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This study aims to examine the potential of Sharia status as ex ante information to signal the quality of an issuing firm by improving the decision-making process of potential investors when assessing initial public offerings (IPOs) in an environment where information asymmetry is pronounced. Potential investors face challenges in evaluating and determining the true value of IPO issues, which inherently influences their decision-making. Consequently, this results in pronounced price fluctuations in IPO shares, leading to higher underpricing.

This study uses a sample of 350 IPOs listed on the Kuala Lumpur Stock Exchange (KLSE) between 2004 and 2021 to examine the signaling role of Sharia-compliance status. A three-model approach is used to ensure that the study's objectives are met. The first model investigates the effect of Sharia status on underpricing to determine whether the main beneficiary of such a signal is the investor or the issuer. The second model examines the effect of Sharia status on investor demand to determine if such a signal influences prospective investors' investment decision-making processes. The third model inspects the effect of Sharia status on investor divergence of beliefs to measure the signal's ability to reduce information asymmetry within the Malaysian IPO market.

The Malaysian IPO market relies heavily on the fixed-price mechanism, which exacerbates high information asymmetry, affecting potential investors' behavior, asset price formation and return generation on the first day of listing. The study results indicate that Sharia status does not have any signaling role in the Malaysian IPO market. This is because investors in the Malaysian market are driven by ex ante information that helps unveil relevant information that leads to capital gains. Furthermore, most new issues in the Malaysian IPO market fall under Sharia status, diluting the relevance of such information for prospective investors in determining profitable investments.

The findings highlight the challenges faced by issuing firms in estimating market demand due to limited premarket insights and the difficulties prospective investors face in identifying the quality of issuing firms. Efforts to provide more information on investor demand can reduce uncertainty and facilitate more informed decision-making.

This research stands as one of the pioneering efforts to provide an empirical explanation of the potential signaling influence of Sharia status in an emerging IPO market.

This study aims to investigate the moderating role of investor demand on the relationship between the investors' divergence of beliefs and the first-day initial public offering (IPO) return.

The study sample covers the period from 2010 to 2019 and consists of 117 IPOs that are priced using the fixed price and listed on the Malaysian stock exchange (Bursa Malaysia). This study employed both the ordinary least square (OLS) and the quantile regression (QR) methods.

Investor demand, proxied by the over-subscription ratio (OSR), plays a moderating role in increasing the effect of investors' divergence of beliefs on initial return, and the moderation effects vary across the quantile of initial return. Pure moderation effects are observed at the bottom and top quantiles, suggesting that investor demand is necessary for divergence of beliefs to influence IPO initial return. However, at the middle quantile of initial return, investor demand is a quasi-moderator. That is, the OSR not only moderates the relationship between the divergence of beliefs and initial return but also has a positive effect on the initial return.

Investors' excessive demand for an IPO issue exacerbates the IPO under-pricing issue induced by a divergence of beliefs amongst investors, thus rendering greater equity market inefficiency.

To the authors' knowledge, this study is amongst the first to empirically investigate the moderating role of investor demand on the investors' divergence of beliefs and IPO initial return relationship.

Empirical examinations of initial public offering (IPO) initial returns often rely heavily on linear regression models. However, these models can prove inefficient owing to their susceptibility to outliers, a common occurrence in IPO data. This study introduces a machine learning method, known as random forest, to address issues that linear regression may struggle to resolve.

The study’s sample comprises 352 fixed-priced IPOs from the year 2004 until 2021. A unique aspect of this research is its application of the random forest method. The accuracy of random forest in comparison to other methods is evaluated. The findings indicate that the random forest model significantly outperforms other methods in all of the evaluated aspects.

The variable importance measure indicates that investors’ demand, divergence of opinion among investors and offer price are the most crucial predictors of IPO initial returns. These determinants hold particular significance due to the widespread use of the fixed-price method in Malaysia, as this method amplifies the information asymmetry in the IPO market.

To the best of the authors’ knowledge, this study is among the pioneering works in Malaysian literature to apply the random forest method to address the constraints of conventional linear regression models. This is achieved by considering a more extensive array of factors and acknowledging the influence of outliers. Additionally, this study adds value to Malaysian literature by ranking and identifying the ex-ante information that best signals the issuing firm’s quality. This contribution facilitates prospective investors’ decision-making processes and provides issuing firms with effective means to communicate their value and quality to the IPO market.

The purpose of this paper is to examine the effects of prestige signals measured by the reputations of the underwriter, auditor and board size on the heterogeneity of investor belief about the true value of IPO in the Malaysian IPO market.

