Financial Investment Research Articles

AI-driven robo-advisors on personal financial management and investment strategies

The advent of AI-driven robo-advisors has revolutionized personal financial management and investment strategies. Leveraging sophisticated algorithms and machine learning, these platforms offer personalized financial advice and automated portfolio management with minimal human intervention. By analyzing vast datasets, including market trends, economic indicators, and individual client preferences, robo-advisors can create tailored investment plans that optimize returns and manage risks effectively. This paper explores the transformative impact of AI in democratizing financial advice, enhancing decision-making processes, and making investment management accessible to a broader audience. The integration of AI in robo-advisory services not only improves efficiency but also provides a scalable solution to meet the diverse financial needs of individuals.

Internet use and household financial market participation: evidence from China

ABSTRACT This paper examines the effect of internet use on household financial market participation and its underlying mechanism. Using data from the 2018 China Family Panel Studies (CFPS), we find that households with internet use are 4.7% more likely to participate in financial market investments than those without. The finding remains robust after accounting for endogeneity concerns using the instrumental variables approach and a fresh double machine learning approach. We highlight the phenomenon of ‘digital divide’ that the positive effects of internet use on making financial investments are more substantial among families living in economically developed regions, and families with higher income and education levels than their counterparts. We identify three novel mechanisms through which internet use affects household investment decision-making, namely the internet information mechanism, the internet social mechanism, and the internet enabling mechanism. These findings suggest that expanding digital infrastructure building and increasing the number of internet users are important ways to enhance households’ participation in financial markets.

Capital structure decisions in the energy transition: Insights from Spain

The renewable energy transition depends heavily on capital structure decisions of energy firms. Most previous research has focused on the decisions of oil companies. This study investigates the financing of new investment in the Spanish renewable energy sector, including decisions about: i) equity versus debt, ii) short versus long-term debt, and iii) equity issuances versus retained earnings for new investment. Our analysis is based on data from over 22,000 energy firms from 2008 to 2021 and shows that these firms prefer debt over equity (more than 90% of changes in assets are financed through increasing debt) and have extended the term of the debt over the period studied (reaching a maximum of almost 73% long-term debt in 2021). The deployment of retained earnings is less usual than raising new equity capital. Our analysis points to a generalized use of project finance to support new investments. Policymakers should focus on increasing financing through equity and thus diversifying the financial risk of the energy transition. In addition, a supportive fiscal policy and a stable regulatory environment are desirable for achieving this goal.

PROGRESSO DO BRASIL NA IMPLEMENTAÇÃO DE ÁREAS COSTEIRAS E MARINHAS PROTEGIDAS COM FOCO NA META 11 DE AICHI

he rapid global loss of biodiversity has promoted initiatives to develop a global network of Protected Areas (PAs), with the Aichi targets suggesting that countries protect at least 17% of continental areas and 10% of marine and coastal areas. For Brazil, there is a knowledge gap regarding the evaluation of qualitative and quantitative objectives through practical indicators of goal achievement and effective management. This study holistically addresses the conservation status of Brazil concerning Aichi Target 11 for marine and coastal ecosystems, using systematic literature review and marine spatial coverage analysis. The results show an increase to 26% of marine spatial coverage, with greater coverage by Environmental Protection Areas. There is a predominance of studies on "Management Effectiveness," with less focus on equitable management and integration between terrestrial and marine landscapes. Indicators primarily focus on "Ecological" and "Governance" dimensions, neglecting "Social" and "Economic" dimensions. Key challenges include the need for increased financial investment, connectivity between protected areas with different social and ecological contexts, and local community involvement in equitable management. Additionally, there is a need for increased coverage of integral protection areas and standardization of qualitative assessments. Keywords: Protected areas; Management effectiveness; Aichi Target 11; Conservation policy; Coastal and marine systems.

