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Tax incentives are a powerful driver for the development of infrastructure real estate investment trusts (REITs). Complementary antiavoidance regulations are essential to ensure the sustainable and healthy development of the REIT market. This paper breaks through the traditional policy approach that emphasizes incentives but neglects supervision. Based on factors such as information asymmetry and regulatory capture, a tripartite game model of REIT tax incentives and antiavoidance regulation is established. Utilizing global REIT policy and market data, the paper sets parameter values and conducts numerical simulations to explore the dynamic strategic interaction mechanisms among the government, REIT stakeholders, and financial regulators. The study finds that (1) government's tax incentive policies and regulatory strategies show a phase transition characteristic with the changes of REIT market returns; and (2) based on the project's profit status, financial regulators and investors are prone to develop a collusive avoidance evolutionary strategy. Therefore, antiavoidance regulations and mechanisms to prevent regulatory capture should be implemented in tandem to ensure the efficiency of tax incentives. The conclusion of the study provides a theoretical basis for the formulation of REIT tax incentive policy and the promotion of the sustainable development of the REIT market. [ABSTRACT FROM AUTHOR]

This paper explores the symbiotic relationship between the Cayman Islands and the centrality of the United States (US) in global financial networks, using their connection as a test case for a broader theory of how infrastructural power of states is achieved through transnational and networked strategies. The legal and financial infrastructure of the Cayman Islands is extensively used by US financial institutions. This infrastructure supports the development of a significantly US-centric fund industry, facilitating substantial investments into US capital markets. Additionally, it serves as a global conduit, channelling funds from regions such as Asia and Latin America into US markets, streamlining the process by which foreign investors acquire US securities, and supporting the development of complex USD-denominated financial products. This dynamic enhances the depth, liquidity, and complexity of US capital markets, thereby reinforcing US centrality in global financial networks and bolstering its geopolitical power through financial diplomacy, economic sanctions, regulatory influence, and control over critical financial infrastructure. The relationship underscores the infrastructural power of the Cayman Islands, whose financial and legal framework is essential for sustaining and amplifying US centrality. Consequently, this paper aims to integrate the transnational perspective on infrastructural power within the International Political Economy (IPE) and Geopolitics literature, demonstrating how the Cayman Islands function as a multifaceted networked site that strengthens, projects, and sustains US state power on a global scale. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of online interaction between investors and enterprises on stock liquidity, using data from A-share listed companies in China from 2010 to 2021. Firstly, our findings reveal that more frequent interaction leads to better stock liquidity, and this result remains consistent across various robustness tests. Secondly, we observe that the expected tenure of senior executives and the ratio of institutional investor ownership exert a significant moderating effect on this relationship. Thirdly, this effect varies across enterprises at different development stages and with different ownership structures, being more pronounced in growing and privately-owned companies. Furthermore, this paper finds an inverted U-shaped relationship between reply length and stock liquidity, indicating that excessively long replies may introduce noise and negatively affect liquidity. This study provides new insights into how online interactions can improve market efficiency and offers practical implications for corporate governance and investor relations. [ABSTRACT FROM AUTHOR]

Today, with a growing emphasis on sustainable economic development, corporate environmental, social and governance (ESG) performance is attracting increasing attention and favor from investors. This triggers a question: can good ESG performance of listed companies mitigate the "up and down" of the stock market by drawing investor attention? This paper utilizes the data from China's A-share listed companies from 2011 to 2020, with investor attention as a mediating variable, to explore how the ESG performance of listed companies influences abnormal stock price volatility. The findings suggest that stronger ESG performance of listed companies significantly reduces abnormal stock price volatility, in which investor attention plays a partial mediating role. This paper confirms the robustness of the findings through multiple robustness and endogeneity tests. Heterogeneity analysis reveals that listed companies with good ESG performance during the growth period are more likely to significantly mitigate abnormal stock price volatility. Similarly, firms that maintain commendable ESG performance in bear markets significantly reduce abnormal stock price volatility. These findings enrich the theoretical research on the impact of ESG performance on abnormal stock price volatility, provide empirical evidence for listed companies to emphasize ESG investment and encourage investors to consider ESG ratings. Additionally, the study provides a new perspective for government agencies to utilize corporate ESG performance to maintain the sound development of the capital market. [ABSTRACT FROM AUTHOR]

Social impact investors claim to promote sustainable development by mobilizing private finance capital to solve pressing global challenges like poverty alleviation. In this paper, I interrogate this claim through an examination of microfinance in Cambodia, a major destination for impact investment. In the past decade, Cambodia has received nearly 10% of global investments from microfinance-specific funds. It now has the largest microfinance-debt per capita ratio of any country in the world. Based on qualitative research between 2021 and 2023, I argue that impact investment functions as an anti-politics of development that reinforces finance as a political technology of neoliberal governance. Over the past two decades, impact investors have poured capital into the country's microfinance industry to expand access to credit without acknowledging structural political-economic conditions that have produced rising over-indebtedness among microfinance borrowers. Instead, they have argued that the problems created by the microfinance industry are best resolved through a self-regulation model that uses a voluntary code of conduct based on global standards of responsible finance. Thus, impact investors have been integral in broader transformations that have extended financial logics, technologies and accumulation imperatives into people's daily lives. This paper contributes to economic geography and critical development studies by explaining how impact investment deepens neoliberal financialization. [ABSTRACT FROM AUTHOR]

