance level. The Shapiro-Wilk test statistics ( p-values) for GSM, PFSA, and WSE, respectively: 0.9452 (0.0199), 0.9155 (0.0003), 0.9555 (0.0328). Source: Own calculations. According to Table 3, at a signic fi ance level of 5%, the hypothesis of equal - ity of means for all pairs of events only can be rejected (for medians, it applies to GSM-PFSA and GSM-WSE). iTh s means that at 120 days ae ft r the event, the CAAR rates for the events: GSM and PFSA, GSM and WSE, and PFSA and WSE indicate that the levels are statistically signic fi antly die ff rent (for the me - dian test, only for PFSA-WSE pair H cannot be rejected). 3.2. Transfer and liquidity In this section, we investigate the impact of a particular event on liquidity. In Figure 4 we present results in Amihud illiquidity ratio units as well as in trad- ing volume. e Th results of the analyses indicate that the transfer of companies from the alternative market to the regulated market of the Warsaw Stock Exchange is associated with a decrease in the Amihud illiquidity ratio, which means an im- provement in the liquidity of the traded shares. At the same time, the biggest change in liquidity concerns the announcement of the change of listing market 126 Economics and Business Review, Vol. 8 (22), No. 4, 2022 Median Mean Note: *** symbol indicate differences between Before and After at 1% significance. Figure 4. Illiquidity ratio before and ae ft r GSM, PFSA and WSE Source: Own calculations. Median Mean Note: *** and ** symbols indicate die ff rences between Before and After at 1% and 5% signic fi ance respectively. Figure 5. Trading volume before and ae ft r GSM, PFSA and WSE Source: Own calculations. announced by the GSM itself. Thus, it is not only the change in the information environment resulting from different regimes of communication with inves - tors that causes increased demand for the company’s shares, but the announce- ment of this change by the GSM and the fact that the PSFA has approved the prospectus prepared by the company. Figure 5 presents the median trading volume 45 days before and 45 ae ft r the event are presented. The results remain consistent with those presented on the illiquidity rate above—the most significant difference in median trading volume can be observed in for PFSA and WSE events. Figure 6 indicates CAAR curves for correspondingly high ILLIQ values, i.e., above the median of all companies. The p-value of equality of medians/means for high ILLIQ companies gives grounds to reject hypothesis H for the pair of GSM and WSE events (Table 4). iTh s means that the cumulative levels of returns for lower average liquidity companies are statistically die ff rent for the GSM announcement event from the WSE listing event. Figure 7 shows the CAAR curve for companies with low ILLQs. D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 127 Figure 6. CAAR curve for –/+ 45 days for high ILLIQ companies Source: Own calculations. Table 4. The tests for the respective pairs of events—high ILLIQ companies Median Mean Pair statistics p-value statistics p-value GSM-PFSA 5.08 0.0242 1.20 0.1167 GSM-WSE 7.81 0.0052 1.98 0.0520 PFSA-WSE 1.52 0.2181 0.84 0.4058 Note: The Shapiro-Wilk test for normality was performed. For the GSM and WSE the CAAR measures are normally distributed with 1% signic fi ance level. The Shapiro-Wilk test statistics (p-values) for GSM, PFSA, and WSE respectevely: 0.9389 (0.0769), 0.9648 (0.3334), 0.9260 (0.0304). Source: Own calculations. Figure 7. CAAR curve for +/– 45 days for low ILLIQ companies Source: Own calculations. 