Potential Investors Research Articles

The Impact of Foreign & Domestic Investment on Export Processing Zones in Bangladesh: An Auto Regressive Distributed Lag (ARDL) Approach

Foreign Direct Investment (FDI) is a major force behind the integration of the global economy and has the potential to boost economic development in both investing and those receiving the investment. The majority of the study focuses on the influence of FDI on Bangladesh’s economic growth. A number of scholars have also looked at how FDI affects trade, domestic investment and other economic sectors. But surprisingly less research has been done on the effects of FDI on Bangladesh's export processing zones (EPZs). This study tries to investigate the impact of foreign and domestic investment on exports of EPZs between 2011-2022. To investigate EPZs export, this study used the Auto Regressive Distributed Lag (ARDL) approach. The Wald test was used to determine the direction of causation. The ARDL estimate shows that investment, GDP and FDI all have a positive correlation with rising EPZ export. The coefficient for FDI inflows is 0.15% which suggests that if FDI inflows raise by 1%, EPZ export will grow by 0.15% while all other factors stay constant. It also shows that a 1% increase in investment leads to 1.32% quicker growth in EPZ exports, assuming all other factors remain constant. The Wald test demonstrates the bilateral causal relationship between EPZ export & FDI and the unidirectional relationship between EPZ export & GDP. Therefore, Bangladesh must take immediate measures to protect potential foreign investors in order to provide a welcoming environment so that they can feel their contribution in the Bangladeshi business industry is respected.

Evolving nature-based solutions for Australia’s Indigenous estate in 2024 – opportunities and challenges

Globally, there is growing interest and potential for investment in Nature-based Solutions (NbS) to protect, manage or restore ecosystems through incentive schemes including Payment for Ecosystem Services (PES), Nature Repair, Carbon Markets, Common Asset Trusts. Collectively, these NbS markets establish interchangeable mechanisms to help address biodiversity and climate crises, as well as socio-economic issues concerning many Indigenous Peoples and Local Communities (IPLCs). IPLCs manage and/or own almost 32% of the world’s land area through customary and community-based tenure arrangements. Since 2000 several PES schemes have been implemented in Australia. These schemes have been overwhelmingly implemented as public-good expenditure, with governments providing ~90% of total funding. Indigenous people have either the legal right to run or veto a carbon market or nature repair project over 57% of the Australian land mass, increasing to 63% in savanna and 85% in desert regions. Here we critically assess opportunities and challenges for Australia’s Indigenous estate associated with existing and emerging NbS market approaches, especially the Commonwealth’s current Savanna Fire Management (SFM) and Human Induced Regeneration methods, evolving Integrated Farm & Land Management (IFLM) and Blue Carbon methods, and proposed Nature Repair (NR) market. To date, Indigenous NbS interests have focused especially on SFM across northern Australia, with prospective opportunities especially for IFLM and NR markets. Most available schemes focus on remediation of degraded lands and seas, ignoring cost-effective investment opportunities to maintain habitats and ecosystems in less-degraded condition. Government-supported Common Asset Trusts can provide effective models for governance of stewardship schemes relevant to on-going care for relatively intact ecosystems. In Discussion we summarise key methodological, institutional, and policy opportunities and challenges for constructive Indigenous engagement with developing NbS markets. Our purpose is to provide an Indigenous land and sea management context to inform development of rapidly evolving NbS markets in Australia.

Sustainable Development Strategy Based on Value-Addedin the Fisheries Sector: Study on the Kangean Islands, Sumenep Regency, Indonesia