On April 29, 2024, the U.S. Food and Drug Administration (FDA) issued a transformative final rule impacting the regulatory landscape for laboratory-developed tests (LDTs). This new regulation categorizes in vitro diagnostics (IVDs) used as LDTs under the same stringent oversight applied to other medical devices, thereby phasing out the agency's long-standing policy of enforcement discretion. This paper offers a concise historical overview and examines the FDA's revised regulatory framework scheduled for the next four years, examining its impact on laboratory operations in terms of safety, efficacy, and innovation. It explores how the new rule's increased compliance demands and economic implications impact laboratory operations, including economic stability, innovation, and patient safety. Also highlighted is how certain laboratories gain strategic advantages that could enhance their market stability and attract investors. The overall intent of this paper is not an in-depth analysis but instead it aims to inform stakeholders in health services about evolving laboratory standards. By doing so, it equips healthcare participants to strategically align with emerging regulatory demands, enhancing comprehension of how these changes influence healthcare delivery and laboratory procedures. [ABSTRACT FROM AUTHOR]

This paper explores the spillover and leverage effects, as well as trading volume dynamics, of Financial, Technology, and FinTech Exchange-Traded Funds (ETFs) using ARMA-GARCH and ARMA-EGARCH models. The study indicates that these ETF sectors and the stock market index have significant connections and interdependencies, which can transmit shocks and volatility. Market fluctuations significantly impact the ETF sectors, with negative shocks having a more significant impact on volatility. Furthermore, increased volatility is linked to increased trading activity, which indicates active investor adjustments in uncertain periods. The practical implications of these findings for investors, portfolio managers, and policymakers are aimed at supporting portfolio diversification, risk management, and asset allocation decisions. Understanding the effect of market volatility on trading volumes can help improve trading strategies and liquidity management. The paper increases comprehension of spillover and leverage effects and trading volume in ETFs, enabling stakeholders to make well-informed decisions in the financial markets. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to unravel the impact of post-pandemic COVID-19 on foreign direct investment (FDI) and its determinants in the South Asian Association for Regional Cooperation (SAARC) Countries. Design/methodology/approach: The study utilized four macroeconomic variables includes growth domestic product growth rate (GDPG), inflation rate (IR), exchange rate (ER), and unemployment rate (UR) to assess their impact on post-pandemic FDI, along with two variables control of corruption (CC) and political stability (PS) to measure the influence of good governance. Random effects, fixed effects, cluster random effects, cluster fixed effects and generalized method of moments (GMM) models were applied to a balanced panel dataset comprising eight SAARC countries over the period 2010–2021. To identify the random trend component in each variable, three renowned unit root tests (Levin, Lin and Chu LLC, Im-Pesaran-Shin IPS and Augmented Dickey-Fuller ADF) were used, and co-integration associations between variables were verified through the Pedroni and Kao approaches. Data analysis was performed using STATA 17 software. Findings: The major findings revealed that the variables have an order of integration at the first difference I (1). Nonetheless, this situation suggests the possibility of a long-term link between the series. And the main results of the findings show that the coefficients of GDPG, CC and PS are positive and significant in the long run, showing that these variables boosted FDI inflows in the SAARC region as they are significantly positively linked to FDI inflows. Similarly, the coefficients of UR, IR, ER and COVID-19 are negative and significant. Practical implications: By identifying the specific impacts of the post-pandemic FDI and its determinants, governments and policymakers can formulate targeted policies and measures to mitigate the adverse effects and enhance investment attractiveness. Additionally, investors can gain a deeper understanding of the risk factors and adapt their strategies accordingly, ensuring resilience and sustainable growth. Finally, this paper adds value to the literature on the post-pandemic impact on FDI inflows in the SAARC region. Originality/value: This paper is the first attempt to trace the impact of COVID-19 on Foreign Direct Investment and its determinants in the SAARC Countries. Most of the previous studies were analytical in nature and, if empirical, excluded some countries due to the unviability of the data set. This study includes all the SAARC member countries, and all variables' data are completely available. There is still a lack of empirical studies related to the SAARC region; this study attempts to fill the gap. [ABSTRACT FROM AUTHOR]

There has been increasing academic interest shown in the evolving market maturity of the private sector, purpose built student accommodation (PBSA) market and its role in supporting the massification of higher education in the UK and elsewhere. This paper focuses on the evolution of the private sector PBSA market in Sheffield, UK, whose material impact upon central Sheffield in the first two decades of the twenty‐first century to both the built environment and socio‐spatial structure of the central city has been transformational. It is asserted that these changes in Sheffield reflect the wider growth dynamics and impact of private sector PBSAs on similar locales across the UK. A fundamental conceptualisation of the paper is that government higher education policy, and the differential interpretation of that policy by higher education institutions, and the enabling planning frameworks of local authorities, have created the market for private sector PBSA. The private sector PBSA market in Sheffield, as elsewhere, has been increasingly drawn into a global financialised framework that positions PBSAs as assets that are enabling of abstracted extraction of value in a knowable and predictable way. The paper foregrounds how this process embeds within a de‐industrialised, secondary city such as Sheffield a deeper connectivity to the global financial economy through not only inflows of investment capital but outflows of revenue to private sector PBSA investors. [ABSTRACT FROM AUTHOR]

Enterprise financial risk refers to the uncertainty of financial status caused by various internal and external factors during investment, financing, operations, and other activities, which may result in losses for the enterprise. Agricultural group enterprises engage in diversified businesses and have a large number of transactions. Characteristics such as natural disasters, financing difficulties, and strong seasonality of income and expenditure make agricultural enterprises face greater financial risks. Based on the perspective of evidence fusion, this paper takes the JS Agricultural Reclamation Group as the research object, puts forward a financial risk early warning model based on evidence theory, and innovatively puts forward the basic probability assignment of evidence obtained by whitening weight function, and uses evidence theory to fuse uncertain risk information. This paper makes an empirical study of 420 subsidiaries of the group and selects 10 subsidiaries as case study objects. The results show that the model proposed in this study can improve the prediction accuracy of the group's intelligent financial decision system and the existing literature and reduce the subjective factors and information loss in the risk assessment process. In addition, this study provides the probability interval of early warning results, which can expose small probability risks and provide a more reliable basis for regulators, enterprise managers, and investors to make efficient and correct decisions. [ABSTRACT FROM AUTHOR]

