Investment Risk Research Articles

The green hydrogen ambition and implementation gap

Abstract Green hydrogen is critical for decarbonizing hard-to-electrify sectors, but it faces high costs and investment risks. Here we define and quantify the green hydrogen ambition and implementation gap, showing that meeting hydrogen expectations will remain challenging despite surging announcements of projects and subsidies. Tracking 190 projects over 3 years, we identify a wide 2023 implementation gap with only 7% of global capacity announcements finished on schedule. In contrast, the 2030 ambition gap towards 1.5 °C scenarios has been gradually closing as the announced project pipeline has nearly tripled to 422 GW within 3 years. However, we estimate that, without carbon pricing, realizing all these projects would require global subsidies of US$1.3 trillion (US$0.8–2.6 trillion range), far exceeding announced subsidies. Given past and future implementation gaps, policymakers must prepare for prolonged green hydrogen scarcity. Policy support needs to secure hydrogen investments, but should focus on applications where hydrogen is indispensable.

Research on the Green Investment of Traditional Energy Enterprises and Its Effectiveness Under Environmental Regulation

Using data from 188 traditional energy companies listed on China’s A-share market from 2012 to 2023, this study adopts the double-difference method to assess the changes in the green investment of traditional energy companies before and after the implementation of environmental regulation policies in depth and further explores the actual effects and potential risks of green investment on the green transformation of traditional energy companies. This study shows that the environmental regulation policies significantly increased the green investment of traditional energy enterprises, but this increase did not effectively promote the overall green transformation of the enterprises; rather, they became more focused on meeting the current compliance requirements while ignoring the fundamental green technological innovation and production mode change. Further analysis reveals that, as environmental standards continue to rise, the increasing green investment expenditure of traditional energy companies for meeting the standards will continue to outpace the growth in capital inflows of traditional energy companies, resulting in a threat to the financial soundness of the companies in the short term and a significant increase in financial pressure. In the long run, the lack of sustained and stable external financial support for a long period of time will not only constrain the green transformation process of enterprises but may also pose a serious threat to the survival foundation of enterprises and even lead to the elimination of enterprises in fierce market competition.

CLUSTER ANALYSIS OF K-MEANS AND WARD METHOD IN FORMING A ROBUST PORTFOLIO: AN EMPIRICAL STUDY OF JAKARTA ISLAMIC INDEX

Building a portfolio is one method of reducing investment risk. Cluster analysis can shorten the time required to choose companies for a portfolio because it makes it easy to put firms in the same category together. To maintain the best state of the portfolio cluster analysis in the case of data containing outliers, K-means, and ward cluster analysis are employed in conjunction with a robust portfolio strategy. K-means clustering is a popular method for grouping data by assigning observations to clusters based on proximity to the cluster’s center meanwhile the Ward method is based on the size of the distance between clusters by minimizing the number of squares. This study seeks to determine the robust portfolio performance comparison outcomes produced by K-Means and Ward clustering utilizing the Sharpe ratio criterion. The Sharpe ratio is one of the most widely used methods to evaluate a portfolio’s risk-adjusted performance. The greater a portfolio's Sharpe ratio, the better its risk-adjusted performance. Stocks included in the Jakarta Islamic Index 70 (JII70) are used in this research. The results of the formation of a robust portfolio on K-Means clustering produce a return rate of 0.01038627 and risk of 0.1066364, while in the Ward cluster, the portfolio profit rate is obtained at 0.01632749 and the risk is 0.1340073. Based on the Sharpe ratio criteria, in this case, the robust portfolio with the Ward cluster is superior to the K-Means cluster because it produces a higher Sharpe value.

Implementation of carbon emission reduction and green innovation on investor reaction with environmental performance as a moderation variable

This research aims to explores the relationship between carbon emission reduction, green innovation, and investor reaction, with environmental performance acting as a moderating factor. Carbon accounting plays a vital role in tracking emissions and evaluating the success of environmental initiatives. Companies that demonstrate efforts to reduce their company's carbon emissions and implement green innovations to demonstrate their commitment to sustainability can reduce investment risks, thereby attracting investors to invest in the company. The population used in this study consists of manufacturing companies listed on the Indonesia Stock Exchange from 2020 to 2023, using a purposive sampling method. The research data utilized are secondary data in the form of annual reports obtained from the IDX website. The analytical method used is multiple linear regression analysis. The research results show that carbon emissions reduction and green innovation significantly negatively affects investor reactions. This is because there is still very little socialization from the company regarding operational activities in the environment towards the community as shareholders. Meanwhile, environmental performance could moderate the effect of carbon emission reduction and green innovation on investor reactions.