Assessing Awareness and Understanding of Gold ETFs Among Residents of Amravati City

This study investigates the level of awareness and understanding of Gold Exchange-Traded Funds (ETFs) among citizens of Amravati City. As a modern investment option, Gold ETFs offer a convenient and secure method for individuals to invest in gold without the physical burden of ownership. Despite their growing popularity, awareness of Gold ETFs remains limited, particularly in smaller urban areas. Using a quantitative approach, this research collects primary data through surveys to evaluate knowledge, perceptions, and investment intentions regarding Gold ETFs among local residents. The findings aim to inform stakeholders about existing gaps in awareness and suggest strategies for enhancing financial literacy and investment participation.

Exploring the Impact of Employee Motivation on Investment Decisions: - A Study of Factors Influencing Mutual Fund Investment Among Corporate Employee

This study explores the impact of employee motivation on investment decisions, specifically focusing on the factors influencing mutual fund investments among corporate employees. As financial literacy and investment participation grow, understanding the underlying motivations that drive investment choices is crucial for both individuals and financial institutions. Utilizing a mixed-methods approach, we conducted surveys and in-depth interviews with corporate employees across various sectors. The findings reveal that intrinsic motivations, such as personal financial goals and career advancement, significantly influence mutual fund investment decisions. Additionally, extrinsic factors, including company-sponsored financial education programs and peer influence, play a critical role in shaping employees' investment behaviors. Our analysis indicates that motivated employees are more likely to engage in proactive financial planning and make informed investment choices. We also identified barriers such as risk aversion and lack of confidence in investment knowledge that hinder mutual fund participation. The implications of this study suggest that organizations should enhance employee motivation through targeted financial education initiatives and create a supportive investment culture. By doing so, companies can not only improve employee financial well-being but also foster a more engaged and motivated workforce. This research contributes to the existing literature on employee motivation and investment behavior, offering insights for corporate stakeholders and financial advisors aiming to enhance mutual fund investment strategies among employees.

The Impact of Digital Finance on the Efficiency of Urban Green Economy

Digital finance is a new financing model for small and medium-sized enterprises and individuals. In recent years, with the rapid development of big data, cloud service technology, and artificial intelligence (AI) technology, it has to some extent promoted the efficient development of urban green economy. From the perspective of applying digital finance to urban enterprises and individual consumers, this study explores the important role of digital finance in enterprise investment and financing services, industrial structure upgrading, technological innovation, and the promotion of personal credit, consumption patterns, job employment, and environmental participation activities. Based on this, the impact of digital finance on the operation and efficiency improvement of urban green economy is obtained, and the problems of inadequate digital transformation and low coordination level in different industries of the city's economy are solved.

Digital financial inclusion, environment volatility and investment efficiency: demand and supply side experiences of Chinese listed renewable energy firms

Digital financial inclusion, environment volatility and investment efficiency: demand and supply side experiences of Chinese listed renewable energy firms

The Use of Primates as Experimental Models in Scientific Research and its Ethical Implications

Non-human primates (NHPs) are considered ideal experimental models for replicating human diseases, due to their physiological, anatomical and neurological similarities to humans. However, the use of NHPs in research has ethical considerations and requires significant financial and temporal investments, due to the costs involved in the process and evaluation time. In addition to ethical issues and legal protection, research with experimental primate models involves advantages, such as the extreme physiological similarity, and disadvantages, such as the difficulty in establishing parameters for pain management and assessment. This literature review analyzed articles from the Pubmed, Scopus and Web of Science databases published in the last five years. This review included 12 articles that addressed topics such as scientific research, primate therapies, animal welfare and legal protection, highlighting the relevance of NHPs in scientific studies and interest in using these models to understand human diseases in order to develop new therapies. Despite the ethical challenges involved in this issue, it was discussed that it is important to take into account the scientific benefits and ethical considerations, as well as developing alternative methods to reduce the use of primates in research.