This study employs a sample of 281 IPOs issued between January 2000 and December 2015. The relationship between prestige signals and investor heterogeneity, measured by first-day price range of IPOs, is analysed using cross-sectional regression and quantile regression technique.

Of the three prestige signals, the findings show that only underwriter reputation and board size have significant negative relationships with IPO first-day price range. This implies that IPOs underwritten by reputable underwriters and issuing firms with larger board members have lower heterogeneity of opinion among investors. The findings also show that underwriter and auditor reputations have negative relationship with IPO initial return, suggesting that these prestige signals help to reduce IPO under-pricing, which is a direct cost of raising capital for the issuing firm. Furthermore, the results indicate that offer price, initial return, over-subscription ratio and private placement are associated with higher first-day price range. However, the findings on offer size suggest that larger IPO offer size is associated with lower first-day price range. Overall, the findings suggest that firm’s prestige signals reduce opinion heterogeneity among investors and that lower investors’ heterogeneity leads to lower IPO under-pricing cost for issuing firms.

Despite the importance of underwriter, auditor and board member reputations in signalling firm’s quality and reducing the level of information asymmetry of the listing firm’s issues, research on the effects of prestige signals on investor heterogeneity remains unexplored. This study investigates the role of prestige signals in influencing investors’ heterogeneity in Malaysia. The authors conjecture that underwriter, auditor and board member with higher reputations are associated with lower levels of opinion heterogeneity among IPO investors.

The purpose of this paper is to examine whether initial public offering (IPO) over-subscription is a function of firm’s prestige signals conveyed by third parties with reputational capital such as underwriter, auditor and independent non-executive board member.

The relationship between prestige signals and over-subscription ratio (OSR) of IPOs is analysed using a cross-sectional regression based on a sample of 393 IPOs issued between January 2000 and December 2015.

The results indicate that IPOs underwritten by reputable underwriters have lower OSR than those underwritten by non-reputable underwriters. While issuer engages reputable underwriter to certify firm quality to reduce information asymmetry, the action brings with it lower initial returns for its IPO. Investors interpret the signal conveyed by issuer’s choice of underwriter from under-pricing perspective and respond accordingly by reducing IPO demand. This implies that investors regard under-pricing as a more valuable signal than firm quality signal associated with underwriter reputation. The findings also indicate that over-subscription increases in IPOs that have above average initial returns and higher institutional participation. Issuing firms that go public in a period of high IPO volume are associated with low OSR.

This is the first paper to examine the relationship between the prestige signals and OSR of IPOs in the Malaysian context.

The purpose of this paper is to investigate the impacts of stock market and banking sectors development on a country’s efficiency in transforming its innovation input into output.

This study employs a generalized method-of-moments panel estimator to examine the role of stock market and banking development in influencing innovation efficiency.

Findings show that a country’s stock market development is positively related to its innovation efficiency ratio. Countries with more developed stock markets have relatively higher efficiency in transforming innovation input into innovation output than those with less developed stock markets. There is no evidence that innovation efficiency is influenced by banking sector development. However, when stock market and banking sectors are modeled together, while stock market development retains its positive influence, the findings indicate that banking sector exerts negative impact on innovation efficiency.

The findings provide useful insights to guide policy decisions for a country’s innovation agenda in enhancing its innovation performance. The findings imply that stock market development should be embraced as one of the key policy areas in order for a country to be more efficient in transforming its innovation input into innovation output.

This paper provides first evidence using data sourced from Global Innovation Index report, first available in 2007 and published by Cornell University, INSEAD and the World Intellectual Property Organization.

The main purpose of this study is to examine the disclosure of earnings forecasts in firms' prospectuses to explain investor demands or, in other words, oversubscription rates of Malaysian initial public offerings (IPOs).

Ordinary least squares and robust methods were used to examine cross-sectional data comprising 466 fixed-price IPOs reported for the period from January 2000 to February 2020 on Bursa Malaysia.

The results showed that IPOs with earnings forecasts obtained higher oversubscription rates than those without earnings forecasts. IPOs with earnings forecasts provide value-relevant signals to prospective investors about the good prospects of firms, resulting in an increase in the demand for IPO shares. For the IPO samples listed during the global financial crisis (GFC) period, IPOs with earnings forecasts had negative impacts on the oversubscription rates. These results were robust to quantile methods and the two-stage least squares method.

The research findings provide fresh information for investors regarding the importance of earnings forecasts as a trustworthy signal of a firm’s quality when making share subscription decisions.