The Role of Technological Innovation in Mitigating Climate Change Risks in Agricultural Investment

This paper examines the critical role of technological innovations in mitigating climate change risks within the agricultural sector, using Cargill as a case study. Climate change poses considerable threats to agriculture, including unpredictable weather patterns, increased severity of extreme events, and disruptions to food production. However, advanced technological solutions such as artificial intelligence, drone technology, and precision agriculture offer promising ways to address these challenges. This essay demonstrates how Cargill has successfully incorporated these technologies to reduce climate-related risks and enhance operational resilience. In addition, the essay provides recommendations for policymakers, large agricultural corporations, and small-scale farmers on leveraging these innovations effectively. These interventions are adaptable to various farming systems, regardless of whether the focus is on livestock or crop production. By embracing these cutting-edge technologies, farmers of all sizes can safeguard their operations from the adverse effects of climate change, ensuring more sustainable and resilient agricultural practices in the long term.

Configuration path identification of investment risk in China's overseas energy projects: An exploration based on LDA and fsQCA

AbstractChina's overseas energy investment is subject to various risks and uncertainties. This study uses the latent Dirichlet allocation (LDA) model for text mining to comprehensively identify risk factors for overseas energy project investment. Then, we utilize fuzzy set qualitative comparative analysis (fsQCA) to explore the configuration path of risk based on 25 overseas energy project investment cases. The results show that there are six categories of investment risks in overseas energy projects, namely: political risk, economic risk, resource risk, environmental risk, social risk, and national relations risk. The occurrence of a single risk is insufficient to cause an investment in an overseas energy project to fail. Rather, it is only when multiple risks occur together and act in concert that the project is disadvantaged. The configuration paths of risk can be categorized into four types, which are geopolitical dominance type, socio‐economic dominance type, resource‐environment dominance type, and comprehensive type. From a holistic perspective, this study examines the cumulative impact of multiple risk factors on the investment effect of energy projects, illustrating the inherent complexity of investment risks associated with overseas energy projects. This study provides direction for investors and policymakers to develop effective risk management programs and sound investment strategies.

Practical Applications of Neutrosophic Logic in Enhancing the Accuracy of Economic Forecasting Models and Supporting Decision-Making in Banks

Using three machine knowledge models that utilise Neutrosophic Logic (NL)—Linear Regression, Random Forest, and Gradient Increasing—this study studies the possibilities of refining financial result forecast. The cognitive behind this is that NL recovers the prediction power of these models across dissimilar organisations by accounting for the inherent uncertainty, unpredictability, and lack of sureness in financial numbers. In this study, the models' presentation is evaluated using a variety of financial factors, including interest rates and stock prices. F1 score, recall, correctness, and exactness are some of the metrics used by this drive. When likened to other models, NL with Gradient Cumulative consistently outperforms them in terms of correctness and robustness. You might think of Abu Dhabi Islamic Bank and the National Bank of Bahrain as two such examples. Companies like Emirates Islamic Bank reap some benefits from Chance Forest's combination of cheap computation with precision, but only to a lower degree. Complex datasets used by businesses like Al Rajhi Bank are beyond the capabilities of Linear Reversion, even when combined with NL. By proving that cooperative techniques combined with NL positively reduce financial data volatility, our results lay the groundwork for improved financial forecasting and decision-making. The exercise has demonstrated that NL has great potential to enhance financial prediction models, which could have future applications in investment planning and risk organization.

Measuring climate-related and environmental risks for equities.

Financial regulators and investors are increasingly concerned about the effects of climate change on investments and seek to capture the climate-related and environmental risks of investments. Whilst energy companies have attracted most of the attention due to the contribution of the Energy sector to environmental degradation, climate-related and environmental risks actually affect companies in every sector. In this paper, we propose novel measures termed as climate Value-at-Risk (VaR) and climate Expected Shortfall (ES) that capture the risk attributed to transition risk factors proxied by environmental scores. We compare the average ratio of climate VaR and ES to total risk in various equity sectors, which enables us to identify the sectors in which climate and environmental risk factors contribute most to the total risk. Our analysis considers different risk measurements and various significance levels. Our findings show heterogeneity in sensitivity to climate and environmental risk factors in various sectors. The Health Care sector is the least cost-effective in reducing climate-related and environmental risks, and the Energy sector benefits most from improving the firms' environmental scores.

