Initial Public Offering Stocks Research Articles

Reviewing Internal Variables on the Level of Underpricing of IPO Shares (Observation of the Company Go Public on IDX 2021-2022)

This research study was held to examine internal variables that can determine the effect of stock underpricing levels when conducting an IPO (Initial Public Offering) on the IDX (Indonesia Stock Exchange) 2021-2022. Internal factors include ROE and ROA. Research is quantitative and uses secondary data, explanatory research study type, using methods by purposive sampling when determining samples. The novelty of the study can be seen from the overall data and the latest samples used by 64 issuers and the periods used, namely 2022 and 2021. The study used hypothesis testing methods, including multiple linear regression analysis through the help of Eviews (Econometric Views). The source of data used in this study is prospectus data issued by companies or issuers that go public with underwriters. The calculation results obtained partially produce ROE and ROA variables have a significant influence on the level of underpricing in IPO shares, and simultaneous results show that ROE and ROA variables together have a significant effect on the level of underpricing of IPO shares. The result of a positive value coefficient is obtained at the IPO stock underpricing level, then the ROE variable has a negative coefficient and the ROA coefficient is positive, this is interpreted by the increase in the ROE value, the stock underpricing level will decrease and apply to vice versa, and for the ROA variable that has a positive coefficient means that the more the ROA value increases, the stock underpricing level will also increase and vice versa.

Analysis of Abnormal Return of Issuer’s Stock after IPO during the Covid-19 Pandemic

The Covid-19 pandemic based on Presidential Decree Number 12 of 2020 was declaredon April 13, 2020. During this Pandemic, many companies offer their shares to the public or known as Initial Public Offering (IPO). This study aims to find out the highest abnormal returns of the issuers' stock after the IPO during the Covid-19 Pandemic. The sample used in this study was 70 companies that IPO on the IDXafter pandemic status was declared in Indonesia, namely from April 15, 2020-November 25, 2021. This research is a descriptive quantitative research anddescriptive statistical analysis techniques was used to calculate abnormal returns and cumulative abnormal returns of each stock. The results showed that cumulatively, the highest abnormal return of 70 stocks within 20 months was owned by TECH shares in the technology sector with a cumulative abnormal return value of 23,562. Meanwhile, the lowest value is owned by DEPO shares in the consumer cyclicals sector with a cumulative abnormal return of 0.624. The results of this study can be used as considerationby investors who want to invest in IPO stocks during prolonged outbreaks such as the Covid-19 Pandemic.

Underpricing or Overvaluation? Theoretical Review of Initial Public Offering Phenomenon

The abnormal initial return of Initial Public Offerings (IPOs) has become an interesting financial phenomenon that attracts many researchers’ interest. This phenomenon has become more attractive because IPOs have increased during the pandemic since 2021. This study investigates whether the positive initial performance of IPO stock led to underpricing or overvaluation in a broader context in the form of literature reviews. After elaborating and analyzing several related studies, theories and empirical research in the literature, this research finds that the aftermarket has a lower performance than the initial one. It shows that abnormal initial returns tend to be caused by investors’ overvaluation and overreaction instead of underpricing.

Are Korea individual investors irrational in initial public offering (IPO) market? An explanation from the winner’s curse perspective

Individual investors are often regarded as irrational sentiment investors whose investment behaviour is affected by psychological factors. This study measures the actual investment return of individual investors who participated in initial price offering (IPO) stock investment in the Korean market from the short-term and long-term perspective and investigates the relationship with IPO characteristics that affect the investment sentiment of individual investors. Even though the underpricing of IPO stocks on the first day of listing on average reached 31% over the past 13 years, individual investors in the Korean stock market earned very little actual return on IPO stock investment. The market-adjusted return on IPO stock investment on the first day was about −0.5%, and even if they held IPO stocks for one year after listing, it was only 3.4%. The so-called winner’s curse, in which individual investors are allocated relatively many overvalued stocks appears to be present in the Korean IPO market. The allocation of IPO stocks by individual investors depends on several factors that reflect individual investors’ sentiment, such as past performance of previous IPOs, past industrial returns, institutional investors’ investment intent, offering size, an upward revision of the offer price, and issuing firm’s financial soundness. It was found that the higher the individual allocation rate, the lower the short-term investment return on the first trading day, confirming the winner’s curse risk of individual investors. However, in the long run, a reversal of returns was observed, in which the long-term returns of IPO stocks with high individual allocation rates rose. In order to mitigate the winner’s curse risk, it is desirable to reform IPO pricing mechanisms and allocation rules in a way that reduces the asymmetry of information between institutional and individual investors and reflects the subscription demand of individual investors.

