Finance Database Research Articles

The Role of AI in Financial Markets: Impacts on Trading, Portfolio Management, and Price Prediction

Today artificial intelligence (AI) has become an indispensable assistance for human traders. AI systems provide human traders with numerous advantages, such as the capability to conduct genuine high-frequency trading (HFT), which capitalizes on price discrepancies and market anomalies, and to analyze a massive data set from multiple sources in a fraction of a second. The main goal of this research is to examine the role that AI plays in the financial markets, with an emphasis on how it affects trading, portfolio management, and price prediction. In this study, quantitative research methodology was utilised. Primary and secondary sources of data were used in the investigation. An online questionnaire was used to collect the primary data, and finance databases, pertinent industry bulletins, and already published literature were used to collect the secondary data. It was found that there is an increasing incorporation of AI and machine learning technologies into financial institutions. Many of the participants revealed that these technologies are used moderately to significantly in their organizations. The most prominent AI and machine learning applications are “algorithmic trading, risk management, fraud detection, credit scoring, and customer service”.

Status and Development of Agricultural Public-Private Partnership Program Implementation in China

<p>As the initiator of the Belt and Road Initiative, the Chinese Government’s goal in agriculture is to promote the sustainable development of agriculture throughout China and the world. One of the feasible ways to realize this goal is to adopt the Public-Private Partnership (PPP) model. This study aims to analyze the current status of agricultural PPP projects in China and their impacts. This study utilized the Ministry of Finance database to collect 2014 to 2022 data on agricultural PPP projects in China. The collected data were organized and analyzed to analyze the current situation and return mechanism of Chinese agricultural PPP projects. The results show that China’s agricultural PPP projects are less attractive than other sectors, government and social-private sector cooperation is less sustainable, and laws and regulations and risk assessment are not well developed. Therefore, this study proposes to promote the development of agricultural PPP projects by standardizing the law, improving the return mechanism, and strengthening the risk assessment. Thus, it further promotes the sustainable development of agriculture and plays a certain positive role.</p>

Green Financing for Sustainable Development in Infrastructure Projects in Kenya

Transitioning into a decarbonized economy requires an unprecedented level of new capital investment, particularly in the form of green finance. Market and regulatory trends indicate that there is an increased interest in green and sustainable finance among investors and policymakers. However, capital mobilization for green investments has been constrained by microeconomic obstacles including maturity mismatches between long-term green investments; the typically short-term time horizons of investors and disintegrated financial and environmental policy approaches. It’s against this backdrop that the study intended to assess the green finance trends, green finance instruments and the challenges on green finance adoption.The study adopted desk review also known as Meta-analysis method to extract information concerning green finance trends, instruments and adoption challenges. The study established that to achieve sustainable development goals (SDGs), its necessary to open-up green projects and scale up the financing of investments that provide environmental benefits through innovative financial instruments and new policies such as green bonds, green banks, carbon market instruments, fiscal policy, green central banking, financial technologies and community-based green funds. However, Financial institutions show more interest in fossil fuel projects than green projects because of the low returns and risks associated with green investment compared to brown investment. To reduce the risk of green investment and increase the rate of return to the investors, the creation of green credit guarantee schemes and tax return on revenue generated from the green energy spillover effect is necessary. In conclusion green finance market is well structured in developed economies unlike developing economies due to underdeveloped capital markets, regulatory gaps and unstandardized green taxonomy.Thus the study recommends the development of green finance database and incorporation of green agenda in public policy institutions’ mandates and procurement;Standardization and information disclosure regarding Green investment risks, green taxonomy and commoditization of environmental factors into tradable assets; Raising awareness; Offering tax incentive on green projects; Developing Carbon Capital Markets; Stock Trading of Green finance products; Strengthen the social responsibilities of investors and Technology adoption.

Stock Market Price Prediction Using Machine Learning Models

Stock forecasting has historically been a popular and lucrative field of study. It has been demonstrated that machine learning applications improve accuracy and return in the area of finance forecasting and prediction. This study chose data from the Yahoo Finance database that represented Apple's (AAPL) close price for research. This study categorized articles using a series of machine learning models, encompassing Linear Regression, Random Forest and so on. This paper also examines each article's dataset, variable, model, and findings. The survey in use showcases the findings using the most popular performance metrics. Recent models that combine LSTM with other techniques, For instance, RF has received a lot of study. Deep learning techniques like reinforcement learning and others produced excellent results. In conclusion, the use of deep learning-based techniques for financial modeling has become growing in popularity over the past few years.