Objective: Kangean Islands is a group of small islands in Sumenep Regency, East Java Province, Indonesia, which is administratively divided into three sub-districts, namely Arjasa District, Kangayan District, and Sapeken District. This archipelago has very large fisheries potential as seen from its contribution to the Gross Regional Domestic Product (GRDP) of Sumenep Regency, but the utilization of the fisheries sector in this archipelago is still carried out traditionally and tends to be exploitative. This study aims to see the level of sustainability of fisheries sector management and recommend fisheries resource management strategies, in order to increase the economic added value of the fisheries sector and maintain the sustainability of fish resources and the environment in the archipelago. Method: The analytical method used to analyze the degree of sustainability in fisheries resource management in the Kangean Islands is Rapid Appraissal for Fisheries (RAPFISH) with the Multi-Dimensional Scaling (MDS) ordination technique. While the analytical tool used to compile a hierarchy of fisheries sector development strategies to increase economic added value is the Analytical Hierarchy Process (AHP). Results and Discussion: The results of the sustainability analysis in the management of the fisheries sector found that, of the five aspects identified, the results showed that the financial aspect and infrastructure aspect had the category of "Sustainable Sustainability", with values of each aspect of 63.113 and 53.885. While the other three aspects, namely: Human Resources (HR) Aspect, Natural Resources Aspect, and Social Aspect are included in the category of "Less Sustainable". Meanwhile, based on the results of the analysis of the hierarchy of fisheries sector development policies, it shows that the most priority policy to be carried out in the development of a sustainable fisheries sector is the "identification of investment potential and opportunities" program with a priority value of 46%. Furthermore, the strategy that must be chosen is to map the potential of the fisheries sector with a limiting value of 21%. With a Rater Agreement value strength of 0.472727 or 47%, it means that the informants agree in providing an assessment on the paired comparison questionnaire, in determining problems and strategies in the development of the fisheries sector in the archipelago.

Desirability of Sukuk as a New Investment Avenue: An Exploratory Study in Bangladesh

Sukuk can be a worthwhile device for meeting demand of those willing to invest in Shariah-compliant avenues of investment, which has been largely catered by Islamic banking products in Bangladesh. Using survey data collected from existing market investors, this study aims to explore the factors contributing to their choice of investment in sukuk. The risk-return preference of the investors is crucial for structuring the sukuk for issuance. Major factors contributing to the investment decision of the sukuk of surveyed participants also include confirmation of the use of proceed of the project in a Shariah-compliant way, risk-adjusted return, timely payment of the expected cash flows, tradability in the secondary market, awareness regarding the expertise, and independence of the Shariah advisors in the Shariah supervisory board (SSB). To facilitate the new instrument and utilize it for the development of the country, especially for the infrastructural development and green projects, government and other policymakers can contemplate offering government guarantee as well as tax exemptions demanded by the respondents of this study. The respondents expressed aversion to longer-term investment opportunities; rather sukuk maturity of up to five years was found desirable. Apprehension for upholding a distinct special purpose vehicle (SPV) and trustee for sukuk was revealed in the study. Although sufficient care was taken in selecting the sample, the limitation of the study is that it may not be deemed conclusive due to the lower sample size. A larger scale study may be conducted to reckon the insight of more potential investors in the market.

Dupont System Analysis For Measure Financial Performance At Automotive Component Industry In Indonesia

The purpose of this study is to evaluate the financial performance of several automotive component industry companies in Indonesia. The research used of descriptive-quantitative research method, the research of attempted to collect and present data from companies for analysis so as to provide a fairly clear picture of the object under study. The type of data used in this research is quantitative data, namely data in the form of explanations or statements in the form of numbers, namely financial reports from several companies listed on the Indonesian Stock Exchange which are used as the population in the research, including; AUTO, ASII, DRMA, BOLT, SMSM, GJTL and INDS for the 2019-2023 period. By using the Dupont system method as an analysis method. Analysis of the Dupont system method also shows that factors such as net profit margin, asset efficiency and financial leverage influence the financial performance of companies in the automotive components industry. The results of this research explain how the dupon system determines between six similar companies providing company performance data in terms of Net Profit Margin (NPM), Total Asset Turn Over (TATO), Equity Multiplier (EM) and Return on Equity which can be used by potential investors in investing in automotive component industry companies in Indonesia.