The paper studies the problems brought about by Resolution 40066 of 2022 of the Ministry of Mines and Energy of Colombia, regarding the new requirements it sets up for the flaring and venting of natural gas in Colombia. These requirements, which must be followed by the investing companies, imply an investment in infrastructure and technology that may imply a contractual imbalance and a negative impact on foreign investors. From a documentary analysis method with a systematic and deductive approach, the authors analyze the problematic scenario posed by the resolution and concludes that it is necessary to find a balance between the two legal interests at stake: the environment and free enterprise. As a result, the paper supplies a comprehensive and integrative view of the State's obligation to protect the environment, but also to ensure a stable and predictable legal framework for investments. [ABSTRACT FROM AUTHOR]

Annual reports are the primary source of information for investors. It contains all the details about the company's activities in the preceding financial year. About 80% of an annual report is text (Cheng et al. 2018); hence proper comprehension and readability enhance the usefulness of the information. Earlier researches prove the positive relationship between firm performance and annual report readability (Li 2008). Studies also find that complexity is a deliberate attempt by companies to obfuscate earnings management and poor performance (Bloomfield 2008). Against this backdrop, we investigate the relationship between firm value, financial performance and annual report readability in the Indian context. For this purpose, we use Gunning Fog Index (Flesch Kincaid index, Smog index, and File size as robustness checks) to measure the annual report readability of NSE 500 firms for the period 2016 to 2020. We find a positive relationship between firm performance (Tobin's Q, ROA, and ROCE) and annual report readability. Further, this paper finds a positive relationship between the annual report readability and firm value (Tobin's Q and ROA) in the next year. The findings will be helpful for the investors as it shows how vital is annual report readability in signaling future firm value. It shows the readability of the narrative content as an important signal about a firm's current performance and prospects. This paper recommends that the management be more cautious while preparing financial disclosures because complex disclosures may send negative signals to the investors about the firm's prospects. [ABSTRACT FROM AUTHOR]

This paper will examine the sustainability of directors' duties from two perspectives, namely that the duties are stable in their own right and that they cover enough ground for them to help achieve sustainable goals. First, we will examine how directors' duties to act in a company's best interest operate well when shareholder interests are aligned. These duties, when breached, can be ratified by shareholders given the traditional understanding that they are the company. This may, in turn, have been associated with the growing acceptance of shareholder primacy over the past 40 years, seen most recently in the UK Supreme Court decision in BTI v Sequana (2022). The Supreme Court, however, also discussed the limitations of shareholder ratification, and its interaction with the rules protecting creditors, particularly as regards capital maintenance. Those rules have, however, been weakened, and private law has had to step in to address the abuse those rules were aimed at. Where the substantive content of directors' duties is concerned, the focus everywhere is on how to make directors take account of external constraints such as environmental, social and governance (ESG) concerns and corporate purposes that may contradict enhancing shareholder value (as well as existing shareholder protection) as an established paradigm of company law. We will also analyse the difficulties in accommodating the interests of other internal constituents, like creditors (some of whom may have been externalised). This paper will build on earlier suggestions that the proper purpose rule has a part to play in balancing the interests of corporate constituents both inter and intra se and even in considering the position of future shareholders. The test of what is in the best interest of the company may not provide enough balance in this regard, as seen perhaps from the recent failed derivative action sought by some shareholders of Shell against its directors, and directors should take account of the interest of the reasonable shareholder in capturing the gist of what ESG should aim at. [ABSTRACT FROM AUTHOR]

Purpose: The research documented in this paper aims to examine multiple factors related to borrowers' default in peer-to-peer (P2P) lending in the USA. This study is motivated by the hypothesis that both P2P loan characteristics and macroeconomic variables have influence on loan performance. The authors define a set of loan characteristics, borrower characteristics and macroeconomic variables that are significant in determining the probability of default and should be taken into consideration when assessing credit risk. Design/methodology/approach: The research question in this study is to find the significant explanatory variables that are essential in determining the probability of default for LendingClub loans. The empirical study is based on a total number of 1,863,491 loan records issued through LendingClub from 2007 to 2020Q3 and a logistic regression model is developed to predict loan defaults. Findings: The results, in line with prior research, show that a number of borrower and contractual loan characteristics predict loan defaults. The innovation of this study is the introduction of specific macroeconomic indicators. The study indicates that macroeconomic variables assessed alongside loan data can significantly improve the forecasting performance of default model. The general finding demonstrates that higher percentage change in House Price Index, Consumer Sentiment Index and S&P500 Index is associated with a lower probability of delinquency. The empirical results also exhibit significant positive effect of unemployment rate and GDP growth rate on P2P loan default rates. Practical implications: The results have important implications for investors for whom it is of great importance to know the determinants of borrowers' creditworthiness and loan performance when estimating the investment in a certain P2P loan. In addition, the forecasting performance of the model could be applied by authorities in order to deal with the credit risk in P2P lending and to prevent the effects of increasing defaults on the economy. Originality/value: This paper fulfills an identified need to shed light on the association between specific macroeconomic indicators and the default risk from P2P lending within an economy, while the majority of the existing literature investigate loan and borrower information to evaluate credit risk of P2P loans and predict the likelihood of default. [ABSTRACT FROM AUTHOR]