Greenfield project finance loan maturity and the role of multilateral development banks in developing countries

This paper is intended to provide empirical evidence for the financial additionality of multilateral development banks (MDBs) in private sector infrastructure projects. To validate MDBs’ financial additionality, this study uses IJGlobal’s project finance database to examine whether the loan tenor of MDBs’ project finance loans is significantly longer than the average loan tenor extended by commercial banks, using ordinary least squares (OLS) and Poisson Pseudo Maximum Likelihood (PPML) estimations. The result of the empirical analysis shows that project finance loans involving MDBs have significantly longer loan maturity than average loans in lower-middle-income and upper-middle-income countries, while projects in low-income countries and Sub-Saharan Africa do not have such a tendency. Furthermore, in host countries where government effectiveness is underdeveloped, the coefficient of project finance loans provided by MDBs is negative with statistical significance. As a policy implication, these findings indicate that for MDBs to ascertain financial additionality in countries where government effectiveness is weak, additional measures such as capacity building of the host government and additional financial intervention are needed.

PENGETAHUAN, KUALITAS HIDUP DAN BIAYA SAKIT PASIEN DENGUE DI RS PKU MUHAMMADIYAH GAMPING

The incidence of dengue virus infection in the D.I. Yogyakarta reached 3,618 cases in 2020. Based on its clinical manifestations, dengue virus infection is divided into Dengue Fever (DF), Dengue Haemorrhagic Fever (DHF), and Dengue Shock Syndrome (DSS). This study aims to identify the level of knowledge, quality of life, and costs of dengue patients at PKU Muhammadiyah Gamping Hospital from March 2021 to October 2021. This study used a cross-sectional design. The measurement of the patient's knowledge level used a questionnaire knowledge of dengue, while the quality of life was assessed using EQ-5D-5L for adult patients and EQ-5D-Y for pediatric patients. The cost of illness data from the hospital finance database. This study involved 31 respondents with the characteristics aged 16-40 years (54.84%), male (87.1%), using BPJS insurance (80.65%), and an average length of stay of 4 days (51.61%). The patient's level of knowledge about dengue, knowledge of dengue prevention, and dengue prevention behavior reached 74.20% (sufficient), 74.20% (sufficient), and 77.42% (sufficient) respectively. The quality of life of dengue patients reached 100% and 85.2% in DF patients, while the DHF patients felt a few anxious/depressed (sad). The average cost of illness in DF patients was Rp. 2,796,386 and Rp. 3,378,537 in DHF patients.

Impact of the Belt and Road Initiative on China's overseas renewable energy development finance: Effects and features

This study investigates the features and effects of the Belt and Road Initiative (BRI) on China's policy banks' overseas renewable energy development finance in BRI countries. To this end, this study uses the financing for energy projects' data in China's Global Energy Finance database and performs regression analysis using Differences-in-differences (DID) and Difference-in-differences-in-differences (DDD) methods. The main findings are as follows. First, compared with non-renewable energy finance, the BRI can increase the number of renewable energy projects financing by China's policy banks in BRI countries; however, this positive effect is mainly reflected in hydropower projects and Southeast Asia. Second, from the perspective of the providers' features, the BRI has a more significant role in promoting the financing of renewable energy by China Export and Import Bank. In terms of recipients' features, China's development finance is mainly directed to high credit risk, low-income countries and regions that traditional donors have disregarded; thus, the policy banks tend to cooperate with government recipients. Third, the BRI has facilitated China's policy banks' renewable energy finance in high carbon intensity countries, breaking the carbon lock-in effect and strengthening renewable energy financing through the establishment of energy partnerships, reflecting the features of joint contribution and cooperation. Our findings alleviate some scholars' concerns about the environmental effects of the BRI to a certain degree and show that proactive policies of investing countries can guide development finance to contribute to the global energy transition and climate goals.

Financing for tuberculosis prevention, diagnosis and treatment services in the Western Pacific Region in 2005-2020.

This paper provides an overview of financing for tuberculosis (TB) prevention, diagnostic and treatment services in the World Health Organization (WHO) Western Pacific Region during 2005-2020. This analysis uses the WHO global TB finance database to describe TB funding during 2005-2020 in 18 low- and middle-income countries (LMICs) in the Western Pacific Region, with additional country-level data and analysis for seven priority countries: Cambodia, China, the Lao People's Democratic Republic, Mongolia, Papua New Guinea, the Philippines and Viet Nam. Funding for the provision of TB prevention, diagnostic and treatment services in the 18 LMICs tripled fromUS$ 358 million in 2005 to US$ 1061 million in 2020, driven largely by increases in domestic funding, which rose from US$ 325 million to US$ 939 million over the same period. In the seven priority countries, TB investments also tripled, from US$ 340 million in 2005 to US$ 1020 million in 2020. China alone accounted for much of this growth, increasing its financing for TB programmes and services fivefold, from US$ 160 million to US$ 784 million. The latest country forecasts estimate that US$ 3.8 billion will be required to fight TB in the seven priority countries by 2025, which means that unless additional funding is mobilized, the funding gap will increase from US$ 326 million in 2020 to US$ 830 million by 2025. Increases in domestic funding over the past 15 years reflect a firm political commitment to ending TB. However, current funding levels do not meet the required needs to finance the national TB strategic plans in the priority countries. An urgent step-up of public financing efforts is required to reduce the burden of TB in the Western Pacific Region.