Relationships between work-family conflict, infertility-related stress, resilience and social support in patients undergoing infertility treatment

ABSTRACT Fertility treatments can be physically and psychologically exhausting for those who do it due to high expectations and possible frustration with the negative results. Moreover, it demands time and high financial investment, which are sometimes stressful factors for the working patient. Two aspects that can ease this context are resilience and social support. The present article aims to investigate the levels of work-family conflict in individuals undergoing infertility treatment and their associations with stress, resilience, and social support. The survey of 242 patients addressed sociodemographic data, Infertility-Related Stress Scale-Brazil (IRSS-BP), Connor-Davidson Resilience Scale 10 (CD-RISC 10), Perceived Social Support Scale (PSSS), and Work-Family Conflict Scale. Data were analyzed using R (4.3.2). Findings suggest that the level of Work-Family Conflict is higher in men (p = 0.020). The scale is also positively associated with Infertility Stress and negatively correlated with Resilience and Social Support.

Strong financial regulation and enterprise digital innovation: promoting or inhibiting?

ABSTRACT Modern financial regulatory systems are vital in bridging the gap between digital and real economies. In this context, enterprises have the opportunity to achieve digital innovation transformation. This study examines the causal relationship between strong financial regulation and enterprise digital innovation using a quasi-natural experiment, focusing on the ‘Guiding Opinions on Regulating the Asset Management Business of Financial Institutions’ (NAMR). We observed a significant improvement in enterprises’ level of digital innovation after the NAMR implementation. Channel analysis confirms the micro-mechanisms of strong financial regulation, eased corporate financing constraints, increased R&D investment, and digital innovation. Furthermore, digital innovation driven by strong financial regulation can significantly improve corporate profitability. We also found that the positive effect of strong financial regulation on enterprise digital innovation is particularly significant in non-state-owned enterprises, highly competitive industries, and regions with high financial development levels. This study expands the understanding of how strong financial regulation affects enterprises’ digital innovation, with practical significance for understanding the relationship between financial regulation, corporate financial investment, and innovation decision-making.

Integrated energy services in parks: Analyzing stakeholder dynamics and innovation under the REITs model through 23 policy documents

Industrial parks are significant consumers of energy, contributing to global carbon emissions and intensifying the need for strategic interventions to meet carbon reduction and energy efficiency goals. In China, the Real Estate Investment Trusts (REITs) model has been adopted to advance the development of Integrated Energy Services (IESs) within these parks. This paper analyzes 23 Chinese government policy documents to explore the key stakeholders in park-based IESs, particularly the central role of energy companies in shaping collective decision-making processes. The study highlights how business models, including financial investment, offline and digital services, and innovative practices, have evolved under the REITs framework to drive the development of IESs and foster collaboration among stakeholders.

A Multi-Agent Financial Investment Decision Method Based on Evolutionary Game

Data-driven smart investment decisions are important for financial development, which has not received much attention from academia. As a result, this paper resorts to the evolutionary game theory, and proposes a novel multi-agent financial investment decision method. Specifically, an evolutionary game theory-based decision-making approach is formulated as the main model for the research purpose. By considering the strategic choices and adaptability among various entities, a comprehensive analysis of the behavior and decision-making process of entities in the financial market is achieved. This paper combines stock exchanges and financial data providers (Bloomberg and Thomson Reuters) to conduct case studies on this method, verifying its effectiveness and feasibility in practical applications. By comparing traditional financial investment decision-making methods, it can be seen that the proposal has significant advantages in improving investment efficiency, reducing risks, and responding to market volatility. This paper delves into the multi-agent financial investment decision-making method based on the evolutionary game, providing new ideas and methods for academic research and practical applications in the financial field.

AI-Driven Insight into Polycarbonate Synthesis from CO2: Database Construction and Beyond