128 Economics and Business Review, Vol. 8 (22), No. 4, 2022 The p-value of the tests of equality of medians/means for companies with a low ILLIQ index value does not warrant rejection of hypothesis H (Table 5). For companies with higher liquidity the response to individual events, as meas- ured by the CAAR value for point t = 45, is similar for the events analysed. Table 5. The tests for the respective pairs of events—low ILLIQ companies Median Mean Pair statistics p-value statistics p-value GSM-PFSA 0.03 0.8531 1.03 0.3088 GSM-WSE 2.35 0.1252 1.44 0.1571 PFSA-WSE 0.02 0.8867 0.64 0.5226 Note: The Shapiro-Wilk test for normality was performed. The CAAR measures are normally distributed for all events with a 1% signic fi ance level. The Shapiro-Wilk test statistics ( p-values) for GSM, PFSA, and WSE, respectively: 0.9870 (0.9911), 0.9728 (0.6373), 0.9756 (0.7704). Source: Own calculations. e Th analysis related to both the abnormal returns and the liquidity is pre - sented in Table 6. The companies were grouped into two baskets: low and high liquidity (based on the median of the Illiquidity ratio). The t-test statistics were calculated for this categorization for selected post-event days, where H states that CAAR is equal to 0. e Th following conclusions can be drawn. First, for the post-WSE transition the average CAAR values decrease for all of the company types (i.e., liquidity). Second, the highest average returns are generated ae ft r the GSM event espe - cially for low liquidity companies. Third, event vs. companies’ liquidity is sta - tistically die ff rent for various combinations (i.e., the various types of liquidity companies react die ff rently on the same event). Conclusions e r Th esults of the analyses and the conclusions drawn from them are largely consistent with the empirical studies described in the article and which were conducted based on observations made on global markets (e.g., Jain & Kim, 2006; Campbell & Tabner, 2011; Vismara et al., 2012; Jenkinson & Ramadorai, 2013; Kwok, 2020; Mortazian, 2021). Considering the initial time horizon of –45/+45 days, CAAR was highest for GSM events amounting to 11.2% and was statistically signic fi antly die ff rent from CAAR for WSE event. For the time ho - rizon of 0/+120 days, i.e. the GSM event seems to provide the most signic fi ant uplift of CAAR amounting to on average 14.7% for the low-liquidity companies. D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 129 Table 6. CAAR summary results table for post-event analysis All firms Low liquidity firms High liquidity firms Days Event post CAAR CAAR CAAR t-statistics t-statistics t-statistics event (%) (%) (%) [0, 5] 1.0 0.7901 –0.2 –0.1170 3.5 1.6619 [0, 10] –0.4 –0.2156 –0.5 –0.2472 0.3 0.0708 [0, 20] –2.7 –1.0048 –2.4 –0.7708 –2.5 –0.5122 [0, 30] 0.0 –0.0065 2.8 0.6647 –3.6 –0.6275 GSM [0, 40] 1.8 0.4668 3.5 0.7451 0.2 0.0339 [0, 50] 4.2 1.0344 4.6 0.9708 4.8 0.6194 [0, 60] 2.5 0.5613 3.2 0.6245 3.4 0.4078 [0, 90] 10.3 2.0389** 10.9 1.8988** 12.4 1.2621 [0, 120] 8.2 1.4934 14.7 2.4725*** 0.5 0.0504 [0, 5] 0.8 0.5445 –0.1 –0.0443 2.0 0.9223 [0, 10] 2.0 0.9472 0.7 0.3196 3.6 0.8804 [0, 20] 2.8 0.9808 1.6 0.4787 4.6 0.9243 [0, 30] 1.3 0.3519 –0.1 –0.0279 3.2 0.5116 PFSA [0, 40] 2.1 0.4479 –1.1 –0.2370 6.7 0.7267 [0, 50] –0.8 –0.1792 –2.6 –0.5182 1.7 0.1901 [0, 60] –3.6 –0.7355 –4.9 –0.9018 –1.4 –0.1635 [0, 90] –4.9 –1.0394 –5.5 –1.1219 –3.6 –0.3942 [0, 120] –8.1 –2.0395** –4.1 –0.7442 –13.6 –2.4056*** [0, 5] –2.0 –0.9459 –2.7 –1.5058 –1.4 –0.3292 [0, 10] –4.9 –2.2083** –5.8 –2.3709** –3.8 –0.9638 [0, 20] –5.7 –2.2835** –2.9 –1.0859 –9.5 –2.1801** [0, 30] –7.3 –2.3200** –2.6 –0.7033 –13.5 –2.4791*** WSE [0, 40] –8.9 –2.7928*** –6.2 –1.5674 –12.3 –2.2974** [0, 50] –11.2 –3.1572*** –7.3 –1.7241** –16.0 –2.7229*** [0, 60] –11.1 –3.6708*** –5.5 –1.4672 –18.1 –3.7447*** [0, 90] –12.9 –3.0129*** –5.5 –1.0636 –22.2 –3.1995*** [0, 120] –18.3 –4.2520*** –6.7 –1.2714 –32.7 –4.8707*** Note: The ** and *** symbols indicate signic fi ance at 5% and 1%, respectively. Source: Own calculations. 