The Bottom Line: Trauma Center Viability During COVID-19

IntroductionThe COVID-19 pandemic was a potential threat to the viability of trauma centers and health systems in general. We sought to answer the question of how COVID-19 was associated with patient characteristics as well as trauma center volume, finances, and viability. MethodsWe reviewed 6375 patients admitted to our verified Level 1 trauma center during two time periods: pre-COVID (February 2019-February 2020) and COVID (March 2020-March 2021). Three thousand ninety-nine patients were admitted pre-COVID and 3276 were admitted during COVID. Data including case-mix index (CMI), total contribution margin, insurance status, age, race, gender, ethnicity, and injury mechanism were collected from the trauma registry and finance databases and analyzed. A P < 0.05 was considered significant. ResultsTrauma admissions decreased initially during COVID but returned to and ultimately surpassed admission trends pre-COVID. Trauma revenue and patient acuity increased significantly along with a decrease in the number of underinsured patients during COVID. When evaluating all service lines, the trauma center was the highest contributor to overall hospital revenue. ConclusionsDespite a decrease in admissions for other service lines and a pause in elective surgeries during the pandemic, the trauma center remained unaffected. In addition, trauma was the most significant contributor to the bottom line of the health system. These findings underscore the need to maintain and even increase trauma center resources and staffing to ensure that optimal care is provided to critically ill and injured patients.

Machine Learning Approach for Credit Card fraud Detection

Abstract: Finance fraud is a growing problem with far consequences in the financial industry and while many techniques have been discovered. Data analysis is to be applied to finance databases to automate analysis of huge volumes of complex data. Data analysis has also played a salient role in the detection of credit card fraud in online transactions. Fraud detection in credit card is a data analysis problem, It becomes challenging due to two major reasons–first, the profiles of normal and fraudulent behaviors change frequently and secondly due to reason that credit card fraud data sets are highly skewed. This project propose investigation and to check the performance of various algorithms on highly skewed credit card fraud data. Dataset of credit card transactions is sourced from European cardholders containing 284,786 transactions. These techniques are applied on the raw and preprocessed data. The performance of the techniques is evaluated based on accuracy, sensitivity, and specificity, precision.

Finding the right partners? Examining inequalities in the global investment landscape of hydropower

Clean and affordable energy is crucial to achieve a sustainable future. Despite being controversial, hydropower remains the predominant low-cost and reliable source of energy at global level, as it stabilizes the provision of electricity and it bears the power peaks without losing efficiency. However, hydropower requires huge upfront investments and patient functional capital. Under the Paris Agreement, countries committed to direct financial capital flows towards a low-emission pathway in order to enable the transition. Furthermore, private capital strongly engaged with a transition towards a climate-smart economy. The aim of this work is to study the investment system behind hydropower, investors’ behaviour and the optimal allocation of finance to favour the deployment of capital flows. We use Bloomberg Energy Finance database to track public–private investments over the past century (1903–2020). We use network models to represent the hydropower project financing landscape as a network of co-investments. We find that investors are highly localized, with continental players mostly interacting with counterparts in the same area of the world. Powerful exceptions are international organisations and multilateral banks which coinvest across the globe. They also tend to support low-income and fragile countries, meeting their mandate of sustainable development champions. Multilateral banks and international organisations are the most critical actors in enabling public–private co-investments; they activate partnerships with a wider diversity of investors within the network creating more opportunities for blended finance tools. Our results offer a novel perspective on finance for the energy transition: it challenges the idea that more capital invested is better and calls for a more efficient allocation of the available resources.

Effects of Mortgage Interest Rate on Real Estate Investment in Kenya

As an investment and consumer good, real estate is significant. Like many developing countries, Kenya has struggled to give its citizens access to decent housing that is also affordable. More people are in need of housing due to urbanization, fast population growth, and rural-to-urban migration. Housing supply is less than demand as a result of several of macroeconomic and financial issues that affect real estate investment and, consequently, housing. This study looked into the impact of mortgage interest rates on real estate investment. The study, which covered the 11-year period from 2010 to 2020, used a causal research design and regression analytic research methods based on the Vector Error Correction Model. Data on real estate investments in Kenya The Kenya National Bureau of Statistics (KNBS) and Cytonn quarterly investments reports were obtained from the Central Bank of Kenya. The Ministry of Finance's database on national budgets (KNBS) provided information on mortgage interest rates, A pre-estimation test was run to verify the outcomes. The variables were stationary on the first difference. The VIF test result of 1.62 indicated that there was no multi-collinearity. The 1.9122 Durbin test value suggested that there was no serial correlation. Pairwise Correlation analysis showed a moderate correlation between mortgage interest rate on real estate investment (0.578). The report suggests that in order to incentivize real estate investment, the government should offer mortgage loans at reasonable rates, control property tax rates, and promote public-private partnerships in infrastructure development.