Recent advancements in materials science have garnered significant attention within the research community. Over the past decade, substantial efforts have been directed towards the exploration of innovative methodologies for developing new materials. These efforts encompass enhancements to existing products or processes and the design of novel materials. Of particular significance is the synthesis of specific polymers through the copolymerization of epoxides with CO2. However, several uncertainties emerge in this chemical process, including challenges associated with successful polymerization and the properties of the resulting materials. These uncertainties render the design of new polymers a trial-and-error endeavor, often resulting in failed outcomes that entail significant financial, human resource, and time investments due to unsuccessful experimentation. Artificial Intelligence (AI) emerges as a promising technology to mitigate these drawbacks during the experimental phase. Nonetheless, the availability of high-quality data remains crucial, posing particular challenges in the context of polymeric materials, mainly because of the stochastic nature of polymers, which impedes their homogeneous representation, and the variation in their properties based on their processing. In this study, the first dataset linking the structure of the epoxy comonomer, the catalyst employed, and the experimental conditions of polymerization to the reaction’s success is described. A novel analytical pipeline based on ML to effectively exploit the constructed database is introduced. The initial results underscore the importance of addressing the dimensionality problem. The outcomes derived from the proposed analytical pipeline, which infer the molecular weight, polydispersity index, and conversion rate, demonstrate promising adjustment values for all target parameters. The best results are measured in terms of the (Determination Coefficient) R2 between real and predicted values for all three target magnitudes. The best proposed solution provides a R2 equal to 0.79, 0.86, and 0.93 for the molecular weight, polydispersity index, and conversion rate, respectively. The proposed analytical pipeline is automatized (including AutoML techniques for ML models hyperparameter tuning), allowing easy scalability as the database grows, laying the foundation for future research.

Exploring the impact of industrialization and electricity use on carbon emissions: The role of green FinTech in Asian countries using an asymmetric panel quantile ARDL approach

PurposeThe purpose of this study is to investigate how industrialization, financial development, electricity consumption, trade openness, and green FinTech affect on carbon emissions asymmetrically in Asian countries. DesignMethod/Approach: The study examined 29 years of panel data from 39 Asian countries from 1995 to 2022, sourced from World Development Indicators (WDI) and the International Monetary Fund (IMF). The study constructs a green financial technology index using principal component analysis (PCA). The study utilizes an Asymmetric Panel Quantile Autoregressive Distributive Lag (A-QARDL) model with pooled mean group (PMG) specifications to explore effects that exhibit cross-sectional homogeneous in the long-run, but heterogeneous in the short-run effects. FindingsIndustrialization and financial development have a strongly asymmetric impact on carbon emissions. Industrialization causes an increase in carbon emissions at various quantiles, while green FinTech plays a crucial role in mitigating these carbon emissions. Trade openness and domestic credit to the private sector also help reduce carbon emissions. Research limitations and implicationsThe study emphasizes the significance of employing green FinTech techniques and using renewable energy sources to meet sustainable industrialization and sustainability goals in Asian countries. The policy consequences include promoting environmentally friendly industrial practices, encouraging green financial investments, and boosting government financing for private sector research and development to mitigate carbon emissions. Originality/valueThe study employs robust modeling to analyze the role of green FinTech to enhance industrial sustainability. Both Industrialization and deindustrialization have an impact on economic emissions, and the potential of green FinTech's to promote sustainability contributes to the environment protection strategy.

Systems modelling and simulation to guide targeted investments to reduce youth suicide and mental health problems in a low–middle-income country

BackgroundDespite suicide’s public health significance and global mental health awareness, current suicide prevention efforts show limited impact, posing a challenge for low- and middle-income countries. This study aimed to develop a dynamic simulation model that could be used to examine the potential effectiveness of alternative interventions for reducing youth mental health problems and suicidal behavior in Bogotá, Colombia.MethodsA system dynamics model was designed using a participatory approach involving three workshops conducted in 2021 and 2022. These workshops engaged 78 stakeholders from various health and social sectors to map key mental health outcomes and influential factors affecting them. A model was subsequently developed, tested, and presented to the participants for interactive feedback, guided by a moderator. Simulation analyses were conducted to compare projected mental health outcomes for a range of intervention scenarios with projections for a reference scenario corresponding to business-as-usual.ResultsA total of 6670 suicide attempts and 347 suicides are projected among 7 − 17-year-olds from January 1, 2023, to early 2031 under the business-as-usual scenario. Mental health issues among 12 − 17-year-olds are projected to increase from 18.9% (2023) to 27.8% (2031), and substance use issues from 2.29 to 2.49% over the same period. School-based suicide prevention and gatekeeper training are the most effective strategies, reducing total numbers of suicide attempts and suicides by more than 20% (i.e., compared to business-as-usual). However, discontinuous funding significantly hinders these effective suicide prevention efforts.ConclusionsSystems modelling is an important tool for understanding where the best strategic financial and political investments lie for improving youth mental health in resource-constrained settings.