130 Economics and Business Review, Vol. 8 (22), No. 4, 2022 e Th hypothesis concerning the market value of shares as a result of the transfer of companies from the alternative market to the regulated market of the Warsaw Stock Exchange has been verie fi d negatively, as there is a decrease in it. It is the announcement of the company’s transfer decided by the GSM and the institutional conr fi mation by supervision of the company’s readiness for this transfer resulting from the approval of the prospectus that creates the market value. On the other hand, the hypothesis regarding the improvement in the liquidity of the shares as a result of the company’s transfer and the ana- lysed events preceding the transfer was conr fi med. PFSA and WSE events pro - vided statistically signic fi ant liquidity changes—ae ft r PFSA and WSE trading volume of the companies usually grows. e r Th esults of the research have an applied dimension for managers and in - vestors, as they indicate the directions of changes in the market value of shares and their liquidity as a result of the events discussed in the article. Given that share price reaction may also ree fl ct other information that becomes available at the time of the listing announcement, conclusions on performance and li- quidity in these two types of markets based on this research may also be limit- ed. In future research also the division by industry could be taken into consid- eration as it was not used primarily because of the shallowness of this market in Poland and the still limited research group. In the context of the literature discussed and the results of the empirical re- search carried out, it would be appropriate to consider Asyngier’s (2015) rightly suggested call for the introduction in Poland of regulations allowing the trans- fer of listings from the regulated market to the alternative market, which could protect small investors from dic ffi ulties in selling delisted shares. This is par - ticularly important considering the trends in the IPO market in Poland indi- cating the declining numbers of initial public oer ff ings and increasing records of delisting—the trend observed also on the developed market, for instance in the US (Doidge, Karolyi, & Stulz, 2017). References Acharya V. V., & Pedersen, L. H. (2005). Asset pricing with liquidity risk. Journal of Financial Economics, 77(2), 375–410. https://doi.org/10.1016/j.jfineco.2004.06.007 Ahmed, S., Aney, M. S., & Banerji, S. (2019). Migration of SMEs in the Bombay Stock Exchange: A die ff rent look at the SME financing issues . The International Growth Centre, Final Report. Amihud, Y. (2002). Illiquidity and stock returns: Cross-section and time-series ef- fects. Journal of Financial Markets, 5(1), 31–56. https://doi.org/10.1016/S1386- 4181(01)00024-6 Amihud, Y., Mendelson, H. (1986), Asset pricing and the bid-ask spread. Journal of Financial Economics, 17(2), 223–249. https://doi.org/10.1016/0304-405X(86)90065-6 D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 131 Amihud, Y., & Mendelson, H. (1991). Liquidity, asset