Analyzing the Selective Stock Price Index Using Fractionally Integrated and Heteroskedastic Models

Stock market indices are important tools to measure and compare stock market performance. The Selective Stock Price (SSP) index reflects fluctuations in a set value of financial instruments of Santiago de Chile’s stock exchange. Stock indices also reflect volatility linked to high uncertainty or potential investment risk. However, economic shocks are altering volatility. Evidence of long memory in SSP time series also exists, which implies long-term persistence. In this paper, we studied the volatility of SSP time series from January 2010 to September 2023 using fractionally heteroskedastic models. We considered the Autoregressive Fractionally Integrated Moving Average (ARFIMA) process with Generalized Autoregressive Conditional Heteroskedasticity (GARCH) innovations—the ARFIMA-GARCH model—for SSP log returns, and the fractionally integrated GARCH, or FIGARCH model, was compared with a classical GARCH one. The results show that the ARFIMA-GARCH model performs best in terms of volatility fit and predictive quality. This model allows us to obtain a better understanding of the observed volatility and its behavior, which contributes to more effective investment risk management in the stock market. Moreover, the proposed model detects the influence volatility increments of the SSP index linked to external factors that impact the economic outlook, such as China’s economic slowdown in 2012 and the subprime crisis in 2008.

Effects of process parameters on biogas production from food waste using aspen plus simulator

This study explores the potential of converting food waste (FW) in South Africa to biogas via anaerobic digestion (AD) using the Aspen Plus Simulator version 11. The simulation modeled the AD process, focusing on hydrolysis, acidogenesis, acetogenesis, and methanogenesis stages, with unconverted substrate recycling at the acetogenesis stage, employing a Non-Random Two-Liquid (NRTL) model for the polar mixture components. The FW used contained 49.86 % volatile solids (VS) of carbohydrates, 39.31 % VS of proteins, and 10.83 % VS of lipids. The results revealed that biogas yield at mesophilic temperature (37 °C) was 50 % higher than at thermophilic temperature (55 °C) with a residence time of 35 days, and methane composition was 45.98 % higher. Methane and carbon dioxide percentage compositions increased with hydraulic retention time (HRT), varying between 37.5–45.5 % and 34.3–39.9 % at mesophilic conditions. Economic analysis indicated a profitable outlook, with a payout period of 3 years, 5 months, and a 15-year positive revenue forecast. The project exhibited an internal rate of return (IRR) of 59.6629 %, suggesting strong economic viability and potential for investment. This study underscores the potential for optimized AD processes to enhance biogas production from FW in South Africa, presenting a viable, eco-friendly waste management solution.

Investment attractiveness factors in the opinion of companies from Special Economic Zones in Poland

The purpose of the research is the identification of important determinants shaping the investment attractiveness of the country (region) from the point of view of potential investors and an assessment of the degree of stakeholder satisfaction with existing methods of examining the investment climate and their availability for practical use. In order to assess a set of determinants that exert the most significant influence on a country’s investment climate, a questionnaire was developed consisting of 25 questions of various orientations. These questions were designed to assess the opinions of potential investors regarding the degree of influence of various factors on their decision on capital allocation and the investment climate of a country. The survey was conducted among 506 enterprises and 14 management bodies of Special Economic Zones in Poland from June 10 to July 20, 2023. The final step involved the analysis of the survey results using statistical methods.

The impact of COVID-19 stringency measures on emerging stock market stability: Does economic resilience matter?

PurposeThe current research aims to investigate the impact of coronavirus 2019 (COVID-19) evolution, government stringency measures and economic resilience on stock market volatility in the Middle East and North African (MENA) emerging markets. Other macroeconomic factors were also taken into account.Design/methodology/approachBased on financial data from 10 selected MENA countries, we tested an integrated framework that has not yet been explored in prior research. The exponential generalized autoregressive conditional heteroskedasticity (E-GARCH) was adopted to analyze data from March 2020 to February 2022.FindingsOur research illustrates the direct and indirect effects of the virus outbreak on stock market stability and reports that economic resilience could alleviate the volatility shock. This finding is robust across the various proxies of economic resilience used in this study. We also argue that the negative impact of the pandemic on equity market variation gets more pronounced in countries with higher level of stringency scores.Practical implicationsPolicymakers ought to strengthen their economic structures and reinforce the economic governance at the national level to gain existing and potential investors’ trust and ensure lower stock market volatilities in times of crisis. Our study also recommends some key economic factors to consider while establishing efficient policies to tackle unexpected shocks and prevent financial meltdowns.Originality/valueOur findings add to the evolving literature on the reaction of economic and financial markets to the sanitary crisis, particularly in developing countries where research is still scarce. This study is the first of its kind to investigate the stock market reaction to stringency measures in the understudied MENA region.