Ambiguous Signals and Information Asymmetry in the Initial Public Offering Process: Examining Ownership Concentration, Process Time, and Underpricing

Initial public offerings (IPOs) represent an important stage of development for many firms as they try to gain access to the resources needed for growth and development. Due to the information asymmetry that accompanies the process, there is extensive research examining what factors might signal quality to potential investors such that the IPO might be more optimally valuated and priced. Herein, we hypothesize and empirically explore how a mixed or ambiguous signal about a firm—the signal of ownership concentration in this case—might be overcome with more opportunities for information disclosure and, thus, lessen underpricing; IPO stocks tend to be underpriced (i.e., the offer price of a stock is lower than the inherent market value), which means that owner’s “leave money on the table.” Using a generalized structural equation model of data on 601 U.S. IPO firms, we find support for our model by demonstrating that longer IPO process times (i.e., days from the IPO firm’s filing date to the actual issue date)—representing opportunities to disclose and disseminate information—act as a mediator between ownership concentration and underpricing. Further, we show that the age of the firm also influences this process model arguing that more historical data and other information is more readily available to the potential investor with increased firm age. Overall, our study contributes to the literature by demonstrating how more disclosure and dissemination of relevant information might reduce asymmetries associated with more ambiguous or difficult-to-interpret signals and improve outcomes.

The Return on IPO Stocks during the COVID-19 Pandemic in Indonesia

Abstract. Conducting an initial public offering (IPO) during the COVID-19 pandemic is not easy due to the current high level of economic uncertainty. This study aims to examine the effect of the COVID-19 pandemic on the initial return on IPO shares in Indonesia. In the study, a cross-sectional regression was applied, using a sample of 51 companies that conduct IPOs. It was found that the fear index over the COVID-19 pandemic negatively affected the initial return. The higher the fear index, the lower the return on IPO stocks on the first listing day. The results therefore demonstrates that the fear of COVID-19 influenced the IPO market return in Indonesia. This study extends the literature on the COVID-19 pandemic, especially on the initial return on IPOs. Practically, this research also provides insight into the issuers regarding the appropriate timing of IPOs during the crisis, particularly for investors who wish to buy IPO shares during an uncertain time. Policymakers are expected to mitigate the cases and deaths of COVID-19 in Indonesia, which may reduce investors’ fear related to COVID-19. This paper's limitation is that it only examines data from 2020, as this was the year in which COVID-19 first announced. Future research could include the short-term and long-term performance of IPOs, and also broaden the sample area to a larger region. Keywords: Initial return, IPO, COVID-19, fear index, Indonesia

Initial Public Offerings and Local Housing Markets

This study explores the link between corporations’ initial public offering (IPO) activities and the housing markets in the MSAs where the IPO firms are headquartered. Using a sample of 4,500 U.S. IPOs occurring from 1990 to 2018, a period covering the tech bubble years and the 2007–2008 financial crisis, we examine the existence and magnitude of the link between IPOs and housing, and related hypotheses including the short-term expectations effects, the wealth effects after the IPO lock-up expiration dates, and the long-term effects. Our results provide strong support to these hypotheses. The effects are stronger during the tech-bubble years. In addition, the results are to some extent driven by IPOs in traffic-congested and/or low-affordability cities, and the effects are generally amplified by local housing supply rigidity and IPO stock performance. We find that the overall impact of IPOs on the housing market is economically significant with the most prominent influence linked to the changes in short-term expectations.