Videogames are an increasingly prominent use case for blockchain technology (what has been termed 'cryptogaming'). Drawing on documents, such as industry presentations, social media posts, interviews and white papers, this article analyses discourses surrounding cryptogames, focusing on the claims made by cryptogame developers and investors. We ask two related research questions: What are the dominant visions of a cryptogaming future, imagined by and for various constituencies? And what sorts of values get realised in such an imagined future of game development and use? We argue that cryptogames imagine players and developers as financialised subjects, adopting attitudes and practices of risk and investment as salves to both microeconomic problems in the games industry as well as broader macroeconomic issues. [ABSTRACT FROM AUTHOR]

Young Innovative Companies have received considerable attention in the last decade in entrepreneurship and management literature. These firms need financial resources to develop but lack legitimacy in the eyes of investors. This paper empirically explores the determinants of fundraising by analysing 545 Italian innovative start-ups, as defined by the Law 221/2012. In an institutional perspective we propose a model that considers the effect of three different sources of legitimacy. Results show that team educational and professional diversity, incubation and IPRs play a significant role in legitimating the company in the fundraising process. [ABSTRACT FROM AUTHOR]

Summary: Plant‐Based Milk (PBM) alternatives have been a hype recently, drawing the high focus of investors, developers, and researchers. However, despite this surge in interest, the market size and potential of these products remain unclear. While several studies explored consumer perspectives on these alternatives, the variability in findings remains poorly understood. This systematic review aims to investigate consumer perceptions of PBM and to identify the factors associated with higher acceptance. Adhering to the PRISMA‐P methodology, searches on two major databases – Scopus and Web of Science – were conducted. Research papers published between 2019 and 2024 were screened to capture the most recent insights, resulting in thirty‐one articles. Among these studies, 71% were surveys, 50% were conducted in Europe and 46% in America. Additionally, 78% of the studies had a sample size of 500 participants or fewer, 71% assessed the perception of PBM alternative in general, while equally, 12.9% focused on soy‐based milk and 12.9% on coconut‐based milk. Overall, the studies evaluated preference for PBM over dairy milk, motives for consumption and other relevant factors. The research describes the socio‐demographic criteria associated with the high adoption rates of these products, the reasons for choosing dairy substitutes (such as curiosity, health benefits, or social influence), and the perceived advantages and barriers to their use. The expected outcomes of this study can provide valuable insights for designing effective marketing strategies for PBM and fostering the development of sustainable and healthy food systems. [ABSTRACT FROM AUTHOR]

In mean-variance portfolio optimization, multi-index models often accelerate computation, reduce input requirements, facilitate understanding, and allow easy adjustment to changing conditions more effectively than full covariance matrix estimation in many situations. In this paper, we develop a multi-index model-based portfolio optimization approach that takes into account aspects of the environment, social responsibility and corporate governance (ESG). Investments in assets related to ESG have recently grown, attracting interest from both academic research and investment fund practice. Various literature strands in this area address the theoretical and empirical relation among return, risk and ESG. Our portfolio optimization approach is flexible enough to take these literature strands into account and does not require large-scale covariance matrix estimation. An extension of our approach even allows investors to empirically discriminate among the literature strands. A case study demonstrates the application of our portfolio optimization approach. [ABSTRACT FROM AUTHOR]

Financial investigation decision is a complex affair that highly relies on expert knowledge. In the era of big data, it remains practical to make intelligent financial investigation decisions via computing technology. As a consequence, this work introduces reinforcement learning to search for effective decision schemes that are adaptive to the diverse financial environment. Therefore, an intelligent financial investment decision model based on multi-agent reinforcement learning is proposed in this paper. First, the long short-term memory (LSTM) model is utilized to strengthen financial investment data. Then, the hidden Markov model (HMM) is utilized to make a preliminary judgment on financial investment strategy. Next, a multi-agent deep deterministic policy gradient (MADDPG) is employed to set the goal of agent reinforcement and determine decision indicators based on the financial market environment. Multiple agents (investors) form a cooperative strategy through learning and interaction to achieve the optimal investment decision in the financial market. The experimental results on realistic data indicate that the proposal can play an important role in investment decision-making. [ABSTRACT FROM AUTHOR]

The privatization of public utilities marked a turning point in European capitalism, reshaping the relationship between the public and private spheres of the economy. However, the extent of state disinvestment varies greatly from country to country. While in some countries direct state ownership has disappeared, in others the state still acts as a reference shareholder in strategic companies. Despite their institutional similarities, Italy and Spain provide a puzzling example of this divergence. While Spain completed the privatization of all public utilities, the Italian state retains a controlling stake in many of them. Through historical case studies based on official documents, legal texts, archival research of newspaper articles, secondary sources and memoirs, this paper explains this divergence. Contributing to recent debates on patient capital and state-business interactions, it is argued that Spain completed the privatization process because the state was able to orchestrate the creation of shareholder alliances among private investors. Crucially, these investors were willing to ensure that management prioritizes long-term investment plans over the distribution of short-term financial profits. In the absence of domestic private providers of patient capital, the Italian state had to keep the role of anchor investor for itself after unsuccessfully experimenting with various privatization strategies. [ABSTRACT FROM AUTHOR]

The outbreak of the war in Ukraine has had a profound and far-reaching impact on the global economy, with notable repercussions observed in stock markets, and particularly pronounced effects evident in commodities markets. This paper examines the connectedness network among 27 NATO stock markets, Russian stock market and a set of three commodity indices (energy, precious metals, and agricultural commodities) over the period 2017-2023. The empirical strategy consists of time and time-frequency connectedness metrics. The empirical results reveal that the connectedness structure has shifted during the Russian-Ukrainian conflict. Moreover, hit by a series of Western sanctions, Russia's stock market appears to be the most isolated of the considered markets during the war period. Furthermore, the energy, agricultural and precious metals commodities seem to be efficient hedging instruments for investors in the stock markets of the NATO countries during the war period. [ABSTRACT FROM AUTHOR]