prices and financial policy. Financial Analysts Journal, 47(6), 56–66. https://doi.org/10.2469/faj.v47.n6.56 Amihud, Y., & Mendelson, H. (2012). Liquidity, the value of the firm, and corporate fi - nance. Journal of Applied Corporate Finance, 24(1), 17–32. https://doi.org/10.1111/ j.1745-6622.2012.00362.x Amihud, Y., Mendelson, H., & Lauterbach, B. (1997). Market microstructure and secu- rities values: Evidence from the Tel Aviv exchange. Journal of Financial Economics, 45, 365–390. https://doi.org/10.1016/S0304-405X(97)00021-4 Ang, A., Shtauber, A. A., & Tetlock, P. C. (2013). Asset pricing in the dark: The cross- section of OTC stocks. Review of Financial Studies, 26(12), 2985–3028. https://doi. org/10.1093/rfs/hht053 Asyngier, R. (2013). Wprowadzanie akcji do obrotu na rynku NewConnect na tle głównych alternatywnych systemów obrotu w Europie. Annales Universitatis Mariae Curie-Skłodowska. Sectio H. Oeconomia, 47(2), 7–16. Asyngier, R. (2015). Wpływ zmiany rynku notowań na cenę akcji polskich spółek giełdowych. Zeszyty Naukowe Uniwersytetu Szczecińskiego. Finanse, Rynki Finansowe, Ubezpieczenia, 862(75), 19–30. https://doi.org/10.18276/frfu.2015.75-02 Atkins, A. B., & Dyl, E. A. (1997). Transactions costs and holding periods for common stocks. Journal of Finance, 52, 309–325. https://doi.org/10.1111/j.1540-6261.1997. tb03817.x Aouadi, A., Arouri, M., & Roubaud, D. (2018). Information demand and stock mar- ket liquidity: International evidence. Economic Modelling, 70, 194–202. https://doi. org/10.1016/j.econmod.2017.11.005 Bacmann, J. F., Dubois, M., & Ertur, C. (2002). Valuation ee ff cts of listing on a more prominent segment of the stock market: Evidence from France. European Financial Management, 8(4), 479–493. https://doi.org/10.1111/1468-036X.00200 Bennett, P., & Wei, L. (2006). Market structure, fragmentation, and market quality. Journal of Financial Markets, 9(1), 49–78. https://doi.org/10.1016/j.finmar.2005.12.001 Bessler, W., Beyenbach, J., Rapp M. S., & Vendrasco, M. (2021). The global financial crisis and stock market migrations: An analysis of family and non-family firms in Germany. International Review of Financial Analysis, 74, 101692. https://doi. org/10.1016/j.irfa.2021.101692 Bessler, W., Beyenbach, J., Rapp, M. S., & Vendrasco, M. (2022). Why do firms down-list or exit from securities markets? Evidence from the German Stock Exchange. Review of Managerial Science. https://doi.org/10.1007/s11846-022-00554-4 Brennan, M. J., & Subrahmanyam, A. (1996). Market microstructure and asset pricing: On the compensation for illiquidity in stock returns. Journal of Financial Economics, 41(3), 441–464. https://doi.org/10.1016/0304-405X(95)00870-K Campbell, K., & Tabner, I. T. (2011). Bonding, firm value and liquidity: An analysis of mi - grations between the AIM and the official list of the London Stock Exchange . h ttps:// doi.org/10.2139/ssrn.1608403 Dang, V. A., Michayluk, D., & Pham, T. P. (2018). The curious case of changes in trad - ing dynamics: When firms switch from NYSE to NASDAQ. Journal of Financial Markets, 41, 17–35. https://doi.org/10.1016/j.finmar.2018.07.001 132 Economics and Business Review, Vol. 8 (22), No. 4, 2022 De Carvalho, A. G., & Pennacchi, G. G. (2012). Can a stock exchange improve corporate behavior? Evidence from r fi ms’ migration to premium listings in Brazil. Journal of Corporate Finance, 18(4), 883–903. https://doi.org/10.1016/j.jcorpn.2011.01.003 fi Dharan, B. G., & Ikenberry, D. L. (1995). The long-run negative drift of post-listing stock