Risk analysis and investment feasibility for green retrofits in high-rise office buildings using the life cycle cost method

Greenhouse gases (GHGs) have caused extreme temperature changes. In January 2023, temperatures were 0.1°C higher than the normal 30-year monthly average. Construction, especially high-rise offices, which occupy 42% of Jakarta, contributes significantly through energy con-Sumption. To reduce carbon emissions, Indonesia has started to implement green retrofits as part of the Net Zero Emission 2050. Due to high costs and lack of public education on new and existing green buildings, the implementation of green retrofits is inhibited, and owners prefer conventional buildings. This research aims to analyze the feasibility and investment risk of implementing green retrofits in high-rise office buildings using the life cycle cost method and the Minister of Public Works and Public Housing Regulation No. 21 of 2021 to generate a feasible and safe in-vestment. It has been proven with cost savings in energy and water consumption of up to 15% compared to conventional office buildings. Profits have also been achieved by providing 9 benefits to the building owner, building manager and building occupants. Therefore, this research has the potential to accelerate the green revolution through feasible and safe green retrofit investments in Jakarta's office buildings.

Determinants of investment attractiveness of countries and investment climate assessment methods. Survey analysis

ObjectivesThe purpose of the research is the identification of important determinants shaping the investment attractiveness of the country from the point of view of potential investors and assessment the degree of stakeholder satisfaction with existing methods of examining the investment climate and their availability for practical use.Material and methodsIn order to achive the aim it was developed a questionnaire consisting of 25 questions. 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 from Special Economic Zones in Poland.ResultsBased on the conducted research, we have developed a list of the most important factors, perceived by potential investors, shaping the investment climate of a country. The most important were economic as well non-economic factors. The study shows also that a qualitative methodology for assessing the investment climate should be based on a variety of analytical tools to provide a more complete and objective picture of the investment attractiveness of a given country.ConclusionsThe use of expert assessments, statistical data and stakeholder opinions allows for a better understanding of the investment context, risk and return potential. This study has important implications for companies and investors who are looking for reliable tools to assess the attractiveness of potential investment locations and make informed investment decisions.

Deciphering Investment Decision in Fintech: The Role of Behavioral Bias and Risk Perception

Purpose – This study aimed to investigate the effect of behavioral biases on Indonesian investors using fintech platforms. The roles of blue-chip stock, availability, herding, and overconfidence bias, as well as disposition effect on investment decisions, were examined both directly and indirectly through risk perception. Methodology – Data were collected via stributing online surveys to over 360 investors between November 2023 and January 2024. Structural Equation Model analysis method was used to evaluate the data. Results – Availability and blue-chip stock biases positively influence investment decisions and risk perception, while herding bias is insignificant. Overconfidence bias and disposition effect significantly affect risk perception but not investment decisions. Risk perception mediates the significant effects of availability and blue-chip stock biases on investment decisions. Originality – The study explores the unique role of fintech platforms in shaping investment decisions, extending beyond traditional analyses of investor psychology. Prospect theory was applied as a theoretical lens to examine the effect of specific behavioral biases on investment decisions and risk perception within the Indonesian fintech context.

A Portfolio Study Based on the Markowitz Model - An Example of the Bitcoin Market

Nowadays, financial markets are becoming more and more complex, and new portfolios need to be built to cope with them. This paper aims to build a Markowitz model for portfolio research based on new calibrations for nine different industries. Firstly, the weights and minimum variance combinations are calculated by using valid information such as mean, standard deviation, variance, and covariance. Second, this paper aims to maximize the return of the portfolio, diversify the investment risk of the selected portfolio, and finally determine the optimal portfolio. The portfolio can be adjusted to reduce risk or increase return by adjusting the percentage of Bitcoin. This paper further explores the portfolio using Bitcoin as a variable. This paper derives the volatility and return of the least risky portfolio to be 11.04% and -0.46%, respectively, when the portfolio is calibrated without Bitcoin, and the volatility and return of its Sharpe optimal portfolio are 14.61% and 7.11%, respectively. When the portfolio contains Bitcoin, the volatility and return of its risk-minimal portfolio are 9.45% and 0.6%, respectively, and the volatility and return of its Sharpe-optimal portfolio are 16.31% and 37.35%, respectively. Ultimately, it is concluded that Bitcoin has some risk-reducing and return-enhancing effects.