Investor Sentiment, Market Volatility, and IPO Initial Returns

This research seeks to determine the impact of investor sentiment and market volatility on IPO initial return when an issuer conducts an Initial Public Offering (IPO). This research lasted ten years, from 2009 to 2020, with a total issuer of 237 conducting Initial Public Offerings (IPOs) on the Indonesia Stock Exchange. The total number of issuers conducting an initial public offering (IPO) met the purposive sampling criteria is 285. Multiple linear regression analysis, with control variables such as Gap of Days, Firm Age, IPO Size, and Firm Size, is used to determine the effect of Investor Sentiment and Market Volatility on IPO Initial Returns. The findings showed that Investor Sentiment and Market Volatility positively affected the IPO Initial Return during the study period. This research aims to increase investor awareness of the importance of IPO stock price, increasing the initial return in the future. In Indonesia, Otoritas Jasa Keuangan (OJK) plays a critical role in policies that facilitate Indonesian investors' monitoring of the volatility of stock price changes in the market.JEL: M2, M21

Do Revenues Matter More Than Earnings for Initial Public Offerings?

We demonstrate that investors in initial public offering (IPO) firms value revenues and that the number of U.S. Securities and Exchange Commission (SEC) revenue recognition comment letters issued on the S-1 registration statement are positively associated with reported revenues. We also find that IPO managers report revenues opportunistically in the fiscal year just prior to the offer. In additional analysis, we find that discretionary revenues are associated with significantly higher first day IPO stock returns but significantly lower 1 year stock returns. Our results are consistent with the incentives of managers to report revenues opportunistically outweighing the higher monitoring and regulatory scrutiny pre-IPO.

Modeling and Estimation of Cumulative Abnormal Return using VECM

This paper examined how firm-level idiosyncratic risk varies over time. It affected initial public offering (IPO) in the presence of pump-and-dump and flipping trends during the early trading of IPO stocks in the Indonesia Stock Exchange. The paper used the IPO data taken from 181 companies during the year 2015-2019. It revisited the relationship between Cumulative Abnormal Return thirty-days (CAR30D) and Cumulative Abnormal Return five-days (CAR5D) and the Characteristics (IPO Floating shares, IPO Fund and Price) and Macroeconomics Condition (Inflation rate). It also used the cointegration analysis and VECM model. The paper found that Both LnFloat and LnPrice had causal evidence in the long-run causality or short-run with Cumulative Abnormal Return thirty days (CAR30D). We also noted that idiosyncratic risk exposure depends on IPO characteristics. It was crucial for firms going public in hot-issue markets, undervalued IPOs, and high idiosyncratic-risk issues. The model suggested that those series should cointegrate firstly. However, the variable of LnIPOFund had causal evidence in the short-run causality only.

Stock price prediction using multiple valuation methods based on artificial neural networks for KOSDAQ IPO companies

ABSTRACT It is difficult to predict future payoffs for initial public offerings (IPOs), since the multiple valuation method used to determine IPOs’ prices provides estimates by reflecting current sentiments in specific market environments. As our model reflects accounting information and stock price, we find that the mean absolute percentage error that verifies the accuracy of IPO stock valuation improves return on investment by 15% to 20%. This can help shareholders and investors accurately estimate stock prices and engage in efficient investment decision-making, while contributing to fintech by applying machine learning to traditional techniques to analyse investment opportunities and optimise trading strategies.

Theoretical Review of Effect of Firm Specific Factors on Performance of Initial Public Offering Stocks at the Nairobi Securities Exchange in Kenya

During the period 1994 to 2020, a total of 18 firms in Kenya floated 16,530,781,060 shares at the Nairobi Securities Exchange (NSE) under Initial Public Offerings (IPOs) raising over Kshs 91 billion. These stocks were significantly over-subscribed with the highest hitting 830%. The NSE became fully automated in 2006. Similarly, in Africa between 2010 and 2019 there were a total of 215 IPOs raising over Kshs 1.6 trillion. This could be explained by divergence of opinion hypothesis. The initial returns were positive. However, in the long run, most of the firms underperformed. This under performance leads to losses incurred by investors and possible collapse of brokerage and investment firms leaving investors with a bitter taste. This study will undertake to establish the effects of firm specific factors on IPO stock performance at the NSE in Kenya. The specific objectives will be: to establish the effect of firm size on performance of IPO stocks at the NSE in Kenya, to determine the effect of age of firm on performance of IPO stocks at the NSE in Kenya, to evaluate the effect of firm board composition on performance of IPO stocks at the NSE in Kenya, to establish the effect of firm ownership structure on performance of IPO stocks at the NSE in Kenya, and to analyze the moderating effect of automation on the firm specific factors and performance of IPO stocks at the NSE in Kenya. The study will be built upon major theoretical streams: Random Walk theory, Winners curse theory, Dow Theory, Signaling theory and Agency theory and contextualize them to firm specific factors and performance of IPO stocks. More studies have previously been undertaken on the pricing of IPO at the NSE in Kenya and the few that studied on performance of IPO stocks at the NSE in Kenya have provided mixed findings depending on the methodology used. None of the studies as far as research has shown have considered the automation of NSE in Kenya as a moderating effect of performance of IPO stocks. The sample size will be the same as population of 18 IPO firms between 1994 and 2020 with 8 IPOs during pre-automation and 10 IPOs post-automation period. This will be a longitudinal and event study that will adopt a descriptive study design. Data will be analyzed using the Econometric Views (Eviews). Hausman test, Augmented Dickey Fuller (ADF) test and other diagnostic tests will be applied to the panel data. The Capital Assets Pricing Model (CAPM) and the Nairobi 20 Share Index will be used as the benchmarks of performance of IPO stocks.