Faktor-Faktor yang Mempengaruhi Penanaman Modal Asing: Studi Kasus Kota Surabaya Tahun 2019-2023

Investment has an important role in the progress of a region's economic growth. Supported by a good investment climate, investment activities will certainly proceed according to plan. The city of Surabaya is one of the largest cities that has investment potential which can be utilized well for the progress of the city itself and country. Investment can be influenced by factors such as inflation, exchange rates, GDP and technology.This research aims to determine the effect of inflation, exchange rate and GDP on foreign investment in 2019-2023. The method used in this research is a time series with 20 observations. The results of this research are that inflation, exchange rate and GDP do not significantly influence foreign investment. Together in the long term, inflation has an influence on foreign investment. Then in the short term, inflation and GDP together influence foreign investment

Анализ возможностей финансирования крупных it-компаний в современной российской экономике за счёт коллективных инвестиций

The study of financing IT companies through collective investments is aimed at analyzing and evaluating this model in the context of modern economic conditions. The relevance of the topic is due to the rapid development of the technology sector and the need to find alternative sources of financing for startups and developing companies in an environment where traditional lending and investment mechanisms are often unavailable or ineffective. The purpose of this study is to assess the potential of collective investments as a tool for supporting and developing IT companies, identify the main factors influencing the success of this type of investment, and develop recommendations to improve the effectiveness of fundraising.

Stock market index prediction based on market trend using LSTM

The stock market data analysis has received interest as a result of technological advancements and the investigation of new machine learning models, since these models provide a platform for traders and business people to choose gaining stocks. The business price prediction is a challenging and extremely complex process due to the impact of several factors on company prices. The numerous patterns that the stock market goes, they have been the focus of extensive research and analysis by numerous experts. There are several large data sets accessible, an artificial intelligence and machine learning techniques are developing quickly, and because of the machine’s improved computational power, complex stock price prediction algorithms can be developed. This paper presents stock market index prediction based on market trend using long short-term memory (LSTM). Using built-in application programmable interface (API), Yahoo Finance offers a simple method to programmatically retrieve any historical stock prices of an organization using the ticker name. The standard and poor’s 500 index (S&P 500 index) include the firms that have been taken into consideration here. Utilizing the selected input variable, single-layer and multi-layer LSTM models are implemented, and the measurement parameters of mean absolute error (MAE), root mean square error (RMSE), and correlation coefficient (R) are used to compare each performance. Nearly all of the real closing price’s curve and the prediction curve’s closing price for test data overlap. A potential stock investor may benefit significantly from such a prediction by using it to make well-informed choices that would increase his earnings.

PLTBg investment analysis from agricultural organic waste to produce electrical energy: preliminary potential analysis study and investment in the Caringin Main Market, Bandung

Abstract Biogas is a product of the decomposition of organic matter by microbial decomposers under anaerobic conditions. Biogas consists of various gases, especially methane, carbon dioxide, hydrogen, H2S and other gases as impurities. Biogas can be converted into fuel or electrical energy. One of the potential biogas raw materials is agricultural organic waste. This article and study are based on a survey of the potential for agricultural organic waste produced by the Caringin Main Market. Bandung and the amount of organic waste production reached 84 tons/day, resulting from the trading process in the market. The waste produced by the market is suitable to be used as biogas with an organic content of more than 97.7%; the remaining 2.3% is inorganic waste. Based on the economic and financial analysis, the NPV value was 356,487,559,415.34 and the IRR was 23%, which means it was higher than the interest rate set by the bank, while the PBP value was 5.8 years, much lower set by investors for 10 years and Profitable Index of 4,2 so that this project is declared economically and financially feasible.