The International Code of Marketing of Breast‐milk Substitutes and subsequent resolutions (the Code) was adopted to address increases in mortality and morbidity resulting from the practices of the breast‐milk substitute (BMS) industry. The lack of success in ensuring company compliance with the Code has prompted advocates to consider engaging with investors to shape the governance of BMS companies. To support these efforts, this paper aimed to identify prominent investors in the global BMS industry and explore their Code‐related policies and practices. Using multiple methods and data sources, we developed a novel approach to identify and rank investors in the world's leading publicly listed BMS companies. We also examined the policies and voting behaviour of a sample of investors using publicly accessible materials from 2020 to 2022. We found that a small number of large investors, led by BlackRock and Vanguard, hold a substantial share in the global BMS industry. Of the top‐10 ranked investors, only Norway's Government Pension Fund (NBIM) reported policy information relating specifically to BMS marketing. Most of these large investors also opposed the sample of public health‐related shareholder proposals analysed. In addition, we identified several investors that have reported engaging with BMS companies on Code‐related issues, including NBIM, Pictet, and UBS, along with several potential investor targets for future advocacy efforts, including some North American public pension funds. The inclusion of Code‐related issues as part of broader policies, disclosures and regulations related to environmental, social and governance oriented investment warrants increased attention. [ABSTRACT FROM AUTHOR]

Forecasting stock prices is always considered as complicated process due to the dynamic and noisy characteristics of stock data influenced by external factors. For predicting the stock market, several approaches have been put forward. Many academics have successfully forecasted stock prices using soft computing models. Recently, there has been growing interest in applying deep learning techniques in combination with technical indicators to forecast stock prices, attracting attention from both investors and researchers. This paper focuses on developing a reliable model for anticipating future stock prices in one day advance using Long Short-Term Memory (LSTM). Three steps make up the suggested model. The approach begins with ten technical indicators computed from previous data as feature vectors. The second phase involves data normalization to scale the feature vectors. Finally, in the third phase, the LSTM model analyzes the closing price for the next day using the normalized characteristics as input. Two stock markets, NASDAQ and NYSE are chosen to evaluate the efficacy of the developed model. To demonstrate how effective the new model is in making predictions, its performance is compared to earlier models. Comparing the suggested model to other models, the findings revealed that it had a high level of prediction accuracy. [ABSTRACT FROM AUTHOR]

As the world progresses into the critical Year 2030, the magic Year for attaining the Sustainable Development Goals, doubts about the certainty of success are high. Amid COVID-19, the climate crisis, the Russia-Ukraine war, among many other wars, and the high cost of living pushing most of the people into poverty and hardship, it is time to reconsider what is being done to make the world a better place for most of the people. In doing this, this paper attempts to interrogate the influence of money in the consistent world economic crises. It argues that the 'inevitability of money', attendant on changing technology, pervading the World Capitalist System needs to be reoriented to homos sociologicus. In a way, it recommends the need to 'humanise' money and technology, such that humans construct it socially instead of vice versa. [ABSTRACT FROM AUTHOR]

This paper contributes to the literature on the expansion of Chinese multinational corporations (CMCs) in Papua New Guinea (PNG) by comparing the operation of a Chinese mine to that of the German New Guinea Company. I start by looking at the two economic positions (helper and merchant) performed by early Chinese immigrants to New Guinea during the colonial era and the host hostility they encountered.1 Then, a case study of a Chinese mining company in postcolonial PNG illustrates how local employees learned to negotiate with Chinese management through unionization instead of striking. In the meantime, Chinese personnel became subject to PNG industrial regulations based on Australian standards rather than operating as a modernizing agent to educate local workers.2 These findings suggest that, despite specific new Chinese communities becoming investors, they must dedicate resources towards comprehending local customs and legislation, given the enhanced agency of local actors. [ABSTRACT FROM AUTHOR]

Our paper presents the first optimal analytical solution for an investor maximizing both consumption and terminal wealth within expected utility theory in the realm of GARCH models. Working in a general family of affine GARCH models, we derive an affine GARCH optimal wealth process, providing analytical representations for optimal allocation, consumption and value functions. In particular, the optimal consumption ratio avoids the undesirable scenario of investors consuming all wealth prior to maturity. Our numerical study highlights the importance of formally accounting for consumption as it disrupts the level of optimal risky allocations. It also shows a larger impact of stochastic conditional variance (heteroscedasticity) on risky allocations in comparison to the impact of non-Gaussianity. We find, in a numerical study based on S&P 500 index data over a 5-years horizon, that an investor following a Gaussian GARCH strategy can achieve 10% more total consumption and at the same time 8% more terminal wealth than another investor following a constant variance (homoscedastic) strategy. [ABSTRACT FROM AUTHOR]

Media information plays an essential role in the stock market. Recent financial research has verified that media information could shock stock price by influencing investors' expectation. Now, a new type of interactive media, called Digital Interactive Media (DIM), is popular in Chinese stock market and becomes the main channel for investors to understand listed companies. Unlike general news media or investor forums, DIM enables direct interaction between listed companies and investors. In the modern society where digital economy is booming, media information would largely affect investors' decisions. Therefore, it is urgent to use natural language processing (NLP) technology to deconstruct the massive questions and answers (Q&A) interactive information in DIM and extract valuable factors that affect stock prices and stock performances to explore the influence mechanism of digital interactive information on stock performances. This paper firstly uses web crawling technology to obtain approximately 110000 Q&A text information from the digital interactive platform ('Panoramic Network') from 2015 to 2021. Then we use big data text analysis technology and emotional quantification technology to extract valuable influencing factors from the massive text. A Multiple Linear Regression (MLR) model was created to explore specific influence mechanism of digital interactive information on stock price performance. The empirical results show that the emotions implicit in investors' questions do not significantly impact stock performance. However, the emotions and attitudes of the answers by listed companies can significantly affect corresponding stock prices, which indirectly confirms the Proximate Cause Effect of behavioral finance. This effect is particularly evident in the stock prices on the current trading day and the next trading day. In the Robustness Test, this paper replaces dependent variable and adds relevant control variables, and the conclusion remains valid. In the Endogeneity Test, this paper selects sample data before the launch of Panorama Network in 2014 as a comparison, and uses a Difference-in-Difference (DID) model to prove the significant impact of the launch of Panorama Network on Chinese stock market. In the Heterogeneity Test, the paper classifies the market value, region, and industry of listed companies and regressed the sub samples, once again confirming the reliability of the empirical conclusions. The results of Robustness Test, Endogeneity Test, and Heterogeneity Test conducted in this paper all support empirical conclusions. [ABSTRACT FROM AUTHOR]