The Impact and Challenge of Digital Infrastructure Construction on Investment and Financing Term Mismatch of Enterprises

With the emergence of the digital age, digital infrastructure has witnessed significant development. Through literature review, summarization, and exemplification, this paper examines the impact of digital infrastructure construction on the maturity mismatch of enterprise investment and financing. The research reveals that the network infrastructure and information service infrastructure within digital infrastructure can respectively reduce the risk of investment and financing term mismatch by alleviating the impact of information asymmetry and by obtaining the support of big - data - based information, enabling enterprises to make more precise decisions. This paper also highlights several issues that require attention during the process of digital infrastructure construction, such as technological updates and data security. The research in this paper is conducive to understanding the mechanism through which digital infrastructure affects the mismatch of enterprise investment and financing terms and the risk alerts associated with digital infrastructure establishment, and provides relevant policy incentives for enterprises utilizing digital infrastructure.

Business Strategy Innovation and Investment Risk Prevention and Control under Sustainable Development

This research investigates the relationship between innovation strategies and investment risk, with a particular focus on the moderating effect of Environmental, Social, and Governance (ESG) practices. Utilizing data from Chinese listed companies, we employ multiple regression models to assess the impact of R&D investments on systematic risk (Beta) and explore how ESG scores influence this relationship. Our findings indicate that increased R&D investment is associated with higher investment risk, highlighting the inherent uncertainties and potential volatility of innovation activities. However, strong ESG practices mitigate these risks, suggesting that companies with robust ESG frameworks can reduce the additional risk introduced by high levels of innovation. The study also reveals significant interrelationships among key financial metrics, underscoring the complexity of managing innovation and investment risk. These insights provide valuable implications for companies, investors, and policymakers, emphasizing the need for balanced growth strategies that incorporate effective risk management and sustainable practices. This research contributes to the literature by offering empirical evidence on the interplay between innovation, ESG, and investment risk, ultimately advocating for more resilient and sustainable business practices.

Study on the Development of Kangtai Biologicals in the Context of the COVID-19 Pandemic--Analysis Based on Financial Indicators

According to data from the National Health Commission, as of July 23, 2022, China's full basic immunization rate was 89.7% and booster immunization rate was 71.7%. Among them, the vaccination rate of at least one dose of vaccine for the elderly over 60 years old was 89.6%, the full immunization rate was 84.7%, and the booster immunization rate was 67.3%, and the new crown vaccine has almost reached market saturation. The Novel Coronavirus Pneumonia background, the vaccine industry is facing the new crown vaccine demand instability, the second type of vaccine government supervision is small, social responsibility events occur frequently (Changsheng Biological vaccine counterfeiting events, Beijing Kexing bribery case) and high R & D investment risk, so, based on the Contagious Biological face technology, patents, production capacity and so on a number of barriers, resulting in the decline in performance of the status quo, how to adjust the strategic direction in a timely manner also become a major test. Whether it will change accounting policies to “do high” performance? How about the direction of future development? Is very worth studying. In this paper, we will take Kangtai Bio as a case study, analyze the relevant indexes of its operation ability and development ability, explore the problems in its current development, and put forward relevant suggestions.

Analysis and Prevention of Financial Risks of Real Estate Enterprises in China

As an important pillar industry of the national economy, the real estate industry has the characteristics of high investment, high return and high risk. In the process of rapid economic development in China, the real estate industry has developed rapidly and become one of the main driving forces of economic growth. However, while pursuing high profits, real estate enterprises are also facing huge financial risks, which are directly related to the survival and development of enterprises. As a leading real estate enterprise in China, Vanke Group's financial situation and risk management strategy have attracted much attention. In recent years, with the constant changes in the macro-control policies of the national real estate industry, the financial risk problem of Vanke Group has become increasingly prominent. This paper aims to analyze the financial risks of Vanke Group and discuss how real estate enterprises can effectively identify, evaluate and prevent financial risks in the complex and changeable economic environment.