Effective Strategies For Small Startups To Attract Venture Capital

In essence, for small startups, securing VC is a major breakthrough for growing and scaling up their business. The paper now zeroes in on the tactics that small startups can employ to capture, to a larger extent, the potential attention of VCs. The most critical strategies in order to engage VCs will be what this discussion will be based on as we turn into a collection of previous literature, case studies, and expert insights. Forge a Convincing Business Model: One solid business model is what lies at the core of how to attract VC investment. How a startup can sketch out its value proposition, revenue streams, and path to scaling. This business model does not only bring out the potential for high returns that the startup might have; it also aligns with the risk appetite of these venture capitalists. Network Building: Networking forms one of the core functions of the entire venture capital business. This paper looks into just how a network of one's own can be built and leveraged via industrial connections, along with mentors and advisors. Proper networking will result in more visibility and credibility, thus increasing the opportunity for start-ups to reach out to potential investors. Demonstrating Market Potential: For venture capitalists, the ability to demonstrate a clear market potential is very much desirable from startups. We will see how startups can present information on market size, customer segments, and competitive landscape to secure an investment interest. Making a Strong Pitch: Preparing a convincing pitch is a sure way of attracting the interest of VCs. We will look at the main components of the pitch: elevator pitch, articulating the problem and solution, definition of the market opportunity, articulation of the solution itself, business model, traction, team, and financial projections. Preparing a sound pitch can dramatically increase the chance of receiving venture capital. Apart from these, the paper also makes the target to address the critical pitfalls which startup companies often face in the form of indistinct ideas, over-promise on market size, and unrealistic projections for financials. It must help the startups, through practical recommendations and insights, reach an optimization of approaches toward venture capital and hence secure the necessary funding portions of growth and success

The Research on the Investment Value of Cigna based on SWOT, Financial and Valuation Methods

Health insurance has always been an area of concern for investors. At the same time, the industry has also been strongly supported by the government in recent years and has always been in the forefront of development.The paper utilizes the SWOT method, financial analysis method, and valuation method to assess the investment potential of Cigna Company. The findings indicate that while Cigna demonstrates strong advantages in technology and innovation collaboration, it also faces challenges related to debt.Companies can adapt to the trend of digital technology and aging population, expand and seize growth opportunities. At the same time, it is reasonable to respond to threats such as disease, data risk, and so on.Through various financial indicators, it can be seen that the overall situation of the company is good and always in an upward trend, and has a good development prospect.Through the valuation method, it is evident that Cigna Enterprises holds a high stock investment value, making it a favorable choice for investors. This paper not only serves as a reference for investors to make more informed decisions, but also aids enterprises in gaining clarity on their strengths and weaknesses, thereby providing a foundation for enhancing market competitiveness.

Valorizing Lycii fructus waste residue into polysaccharide-rich extracts: Extraction methodologies, physicochemical characterization, in vitro activities and economic feasibility

The high polysaccharide content of Lycii fructus agri-food waste should be reclaimed for value liberation from both environmental and economic perspectives. In this study, waste from L. fructus pigment products was valorized on a bench scale by upcycling into active polysaccharide-rich extracts. The methodological feasibility of polysaccharide recovery from L. fructus waste was evaluated using sequential extraction techniques. Three fractions LFP-30, LFP-100, and LFP-121, were obtained under stepwise increases in temperature and pressure. Highly heterogeneous xyloglucan (XG)-pectin macromolecules composed of linear homogalacturonan (HG) and alternating intra-RG-I-linkers, with topological neutral branches and XG participation, were predominant among the L. fructus polysaccharides (LFPs). Antioxidant activities in LFPs were unaffected by waste resources and severe extraction methodology conditions. Additionally, the direct investment potential of polysaccharide recovery was evaluated for full-scale implementation. This study demonstrated the necessity and feasibility of extracting bioactive polysaccharides with potential applications from L. fructus waste, and provided a sustainable strategy for transforming L. fructus waste disposal problems into value-added products using cost-effective methodologies.