With the increasing importance of the stock market, it is of great practical significance to accurately describe the systemic risk of the stock market and conduct more accurate early warning research on it. However, the existing research on the systemic risk of the stock market lacks multi-dimensional factors, and there is still room for improvement in the forecasting model. Therefore, to further measure the systemic risk profile of the Chinese stock market, establish a risk early warning system suitable for the Chinese stock market, and improve the risk management awareness of investors and regulators. This paper proposes a combination model of EEMD-LSTM, which can describe the complex nonlinear interaction. Firstly, 35 stock market systemic risk indicators are selected from the perspectives of macroeconomic operation, market cross-contagion and the stock market itself to build a comprehensive indicator system that conforms to the reality of China. Furthermore, based on TEI@I complex system methodology, an EEMD-LSTM model is proposed. The EEMD method is adopted to decompose the composite index sequence into intrinsic mode function components (IMF) of different scales and one trend term. Then the LSTM algorithm is used to predicted and model the decomposed sub-sequences. Finally, the forecast result of the composite index is obtained through integration. The empirical results show that the stock market systemic risk index constructed in this paper can effectively identify important risk events within the sample period. In addition, compared with the benchmark model, the EEMD-LSTM model constructed in this paper shows a stronger early warning ability for systemic financial risks in the stock market. [ABSTRACT FROM AUTHOR]

This paper explores the application of Random Matrix Theory (RMT) as a methodological enhancement for portfolio selection within financial markets. Traditional approaches to portfolio optimization often rely on historical estimates of correlation matrices, which are particularly susceptible to instabilities. To address this challenge, we combine a data preprocessing technique based on the Hilbert transformation of returns with RMT to refine the accuracy and robustness of correlation matrix estimation. By comparing empirical correlations with those generated through RMT, we reveal non-random properties and uncover underlying relationships within financial data. We then utilize this methodology to construct the correlation network dependence structure used in portfolio optimization. The empirical analysis presented in this paper validates the effectiveness of RMT in enhancing portfolio diversification and risk management strategies. This research contributes by offering investors and portfolio managers with methodological insights to construct portfolios that are more stable, robust, and diversified. At the same time, it advances our comprehension of the intricate statistical principles underlying multivariate financial data. [ABSTRACT FROM AUTHOR]

This paper delves into the critical role of tax credits, specifically Sections 45Q and 45V, in the financing and economic feasibility of low-carbon-intensity hydrogen projects, with a focus on natural-gas-based hydrogen production plants integrated with carbon capture and storage (CCS). This study covers the current clean energy landscape, underscoring the importance of low-carbon hydrogen as a key component in the transition to a sustainable energy future, and then explicates the mechanics of the 45Q and 45V tax credits, illustrating their direct impact on enhancing the economic attractiveness of such projects through a detailed net present value (NPV) model analysis. Our analysis reveals that the application of 45Q and 45V tax credits significantly reduces the levelized cost of hydrogen production, with scenarios indicating a reduction in cost ranging from USD 0.41/kg to USD 0.81/kg of hydrogen. Specifically, the 45Q tax credit demonstrates a slightly more advantageous impact on reducing costs compared to the 45V tax credit, underpinning the critical role of these fiscal measures in enhancing project returns and feasibility. Furthermore, this paper addresses the inherent limitations of utilizing tax credits, primarily the challenge posed by the mismatch between the scale of tax credits and the tax liability of the project developers. The concept and role of tax equity investments are discussed in response to this challenge. These findings contribute to the broader dialogue on the financing of sustainable energy projects, providing valuable insights for policymakers, investors, and developers in the hydrogen energy sector. By quantifying the economic benefits of tax credits and elucidating the role of tax equity investments, our research supports informed decision-making and strategic planning in the pursuit of a sustainable energy future. [ABSTRACT FROM AUTHOR]

Climate change is a financial risk to companies, and those that disregard this will have to deal with losses due to extreme weather events, new regulations, or the disruption of the supply chain. Companies must disclose climate-related financial implications to enable informed decision-making by investors and other stakeholders. Any indifference or disregard for climate-related disclosures will harm the investors who may trade based on insufficient information and prices of securities that do not account for climate risks. In India, disclosures are mandated for companies under the Companies Act 2013 and various Securities and Exchange Board of India Regulations. This paper will explore the adequacy of the current disclosure regime concerning climate change and argue that, although information regarding climate risks falls within the ambit of the current set of mandated disclosures, it is insufficient. The paper concludes by making a case for mandatory climate disclosures under the Companies Act. [ABSTRACT FROM AUTHOR]