A Machine Learning Portfolio Allocation System for IPOs in Korean Markets Using GA-Rough Set Theory

An initial public offering (IPO) is a type of public offering in which a company’s shares are sold to institutional and individual investors. While the majority of studies on IPOs have focused on the efficiency of raising capital and price adequacy in IPOs, studies on portfolio allocation strategies for IPO stocks are relatively scarce. This paper develops a machine learning investment strategy for IPO stocks based on rough set theory and a genetic algorithm (GA-rough set theory). To reduce issues of information asymmetry, we use nonfinancial data that are publicly available to individual and institutional investors in the IPO process. Based on the rule sets generated from the training sets, we conduct 120 tests with various conditions involving the target days and the partition of the training and testing sets, and we find excess returns of the constructed portfolios compared to the benchmark portfolios. Investors in IPO stocks can formulate more efficient investment strategies using our system. In this sense, the system developed in this paper contributes to the efficiency of financial markets and helps achieve sustained economic growth.

Clusters of investors around initial public offering

The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPOs) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki Stock Exchange by using a statistically validated network method to infer investor links based on the co-occurrences of investors’ trade timing for 69 IPO stocks. Our findings show that a rather large part of statistically similar network structures form in different securities and persist in time for mature and IPO companies. We also find evidence of institutional herding.

Price stabilization, short selling, and IPO secondary market liquidity

Prior research shows that failures to deliver, which commonly occur around initial public offerings (IPOs), typically result from underwriter price stabilization. Additionally, investors often establish short positions in IPO stocks that are unrelated to underwriter price stabilization. We study the relation between failures to deliver, short sales, and IPO trading costs. We find that failures to deliver are associated with greater liquidity, especially for IPOs likely to receive underwriter price support. However, contrary to prior research that finds that short selling is associated with greater liquidity, we find that short selling is negatively correlated with liquidity for IPO stocks with strong investor demand.

Clusters of Investors Around Initial Public Offering

The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPO) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki Stock Exchange by using a statistically validated network method to infer investor links based on the co-occurrences of investors' trade timing for 69 IPO stocks. Our findings show that a rather large part of statistically similar network structures form in different securities and persist in time for mature and IPO companies. We also find evidence of institutional herding.

Using Pre-Listing Information to Mitigate Initial Public Offerings’ Long Run Underperformance: Evidence from Sri Lanka

The main channel of information dissemination for initial public offerings (IPO) in the pre-listing stage is the prospectus. Auditor fee and director emoluments are two types of information that investors know about in advance through the prospectus. Industry and media publicity are also in the focus of investors in the pre IPO stage. This study inquires whether such information can be used to form successful trading strategies in the long run. IPO stock portfolios have been constructed based on the above four types of information and their returns have been tested using four popular asset pricing models to answer the above question. The findings confirm that long only strategies are successful with regard to all four types of information while long and short strategies are proved to be a failure. The findings also reveal that portfolios consisting of non-finance stocks, stocks with high media coverage, high audit fees and high director fees tend to provide the highest returns compared to other IPO stock portfolios. Hence, this study provides useful insights to investors, regulators and other professionals in the Sri Lankan capital market.