Стратегічні пріоритети формування економічної безпеки і диджиталізації управлінської звітності для розвитку малих форм господарювання на сільських територіях

The article is dedicated to examining the fundamental strategic priorities for developing managerial reporting in the context of economic security for small-scale enterprises in rural areas, considering the growth of agribusinesses in Ukraine and worldwide. It has been demonstrated that integrating digitalization into managerial accounting significantly improves the efficiency of the information support system for agricultural enterprises. Approaches have been proposed to establish optimal managerial reporting for small-scale enterprises in rural areas. It is noted that implementing digital technologies in reporting dramatically enhances the transparency and accuracy of financial operations, allowing for the timely identification of financial risks and the prevention of undesirable losses, thereby maintaining the economic security of agribusiness enterprises. Small enterprises in rural areas, which are limited in resources and opportunities for obtaining credit or external investments, can. However, they leverage digitalized reporting systems to improve their financial reliability when collaborating with potential investors and creditors. Moreover, the digitalization of managerial reporting facilitates the optimization of management processes, allowing for more rational planning of the enterprise’s available resources. To this end, we analyzed data from a sheep farming enterprise. In calculating economic indicators in managerial reporting, a developed format for digitalized accounting and reporting information is presented for small-scale enterprises involved in sheep farming. The decrease in the number of sheep and the productivity of products (milk and wool) by 4% from the planned volumes relates to the low quality of fodder, which directly affected the economic results of the agrarian business enterprise. At the same time, the actual revenues of the enterprise turned out to be 4.2% lower than planned due to the fall in the wool market and a slight decrease in revenues from the sale of dairy products. The conclusion is drawn that further implementation of digitalization in accounting processes is advisable to reduce bookkeeping costs. It is substantiated that, in the context of globalization and the digital transformation of markets, the digitalization of accounting procedures is an integral element of the development of management systems, ensuring their adaptability to the challenges of the modern economy. Keywords: agrarian business, strategic priorities, economic development, small businesses, international business, rural areas, enterprise, digitalization, management reporting, economic security.

ANALYZING FINANCIAL RATIOS' IMPACT ON STOCKS RETURNS: CASE STUDY OF LQ45 INDEX 2014-2023

This study examines the correlation between fundamental financial metrics and stock returns of Indonesia's LQ45 Index over a 10-year period (2014-2023). The study aims to provide actionable insights for investors and companies by identifying the most critical financial metrics in predicting stock price movements. By analyzing data from 16 consistently listed Indonesian companies, the study focuses on stocks that have consistently maintained their position in the index over the past decade, a gap that has been underexplored in prior research. The study employs various statistical tests to validate the regression model, with hypothesis testing conducted through t-test and F-tests to determine the significance of financial ratios on stock returns. The analysis shows that Return on Equity, Price to Earnings Ratio (PER), Price to Book Value (PBV), Free Cash Flow per Share to Price (PFCF), and Dividend Payout Rate (DPR) have a significant positive effect on stock return. The research recommends that retail investors prioritize the PFCF ratio when evaluating potential stock investments. Transparency in financial reporting is essential, with companies encouraged to provide accurate and comprehensive financial statements, including clear reporting of key financial metrics, to build investor confidence.

A new portfolio approach integrating three-way decision and Encoder–Decoder network

In the stock market, it can be challenging to predict stock trends and identify stocks with investment potential due to uncertainty and risk. Accurate predictive models and reliable asset preselection methods are essential for portfolio management. This paper proposes an integration of the deep learning model, the three-way decision (3WD) theory, and the Mean-Variance (MV) method for asset preselection and optimal asset allocation. In the initial stage, an attention-based Encoder–Decoder model is used to predict asset returns and calculate volatility. It outperforms other benchmark models regarding relative error, absolute error, and directional accuracy. The subsequent stage involves selecting stocks based on expected returns and volatility characteristics. The 3WD theory is then used to identify the delayed decision set for implementing additional investment strategies to hedge portfolio risk and enhance returns. Finally, the MV model is employed for investment portfolio optimization. The proposed model is validated using a substantial dataset from the A-share market’s SSE 50 Index from January 2010 to December 2022. Results indicate that the proposed model outperforms benchmark models in terms of daily average returns, annualized Information ratio, Sortino ratio, and other aspects under certain trading costs. However, further exploration is required to establish a mechanism that limits the quantity of preselected assets to ensure its broad applicability.

An insight into the signaling role of Sharia status: a case from an emerging IPO market

Purpose 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. Design/methodology/approach 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. Findings 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. Practical implications 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. Originality/value 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.