This paper discusses finding solutions to the modified Fractional Black–Scholes equation. As is well known, the options theory is beneficial in the stock market. Using call-and-pull options, investors can theoretically decide when to sell, hold, or buy shares for maximum profits. However, the process of forming the Black–Scholes model uses a normal distribution, where, in reality, the call option formula obtained is less realistic in the stock market. Therefore, it is necessary to modify the model to make the option values obtained more realistic. In this paper, the method used to determine the solution to the modified Fractional Black–Scholes equation is a combination of the finite difference method and the fractional differential transformation method. The results show that the combined method of finite difference and fractional differential transformation is a very good approximation for the solution of the Fractional Black–Scholes equation. [ABSTRACT FROM AUTHOR]

The purpose of this study paper is to examine Jordan's mineral development and investment policies. Mining policies that attract foreign investment must handle both traditional investor concerns and some new challenges. The paper delves deeply into issues such as a country's geological, political, financial, regulatory, operational, fiscal, social, and environmental characteristics, as well as profit and marketing factors. After analyzing these criteria for Jordan, they were compared to the MENA region in order to provide insights into potential changes and improvements to both the MENA and Jordan mineral policies. International investors have not been drawn to Jordan's mineral resource sector for a number of reasons, including—but not limited to—a lack of digitally available and accessible geological data, lack of access to finance exploration projects, an unfavorable legal and fiscal environment, lack of many of the best practices for transparency standards, and lack of awareness and promotion of Jordan's mineral potential among international businesses. For Jordan to improve its standing in the world for investing in mining, it needs effective mining regulations, effective regulatory agencies, very lenient foreign investment laws, highly competitive tax system, enormous geologic potential, highly qualified personnel, exceptional local expertise and skills, modern infrastructure, and stable political and economic systems. [ABSTRACT FROM AUTHOR]

Carbon allowance prices (CAP) directly reflect the overall movement of the carbon market, which is the core of the carbon market operation and an important perspective for studying the carbon market. Based on the threshold model and regime switching model, through studying the performance of CAP in China's carbon market, the paper has the following conclusions. First, CAP show significant non-linear structure and three operating intervals of high, medium, and low, with most of the time being active in the medium and low intervals. Second, there is a stabilization mechanism in the current operation of CAP, which can adequately regulate the trend of CAP fluctuations and eventually converge back to the normal state. Finally, it is found that moderate increases are the main form of CAP volatility in China's carbon market, but other possible states and the risk of abnormal CAP volatility due to state transformation still exist. Furthermore, for investors, China's carbon market may be an ideal place to make long-term investments and hedge risks in the future. This paper provides theoretical support for investors and regulators in the carbon market to make scientific decisions based on the carbon market. [ABSTRACT FROM AUTHOR]

At present, with the increasing digital competition among enterprises, it is of great importance for enterprises to promote digital transformation and achieve sustainable development. Taking China's A-share listed companies from 2007 to 2021 as samples, this paper performs empirical tests in order to explore the impact of enterprise digital transformation on the comparability of accounting information and its mechanism. The results show that digital transformation has significantly enhanced accounting information comparability, which is still significant after a series of robustness tests. The mechanism test shows that the improvement of the comparability of accounting information by the digital transformation is mainly achieved by alleviating earnings management and agency problem. Further research shows that when the degree of market competition or transparency is high, the role of enterprise digital transformation in enhancing the comparability is more significant. This paper enriches the literature on the economic consequences of digital transformation and the factors affecting the comparability of accounting information. At the same time, the conclusions of this paper confirm the governance effect of enterprise digital transformation, provide evidential support for investors to improve decision-making efficiency, and urge enterprises to accelerate digital transformation. [ABSTRACT FROM AUTHOR]

The following research paper conducts a comprehensive analysis into the intricate dynamics governing the relationship between Foreign Direct Investment (FDI) and International Trade, with a specific focus on the Western Balkan Countries-6 (WB-6). This research spans the period from 2000 to 2020 and seeks to shed light on the interplay between FDI and International Trade within this region. To analyse and interpret these dynamics, various regression models, including Ordinary Least Squares (OLS), Fixed Effects, Random Effects, and the Hausman-Taylor model, are employed as analytical tools. Moreover, the research takes into consideration the influence of specific institutional factors within each country, which play a pivotal role in shaping foreign investors' decisions to invest in a particular country. The study's results reveal that gravity factors, in conjunction with institutional determinants such as economic integration, control of corruption, political stability, and other indicators of governance quality, significantly impact the attractiveness of the WB-6 countries to foreign investors. The findings of this paper hold substantial relevance for the development of an analytical framework aimed at evaluating national policies and institutions geared towards enhancing the appeal of Western Balkan countries to foreign investors. Furthermore, the research underscores the importance of these host countries prioritizing efforts to bolster the effectiveness of governmental institutions, combat corruption, streamline bureaucratic processes, and improve overall economic conditions to attract and retain foreign investment. [ABSTRACT FROM AUTHOR]

Since financial assets on stock exchanges were created, investors have sought to predict their future values. Currently, cryptocurrencies are also seen as assets. Machine learning is increasingly adopted to assist and automate investments. The main objective of this paper is to make daily predictions about the movement direction of financial time series through classification models, financial time series preprocessing methods, and feature selection with genetic algorithms. The target time series are Bitcoin, Ibovespa, and Vale. The methodology of this paper includes the following steps: collecting time series of financial assets; data preprocessing; feature selection with genetic algorithms; and the training and testing of machine learning models. The results were obtained by evaluating the models with the area under the ROC curve metric. For the best prediction models for Bitcoin, Ibovespa, and Vale, values of 0.61, 0.62, and 0.58 were obtained, respectively. In conclusion, the feature selection allowed the improvement of performance in most models, and the input series in the form of percentage variation obtained a good performance, although it was composed of fewer attributes in relation to the other sets tested. [ABSTRACT FROM AUTHOR]