The influence mechanism of internet finance on residents’ online consumption

This study investigates the impact of Internet finance (IF)11Internet finance (IF): Traditional financial institutions and Internet enterprises use Internet technology and information communication technology to realize the new financial business model of financial financing, payment, investment and information intermediary services.on residents’ online consumption using annual data from 2013 to 2022 in China. To examine the impact of IF on overall consumption, survival, development, and enjoyment, four vector autoregressive models are constructed. This study employs comprehensive methods, including parameter estimation, impulse response function analysis, and variance decomposition. Findings reveal that the development of IF has significantly stimulated residents’ online consumption, with the increase in developmental expenditure being the most significant, followed by the increase in entertainment expenditure.

Explanatory Factors of the Accounting Choices for Investments Under IAS 27 of Listed European Union Entities

ABSTRACTThis study aims to analyze the explanatory factors of the accounting choices for investments of entities with securities traded on regulated markets from the European Union (EU) under International Accounting Standards (IAS) 27—Separate Financial Statements (SFS). According to IAS 27, investments in their scope can be accounted for by using the cost, equity method, or fair value, which represents alternative accounting methods commonly known in the literature as accounting choices. To identify the factors that may explain the accounting choices for investments under IAS 27, a logistic regression model is used. The research covers listed entities from 19 out of the 21 EU countries where IAS 27 is required or permitted. The findings highlight that the entities’ size and investment weight likely explain the adoption of the cost method, conversely to the size of the board of directors, which negatively explains its use. Accounting choices for investments under SFS are not yet explored in the literature. Moreover, this research also proposes further explanatory factors in the scope of the literature on accounting choices. This paper can potentially benefit a diverse set of stakeholders, namely the accounting standard‐setters, as they can draw attention to the comparability issues from the use of accounting choices, which may mitigate the financial information usefulness for decision‐making. Furthermore, auditors, supervisors, as well as investors and other users, can have a more comprehensive perspective of the reasons behind the method chosen by entities for accounting for their financial investments.

Contextual embedded text summarizer system: A hybrid approach

AbstractSelecting crucial sentences from a document is a pivotal task in automatic text summarization systems. Abstractive summarization involves rephrasing key content through advanced natural language techniques, generating a concise, new text conveying critical information. Conversely, extractive summarization reproduces important material from the original text. In the proposed method, a hybrid ensemble approach combines BERTsum for extractive summarization and Longformer2Roberta for abstractive summarization for generating a contextual semantic rich summary for a huge collection of text. These proposed system‐generated summaries were evaluated against reference summaries using the ROUGE package at three rouge levels (Rouge‐1, Rouge‐2, and Rouge‐L). The Proposed contextual embedded hybrid text summarization model has shown significant performance improvement in multiple levels of Rouge score and word mover distance (WMD) of generated summary with a reference summary. The proposed hybrid model demonstrates superior performance over existing state‐of‐the‐art summarizing models on three distinct datasets CNN dataset, WikiSum, and Gigaword dataset. The proposed hybrid model as a text summarizer involves leveraging its capabilities to process longer sequences of text with domain‐specific contextual summaries. This transformers‐based text summarization model has great potential in developing expert systems in various research domains such as health decision support systems, the education sector, customer support chatbots, financial analysis investment recommendations, and financial assistance.

The Significance and Practical Exploration of Financial Investment Management in Enterprise Operation and Management

Enterprises can carry out financial investment activity management, and through institutional control, risk prevention and other methods, ensure the stability of financial investment activities, enhance their own risk resistance ability, and provide support for the healthy and long-term development of enterprises. Based on this, this article briefly analyzes the significance and value of financial investment management in enterprise operation and management, elaborates on the current overview of enterprise financial investment management, and explores in depth the path of financial investment management in enterprise operation and management.