Research on the Impact of ESG Performance, Green Innovation Investment and Stock Price Crash Risk

With the development of national sustainable policies, the ESG performance of enterprises has increasingly attracted scholarly attention, leading to extensive research in the area. The study empirically examines the link between corporate ESG monetization and stock price crash risk by analyzing data from firms that are publicly traded on the A-share market in Shanghai and Shenzhen spanning 2011 to 2022. The results indicate that is negatively correlated between the monetization of corporate ESG efforts and the probability of stock price crashes. Furthermore, through mechanism analysis, it is revealed that robust ESG performance mitigates the chances of notable declines in stock prices not only via investments in green innovation but also by alleviating financing constraints. In terms of heterogeneity testing, the influence of ESG performance on the probability of stock price crashes appears to be somewhat more conspicuous for state-owned enterprises (SOEs) in comparison to non-state-owned enterprises and analysts' focus.

Portfolio Choice Using Additional Information from Financial Statements - Evidence from the Frankfurt Stock Exchange

Classical portfolio construction models consider only the information contained in the market prices of stocks, but ignore the financial performance of companies. Typically, the variance is used as the dispersion parameter. This symmetric measure of risk may be inadequate if the distribution of returns differs significantly from the normal or symmetric distribution. With this in mind, we introduce some additional portfolio selection criteria based on companies' financial performance. In addition, we consider semi-variance as an alternative risk measure to variance. The main research objective is to develop a classical portfolio theory by incorporating firms' financial indicators and using semi-variance as a measure of investment risk. In the paper a novel method for portfolio selection has been proposed and we have developed an original computer code to find the efficient three criteria portfolios. A set of 13 types of portfolios was constructed, differing in terms of fundamental values and risk measures. The proposed models were evaluated under the condition of an economic crisis caused by the COVID-19 pandemic. The research sample consisted of the largest companies listed on the Frankfurt Stock Exchange, the DAX 30 index. The research showed that the highest returns were observed for portfolios based on indicators related to the financial condition of the companies. These types of portfolios were also characterized by the highest level of risk, as measured by variance and semi-variance. The analysis thus confirms the usefulness of corporate financial indicators in portfolio decisions and points to the need for further research in this area.

When MNC Subsidiaries Are Caught in a Political Crisis: The Case of Mozambique

ABSTRACTIn political crises, subsidiary‐level managers of multinational corporations (MNCs) face critical decisions around managing investment risk. Given the potentially existential threat posed by political crises, this study examines subsidiary responses to political risk. The focus is on the effect of firm crisis experience, threat perception, and managerial social embeddedness on the stay‐or‐exit decisions. With data from senior managers of 107 MNCs in Mozambique, we test three hypotheses. We find that the crisis experience of the MNC is a significant predictor of managers' threat perceptions (H1). While threat perception positively affects the likelihood of subsidiary exit (H2), the social embeddedness of the subsidiary manager dampens that relationship (H3). Threat perception does not necessarily drive exit likelihood, as subsidiaries led by socially embedded managers with high levels of social interactions with Mozambican and foreign friends are less likely to exit. These findings contribute to the literature on subsidiary‐level political risk management and underscore the significance of social embeddedness and crisis experience in shaping subsidiary resilience to political instability. For managers, these results highlight the value of fostering strong local networks and crafting flexible risk management strategies. Such insights are crucial for navigating the complexities of international markets during political turmoil.

Navigating investment risks mode and transmission: a study of China’s participation in the Belt and Road Initiative through the lens of risk society

ABSTRACT The world is experiencing a period of heightened complexity and uncertainty, where risks are interconnected and extend beyond traditional boundaries. This paper delves into the effective identification of investment risks for China’s involvement in the Belt and Road Initiative (BRI), utilizing methodologies rooted in complex networks and Minimum Spanning Tree. It establishes an indicator system for foreign direct investment (FDI) risks across four dimensions: economic, political, social, and bilateral relations, while also developing a risk identification model grounded in complex network theory. The empirical analysis draws from data spanning 2010 to 2019, encompassing 103 co-building countries of the BRI. Key findings include: (1) Political risk emerges as pivotal when Chinese enterprises invest in co-building countries of the BRI. (2) Examining individual country investment risks reveals an increased transmissibility of China’s FDI risks. Notably, Indonesia, Brazil, and Bangladesh showcase internally complex investment risk environments. (3) Analysis of investment risks between countries and regions indicates a rise in risk transmission paths since 2010. Particularly, the South Asian region stands out for harbouring the longest transmission path. This study advances theoretical and empirical understanding of effective identification of China’s overseas investment risks, offering valuable insights for the development of global risk society governance.