AbstractUnderstanding how urban recreational amenities are agglomerated and clustered with each other is crucial. This paper attempts to reveal the features of such spatial agglomeration patterns by innovatively developing a model termed as spatial agglomeration mining. Based on the case of Greater Bay Area in China, it achieves three conclusions. First, recreational amenities are highly agglomerated rather than evenly distributed at both regional and urban scales. Second, the regional and urban agglomeration patterns are similar in the sense that the agglomeration core is mainly composed of convenience-service amenities, while the periphery is mainly composed of leisure and entertainment amenities. Third, cities with similar size and economic functions share a similar structure, whereas amenities with a larger number do not guarantee a more central position in the clusters. This study sheds light on the general principle’s relativeness among amenities for urban investors and managers to make better decisions. [ABSTRACT FROM AUTHOR]

The impact of exchange rate (ER) movements on the trade balance has been extensively debated in the literature, with conflicting views on the nature and magnitude of this effect. This paper investigates the relationship between ER movements and trade balance in developing economies, with a specific focus on bilateral analysis involving Pakistan. Employing the Nonlinear Autoregressive Distributed Lag (NARDL) model, our results reveal a symmetric relationship between positive and negative ER changes and the trade balance, showing significant long-term and short-term effects across the panel of developing economies. However, country-specific asymmetries are observed, especially in the cases of India and China, and are more pronounced in each bilateral analysis, whether in the short run or long run. The study findings highlight the critical importance of maintaining a stable exchange rate policy, which can provide policymakers with precise insights into the money market and the broader economy while preventing high volatility and continuous depreciation of domestic currencies. Such measures can mitigate the long-term adverse effects of ER movements on trade agreements. The study offers valuable insights for policymakers and investors in developing economies, aiding them in making informed decisions about exchange rate policies. [ABSTRACT FROM AUTHOR]

This paper examines equilibrium asset prices and leverage in an exchange economy populated with both retail and institutional investors. Institutional investors influence the price of the stocks they trade and are aware of the price impact of the opponent and, thus, interact strategically. Because of the price impact, institutional investors decrease their demand for stocks and lend money to the retail sector, thereby increasing leverage in the economy. The risk-free rate (equity premium) tends to be lower (higher) as compared to an economy populated by retail investors only. Retail investors' compensation for liquidity provision depends on the behavior of institutional investors and the state of the economy. [ABSTRACT FROM AUTHOR]

This paper examines the effects of the collateral-based monetary policy, implemented by the People's Bank of China, on green financing costs. Employing a Difference-in-Differences (DID) method to examine credit spreads of financial bond in primary and secondary markets from 2017 to 2019, our findings highlight a significant decrease of 26 basis points (bps) in the financing costs of green financial bonds in the primary market, with a 12-bps decline in the secondary market post-policy. Our study underscores the crucial role of implicit credit enhancement provided by the People's Bank of China's collateral endorsement. Interestingly, the liquidity provision mechanism, where investors pay premiums to secure liquidity support, does not find empirical backing in the specific context of China's bond market. These findings illuminate the effectiveness of collateral-based monetary policies in reducing green financing costs, offering valuable insights for using collateral strategies to green monetary policies. Collateral-based policies' success in reducing green financing costs suggests a strategic avenue for supporting green monetary policy goals. Implicit credit enhancement serves as a crucial mechanism driving this cost reduction. The People's Bank of China's experience exemplifies the robustness of such policies without requiring strict collateral scarcity, highlighting broad policy applicability. Collateral-based monetary policy could drive the 'green premium', broadening green bond appeal beyond just environmentally-focused investors. [ABSTRACT FROM AUTHOR]

We examine how investors' perceptions of firms' philanthropic behaviors alter the effect of corporate philanthropy on costs of equity capital. Using a sample of Chinese A‐share listed firms from 2007 to 2018, we find that firms making philanthropic donations have higher equity financing costs. In contrast, firms without politically connected executives, experiencing provincial official turnovers, and located in provinces with fiscal pressure do not see an increase in costs of equity capital. In addition, Chinese investors consider strategic corporate philanthropy to establish political connections less valuable after anticorruption campaigns are launched, hence requiring higher rates of return from firms making monetary donations. Overall, this paper provides evidence that investors' perceptions of firm behavior are shaped by unique institutional factors in emerging markets, resulting in unintended economic consequences for firms. [ABSTRACT FROM AUTHOR]

This paper compares the hedging and safe haven properties of clean (renewable) energy and unclean (non-renewable) energy stocks. Using around 20 years of monthly clean and unclean energy indices and applying the GARCH and quantile regression models with dummy variables, we find that likewise the unclean energy stocks renewable energy stocks provide a weak hedge and a safe haven against the global economic policy uncertainty and its extreme values even during the pandemic and low and high return environments. These findings suggest that clean energy stocks provide immunity to investors against unfavourable changes to economic policy uncertainty and market volatility. [ABSTRACT FROM AUTHOR]

In the context of global economic digitalization, financial information is highly susceptible to internet financial public opinion due to the overwhelming and misleading nature of information on internet platforms. This paper delves into the core entities in the diffusion process of internet financial public opinions, including financial institutions, governments, media, and investors, and models the behavioral characteristics of these entities in the diffusion process. On this basis, we comprehensively use the multi-agent model and the SIR model to construct a dynamic evolution model of internet financial public opinion. We conduct a simulation analysis of the impact effects and interaction mechanisms of multi-agent behaviors in the financial market on the evolution of internet financial public opinion. The research results are as follows. Firstly, the financial institutions' digitalization levels, government guidance, and the media authority positively promote the diffusion of internet financial public opinion. Secondly, the improvement of investors' financial literacy can inhibit the diffusion of internet financial public opinion. Thirdly, under the interaction of multi-agent behaviors in the financial market, the effects of financial institutions' digitalization level and investors' financial literacy are more significant, while the effects of government guidance and media authority tend to converge. [ABSTRACT FROM AUTHOR]