returns. Journal of Finance, 50(5), 1547–1574. https://doi.org/10.2307/2329326 Diamond, D. W., & Verrecchia, R. E. (1991). Disclosure, liquidity, and the cost of capital. Journal of Finance, 46(4), 1325–1359. https://doi.org/10.2307/2328861 Doidge, C., Karolyi, G. A., & Stulz, R. M. (2017). The U.S. listing gap. Journal of Financial Economics, 123(3), 464–487. https://doi.org/10.1016/j.jfineco.2016.12.002 Doman, M. (2011). Mikrostruktura giełd papierów wartościowych. Poznań: Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu. Engle, R. F., & Lange, J. (2001). Predicting VNET: A model of the dynamics of market depth. Journal of Financial Markets, 4(2), 113–142. https://doi.org/10.1016/S1386- 4181(00)00019-7 Goyenko, R. Y., Holden, C. W., & Trzcinka, C. A. (2009). Do liquidity measures measure liquidity?. Journal of Financial Economics, 92(2), 153–181. https://doi.org/10.1016/j. jfineco.2008.06.002 Gurgul, H. (2006). Analiza zdarzeń na rynkach akcji. Wpływ informacji na ceny pa- pierów wartościowych. Kraków: Oc fi yna Ekonomiczna. Hadro, D., & Pauka, M. (2019). Underpricing on the selected European alternative in- vestment markets. e-Finanse, 15(2), 87–94. https://doi.org/10.2478/fiqf-2019-0014 He, J., Huang, H. H., & Zhang S. (2022). Correlation ambiguity, listing choice, and mar- ket microstructure. Journal of Management Science and Engineering, 7(1), 61–97. https://doi.org/10.1016/j.jmse.2021.08.003 Jain, P. K., & Kim, J. (2006). Investor recognition, liquidity, and exchange listings in the reformed markets. Financial Management, 35(2), 21–42. https://doi.org/10.1111/ j.1755-053X.2006.tb00140.x Jenkinson, T., & Ramadorai, T. (2013). Does one size t fi all? e Th consequences of switch - ing markets with different regulatory standards. European Financial Management, 19, 852–886. https://doi.org/10.1111/j.1468-036X.2013.12021.x Kadlec, B. G., & McConnell, J. J. (1994). The ee ff ct of market segmentation and illi - quidity on asset prices: Evidence from exchange listings. Journal of Finance, 49(2), 611–636. https://doi.org/10.1111/j.1540-6261.1994.tb05154.x Karolyi, G. A., Lee, K. H., & van Dijk, M. A. (2012). Understanding commonality in li- quidity around the world. Journal of Financial Economics, 105(1), 82–112. https:// doi.org/10.1016/j.jfineco.2011.12.008 Kedia, S., & Panchapagesan, V. (2011). Why do only some Nasdaq firms switch to the NYSE? Evidence from corporate transactions. Journal of Financial Markets, 14(1), 109–126. https://doi.org/10.1016/j.finmar.2010.07.002 Kordela, D. (2011). Przejścia z NewConnect na rynek regulowany GPW – nowy trend czy naturalna droga rozwoju spółki?. Zeszyty Naukowe Uniwersytetu Szczecińskiego, 639(37), 473–482. Kordela, D. (2013). NewConnect – rynek giełdowy dla małych i średnich przedsiębiorstw. Warszawa: CeDeWu. D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 133 Kujawa, S., & Ostrowska, E. (2016). Analiza zdarzeń i jej zastosowanie w n fi ansach be - hawioralnych. Finanse, Rynki Finansowe, Ubezpieczenia, 4(82/2), 191–200. https:// doi.org/10.18276/frfu.2016.4.82/2-15 Kwok, J. K. H. (2020). Does switching trading venues create value? Evidence from Hong Kong. Journal of Asian Business and Economic Studies, 27(2), 209–222. https://doi. org/10.1108/JABES-09-2019-0080 Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica, 53(6), 1315– 1336. https://doi.org/10.2307/1913210 Le, H., & Gregoriou, A. (2020). How do you capture liquidity? A review of the literature on low-frequency stock liquidity. Journal of Economic Surveys, 34(5), 1170–1186. https://doi.org/10.1111/joes.12385 Leuz, C., & Verrecchia, R. E. (2000). e Th economic consequences of increased disclo - sure. Journal of Accounting Research, 38, 91–124. https://doi.org/10.2307/2672910 Lizińska, J., & Czapiewski, L. (2014). Performance of Polish IPO firms: Size and prot fi - ability effect. Gospodarka Narodowa, 1, 53–71. https://doi.org/10.33119/GN/100877 Lizińska, J., & Czapiewski, I. (2015). Determinanty underpricingu w Polsce i na innych rynkach wschodzących. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 386, 112–125. Ljungqvist, A. (2007). IPO underpricing. In: B. E. Eckbo (Ed.), Handbook of corporate na fi nce (pp. 375–422). North Holland: Elsevier. Lo, A., & Wang, J. (2000). Trading volume: Den fi itions, data analysis, and implica - tions of portfolio theory. Review of Financial Studies, 13(2), 257–300. https://doi. org/10.1093/rfs/13.2.257 Lou, X., & Shu, T. (2017). Price impact or trading volume: Why is the Amihud (2002) measure priced?. Review of Financial Studies, 30(12), 4481–4520. https:// doi.org/10.1093/rfs/hhx072 Loughran, T., & Ritter, J. R. (1997) The operating performance of firms conduct - ing seasoned equity oer ff ings. Journal of Finance, 52(5), 1823–1850. https://doi. org/10.1111/j.1540-6261.1997.tb02743.x Loughran, T., & Ritter, J. R. (2004). Why has IPO underpricing changed over time?. Financial Management, 3(4), 5–37. Ma, R., Anderson, H. D., and Marshall, B. R. (2016). International stock market liquid- ity: A review. Managerial Finance, 42(2), 118-135, doi:10.1108/MF-04-2015-0096 Mizerka, J., & Lizińska J. (Eds.). (2017). Pierwsze oferty publiczne w Polsce i na świecie. Kontrowersje wokół anomalii rynkowych. Warszawa: CeDeWu. Mortazian, M. (2021). Liquidity and volatility of stocks moved from the main market to the Alternative Investment Market (AIM). Asia-Pacic F fi inancial Markets , 29, 195–220. https://doi.org/10.1007/s10690-021-09344-6 Muscarella, C., & Piwowar, M. (2001). Market microstructure and securities values: Evidence from the Paris Bourse. Journal of Financial Markets, 4(3), 209–229. https:// doi.org/10.1016/S1386-4181(00)00022-7 Olbryś, J. (2103). Zastosowanie wybranych miar płynności aktywów kapitałowych na Giełdzie Papierów Wartościowych w Warszawie S.A. Zarządzanie i Finanse, 11(3/2), 65–77. Pagano, M., Panetta, F., & Zingales, L. (1998). Why do companies go public? An empirical analysis. Journal of Finance, 53(1), 27–64. https://doi.org/10.1111/0022-1082.25448 134 Economics and Business Review, Vol. 8 (22), No. 4, 2022 Panfil, M. (2013). Analiza porównawcza NewConnect i innych europejskich rynków al - ternatywnego systemu obrotu akcjami. Zeszyty Naukowe Uniwersytetu Szczecińskiego, 768(63), 347–368. Papaioannou, G. J., Travlos, N. G., & Viswanathan, K. G. (2003). The operating perfor - mance of firms that switch their stock listings. Journal of Financial Research, 26(4), 469–486. https://doi.org/10.1111/1475-6803.00069 Papaioannou, G. J., Travlos, N. G., & Viswanathan, K. G. (2009). Visibility ee ff cts and timing in stock listing changes: Evidence from operating performance. e Th Quarterly Review of Economics and Finance, 49(2), 357–377. https://doi.org/10.1016/j. qref.2007.09.007 Park, J. H., Binh, K. B., & Eom, K. S. (2016). The ee ff ct of listing switches from a growth market to a main board: An alternative perspective. Emerging Markets Review, 29, 246–273. https://doi.org/10.1016/j.ememar.2016.08.006 Pastusiak, R. (2011). Rynki alternatywne w Europie. Londyński Alternative Investment Market a NewConnect. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 174, 293–304. Perepeczo, A. (2010). Analiza zdarzenia i jej zastosowania. Zeszyty Naukowe Uniwersytetu Szczecińskiego, 632(33), 35–51. Podedworna-Tarnowska, D. (2018). Niedowartościowanie w procesie IPO spółek migrujących z rynku NewConnect na rynek główny Giełdy Papierów Wartościowych w Warszawie. Zarządzanie i Finanse, 16(4/1), 151–163. Podedworna-Tarnowska, D. (2020). Niedowartościowanie spółek debiutujących na rynku głównym i alternatywnym Giełdy Papierów Wartościowych w Warszawie. In P. Antonowicz, P. Galiński, P. Pisarewicz (Eds.), Perspektywa ekonomiczna, finansowa i prawna kreowania wartości w gospodarce (pp. 267–281). Gdańsk: Wydawnictwo Uniwersytetu Gdańskiego. Pomykalski, P., & Domagalski, M. (2015). IPO Underpricing and financial analysts’ forecast accuracy in Poland. Acta Universitatis Lodziensis, Folia Oeconomica, 1(310), 117–132. https://doi.org/10.18778/0208-6021.310.09 Radke, M. (2020). The position of NewConnect against the Alternative Markets of European countries. The impact of GDP on volatility in the indices and turn- over value. Journal of Economics and Management, 40(2), 109–131. https://doi. org/10.22367/jem.2020.40.06 Ritter, J. R. (1984). The “hot issue” market of 1980. e Th Journal of Business , 57(2), 215– 240. http://doi.org/10.1086/296260 Sarr, A., & Lybek, T. (2002). Measuring liquidity in financial markets . (IMF Working Paper, No. 02/232). Sanger, G. C., & McConnell, J. J. (1986). Stock exchange listings, firm value, and security market efficiency: The impact of NASDAQ. e Th Journal of Financial and Quantitative Analysis, 21(1), 1–25. https://doi.org/10.2307/2330987 Sieradzki, R. (2016). Niedowartościowanie pierwotnych ofert publicznych na przykładzie akcji notowanych na Giełdzie Papierów Wartościowych w Warszawie. (Niepublikowana rozprawa doktorska). Uniwersytet Ekonomiczny w Krakowie. Tomaszewski, J. (2012). Obowiązki informacyjne spółek notowanych na rynku NewConnect GPW S.A. w świetle rozwiązań europejskich giełdowych platform ASO. Prace Naukowe Wyższej Szkoły Bankowej w Gdańsku, 27, 115–127. D. Podedworna-Tarnowska, D. Kaszyński, Stock returns and liquidity ae ft r listing switch 135 Vismara, S., Paleari, S., & Ritter, J. (2012). Europe’s second markets for small companies. European Financial Management, 18(3), 352–388. https://doi.org/10.1111/j.1468- 036X.2012.00641.x Welch, I., & Ritter, J. (2002). A review of IPO activity, pricing and allocations. e Th Journal of Finance, 57(4), 1795–1828. https://doi.org/10.1111/1540-6261.00478 Włosik, K. (2017). Płynność przy wycenie akcji na Giełdzie Papierów Wartościowych w Warszawie. Ruch Prawniczy, Ekonomiczny i Socjologiczny, 79(2), 127–141. https:// doi.org/10.14746/rpeis.2017.79.2.11 Zarzecki, D., & Wołoszyn, A. (2013). The impact of the January ee ff ct on the IPO un - derpricing in Poland. Folia Oeconomica Stetinensia, 13(1), 121–135. https://doi. org/10.2478/foli-2013-0010 Zarzecki, D., & Wołoszyn, A. (2016). The impact of value and growth companies on IPO underpricing on the Polish capital market. Finanse, Rynki Finansowe, Ubezpieczenia, 4(82), 325–334. https://doi.org/10.18276/frfu.2016.4.82/2-28 Zhang, X. (2006). Information uncertainty and stock returns. Journal of Finance, 61(1), 105–137. https://doi.org/10.1111/j.1540-6261.2006.00831.x Zygmanowski, P. (2017). Determinanty rozwoju rynku akcji NewConnect. Warszawa: CeDeWu.
Journal
Economics and Business Review – de Gruyter
Published: Dec 1, 2022
Keywords: alternative market; main market; listing change; stock liquidity; G10; G14; G18; G30; G32