People have the power: post IPO effects of intellectual capital disclosure

We study the effects of disclosure practices regarding non-financial information in Initial Public Offering (IPO) prospectuses on the post IPO stock performance. Previous literature is in short supply of evidences regarding the effect of Intellectual Capital (IC) disclosure on the long-run IPO performance and it also provides inconsistent results, possibly due to the different IC classifications that are employed and to a variety of omitted concurrent factors which could befog the effect of the IC disclosure. In this paper, we disengage from any ready-made classification of IC and we shed light on the effects that unbiased IC information exert on the post IPO stock performance. In particular, we consider all the IC information that is provided in the listing prospectus of a sample of firms recently listed on Borsa Italiana by considering a series of 87 variables, as suggested by (Cordazzo J Intellect Cap 8(2):288-305, 2007) and we apply a principal component analysis to such information thus overcoming the subjectivity of any possible classification. The revealed IC components are then included in a multivariate analysis explaining the long-term IPO stock performance. We also include a wide set of variables to control for the short-term performance, the quality of the firm and other factors which could blur the effect of IC disclosure on the long run performance. Our empirical evidences show that information regarding the human resources and the information technology activities disclosed in the IPO prospectus continue to exert their positive effect on the behavior of secondary market investors in the 12 months that follow the IPO. Moreover, the information regarding the human resources is positively linked to the 36 months’ performance as well. Such a result underlines the key role that people have in the perception of a firm’s value in the IPOs setting, thus confirming that human resources are recognized as being very important contributors to the competitive advantage of corporations.

Exploring the Existence of Short-run Initial Public Offering (IPO) Underpricing at Three Different Stock Exchange Markets in Japan

This study conducted the examination of the short-run performance of IPO stocks in the Japanese market by measuring daily AAR/CAAR of sample IPO stocks.. The study did so, in order to detect the positive initial abnormal return of sample IPO stocks as well as the short-run IPO underpricing that was observed by Ibbotson (1975) and McDonald and Fisher (1972) in the US market, and Chang (2011) in the Taiwanese market. The finding was that unlike findings in prior research, this study did not discover the positive initial abnormal returns for sample IPO firms in the Japanese market on the event day with statistical significance. Thereby, the short-run IPO underpricing did not occur in the Japanese market and it is inferred that offer prices of IPOs in the Japanese market are priced rationally, reflecting all available pieces of information at the time of offering. The implication of this finding for Efficient Market Hypothesis is that in the short-run, market efficiency holds well for the Japanese market. Findings from the examination on short-run performance of IPO stocks in the Japanese market has enabled this study to answer the research question: Does short-run IPO underpricing exist at stock exchange markets in Japan? The answer is, the short-run IPO underpricing did not exist.

The 2017 State New Economy Index: Benchmarking Economic Transformation in the States

The purpose of the State New Economy Index is to measure states’ economic structure. Unlike other reports that assess state economic performance or state economic policies, this study focuses more narrowly on a simple question: To what degree does the structure of the 50 state economies match the ideal structure of the innovation-driven New Economy? For example, we know that a defining characteristic of the New Economy is that it is global. Therefore, the Index uses a number of variables to measure state economies’ degrees of global integration. This edition of the Index builds on seven prior editions, which were published in 1999, 2002, 2007, 2008, 2010, 2012, and 2014. It now uses 25 indicators, which are divided into five categories that best capture what is important about the New Economy: 1. Knowledge jobs: Indicators measure employment of IT professionals outside the IT industry; jobs held by managers, professionals, and technicians; the educational attainment of the entire workforce; immigration of knowledge workers; migration of domestic knowledge workers; worker productivity in the manufacturing sector; and employment in high-wage traded services. 2. Globalization: Indicators measure foreign direct investment; export orientation of manufacturing and services; and the share of each state’s output that goes to high-tech goods and services exports. 3. Economic dynamism: Indicators measure the degree of business churn (i.e., the percentage of new business start-ups and failures); the number of fast-growing firms (businesses listed in the Inc. 5000 index); the number and value of initial public stock offerings (IPOs) by companies; and the number of individual inventor patents granted. 4. The digital economy: Indicators measure Internet and computer use by farmers; the degree to which state governments use information technologies to deliver services; adoption rates and speed of broadband telecommunications; and use of information technology in the health care system. 5. Innovation capacity: Indicators measure the number of jobs in high-tech industries such as electronics manufacturing, telecommunications, and biomedical industries; the number of scientists and engineers in the workforce; the number of patents granted; industry investment in research and development; non-industry investment in research and development; movement toward a clean energy economy; and venture capital investment.