The regulator is advised to encourage issuers to include earnings forecasts in their prospectuses since such forecasts help to increase the demand for IPOs.

This study contributes to the literature by offering empirical evidence regarding the signalling impact of earnings forecast disclosures on investor demands for Malaysian IPOs. Moreover, this study provides evidence demonstrating the impact of earnings forecast disclosures on oversubscription rates of Malaysian IPOs during the GFC period.

This paper aims to review, discuss and synthesize the literature focusing on the Indian initial public offering (IPO) market. Understanding the Indian IPO market can help answer broader corporate finance questions. The growing number of IPOs in the Indian context, coupled with the increasing importance of the Indian economy in the global market, makes this review an essential topic.

The systematic literature review methodology was adopted to review 111 papers published between 2002 and 2021. The authors used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach during the review process. Additionally, the authors use a bibliometric review methodology to examine the pattern and trend of research in this area of interest. Furthermore, the authors conduct a critical review and synthesis of the top 20 papers based on citations. The authors also use a co-citation network and manual content analysis method to identify key research themes.

This review helps in identifying major themes of research in this area of interest. The authors find that majority of the research has focused on IPO performance whereas post-IPO performance needs critical attention as well. The authors develop a comprehensive framework and future research agenda based on their discussion.

Meta-analysis of the literature can be conducted to gain better insights into the findings of prior studies.

This review paper develops a comprehensive overview on Indian IPO market which can be of interest not only to Indian scholarship. India as an economy is increasingly gaining attention at the global level. Hence, the future research objectives as illustrated in the study can be of interest for the global scholarship also.

To the best of the authors’ knowledge, this is the first comprehensive review paper that examines, synthesizes and outlines the future research agenda on Indian IPO studies. This review can be useful for researchers, business policymakers, finance professionals and anyone else interested in the Indian IPO market.

Boussinesq approximation is widely used in solving natural convection problems, but it has severe practical limitations. Using Boussinesq approximation, the temperature difference should be less than 28.6 K. The purpose of this study is to get rid of Boussinesq approximation and simulates the natural convection problems using an unsteady compressible Navier-Stokes solver. The gravity force is included in the source term. Three temperature differences are used namely 20 K, 700 K and 2000 K.

The calculations are carried out on the square and sinusoidal cavities. The results of low temperature difference have good agreement with the experimental and previous calculated data. It is found that, the high temperature difference has a significant effect on the density.

Due to mass conservation, the density variation affects the velocity distribution and its symmetry. On the other hand, the density variation has a negligible effect on the temperature distribution.

The present calculation method has no limitations but its convergence is slow. The current study can be used in fluid flow simulations for nuclear power applications in natural convection flows subjected to large temperature differences.

This work aims to describe the physical and numerical modeling of a CFD solver for hypersonic flows in thermo-chemical non-equilibrium. This paper is the second of a two-part series that concerns the application of the solver introduced in Part I to adaptive unstructured meshes.

The governing equations are discretized with an edge-based stabilized finite element method (FEM). Chemical non-equilibrium is simulated using a laminar finite-rate kinetics, while a two-temperature model is used to account for thermodynamic non-equilibrium. The equations for total quantities, species and vibrational-electronic energy conservation are loosely coupled to provide flexibility and ease of implementation. To accurately perform simulations on unstructured meshes, the non-equilibrium flow solver is coupled with an edge-based anisotropic mesh optimizer driven by the solution Hessian to carry out mesh refinement, coarsening, edge swapping and node movement.

The paper shows, through comparisons with experimental and other numerical results, how FEM + anisotropic mesh optimization are the natural choice to accurately simulate hypersonic non-equilibrium flows on unstructured meshes. Three-dimensional test cases demonstrate how, for high-speed flows, shocks resolution, and not necessarily boundary layers resolution, is the main driver of solution accuracy at walls. Equally distributing the error among all elements in a suitably defined Riemannian space yields highly anisotropic grids that feature well-resolved shock waves. The resulting high level of accuracy in the computation of the enthalpy jump translates into accurate wall heat flux predictions. At the opposite end, in all cases examined, high-quality but isotropic unstructured meshes gave very poor solutions with severely inadequate heat flux distributions not even featuring expected symmetries. The paper unequivocally demonstrates that unstructured anisotropically adapted meshes are the best, and may be the only, way for accurate and cost-effective hypersonic flow solutions.

Although many hypersonic flow solvers are developed for unstructured meshes, few numerical simulations on unstructured meshes are presented in the literature. This work demonstrates that the proposed approach can be used successfully for hypersonic flows on unstructured meshes.