Egg production: conventional or cage-free?

Research methodology This case was primarily researched using academic research papers, industry reports (Egg Industry Center and others), and finance databases including Standard and Poor’s Capital IQ. Regarding the cost and investment budgets, the case relies mainly on an experiment conducted by the Coalition for Sustainable Egg Supply, updated by the authors of this case. Case overview/synopsis Eggs produced by cage-free birds, while more expensive than conventionally produced eggs, are gaining in popularity among consumers who want only eggs that are produced more humanely. A number of major distributors, including Whole Foods, McDonalds and Starbucks have pledged to sell only cage-free produced eggs by 2025. Several states including California, Oregon and Michigan have passed laws limiting conventional egg production. The case provides costs and industry information and needed to project free cash flows and risk-adjusted opportunity cost of capital and perform break-even capital budgeting analysis of the two egg production alternatives. Complexity academic level This case is appropriate for graduate corporate finance courses. It is particularly appropriate for agribusiness finance courses. A preliminary exercise was used during the fall 2018 in a land grant university, just after the “Prevention of Cruelty to Farm Animals Act,” also known as Proposition 12, was passed in California in favor of cage-free egg production. The exercise was revised and used in the fall 2019 in the same class. This extended version of the case, was classroom tested in the fall 2020 in an agribusiness finance graduate class, with agricultural economics and business students enrolled.

Financial sector transparency and bank interest margins: do quality of political and financial regulatory institutions matter?

Purpose This study aims to examine the effect of private (PRST) and public (PUST) sector-led financial sector transparencies on bank interest margins (BIM) termed as social cost of financial intermediation in different institutional quality setups. Design/methodology/approach This study uses a two-step dynamic generalized method of moments panel data and bootstrapped quantile models with 91 economies between 2004 and 2016. Data is sourced from World Development Indicator and Global Development Finance databases. Findings The results show that under strong and weak political and financial regulatory institutional setups, the reducing effect of PRST on BIM are observed and reported while the full sample reports no significant nexus between PRST and PUST on BIM. Furthermore, under political institutional quality sample, economies with strong corruption control and regulatory quality are able to reinforce the dampening effect of PRST on BIM while under the same political institutional quality sample, economies with weak rule of law are able to heighten the reducing effect of PRST on BIM. Moreover, under financial regulator institutional quality sample, economies with strong overall weighted and unweighted, chief executive officer and policy dependent central banks are able to intensify the diminishing effect of PRST on BIM while under the same financial regulator institutional quality sample, economies with weak limits on lending are able to amplify the reducing effect of PRST on BIM. However, PUST is reported to propel lower levels BIM in the bootstrap models, especially in strong institutional economies. Practical implications These findings imply that policymakers may rely on PRST to reduce BIM, especially under financial regulatory institutional quality. Additionally, economies must be careful on their reliance on PRST because the effectiveness of PRST to tame high BIM is dependent on the strength of political and financial regulatory institutions. Originality/value To the best of the authors’ knowledge, this study presents first time international evidence on the effect of private and public sector-led financial transparency on BIM in strong and weak political and financial regulatory institution economies.

RELAÇÕES ECONÔMICAS ENTRE AMÉRICA LATINA E CARIBE E CHINA E SEUS IMPACTOS NA INTEGRAÇÃO REGIONAL (2001-2016)

The article provides an analysis of the Chinese presence and influence in Latin America and the Caribbean (LAC), and how it affects regional integration processes that exist in the region. We start from a brief qualitative analysis, stressing the role of foreign influence on regional integration, highlighting how the Chinese expansion plan affects the case of Latin American integration. Then, a critical quantitative analysis of the transactions between LAC-China is carried out, analyzing imports/exports, preferential trade agreements (PTA), and foreign direct investment (FDI). The data comprises the 2001-2016 period and were retrieved from the United Nations Commodity Trade Statistics Database (UN Comtrade), World Integrated Trade Solutions (WITS), China-Latin America Finance Database, and China Global Investment Tracker. In conclusion, we highlight the growing Chinese influence in the Latin America region, emphasizing that the bilateral narrowing of Latin American countries with China has an indirect and adverse impact on regional integration.

The Post–Great Recession Geographies of U.S. Municipal Borrowing and Indebtedness

Borrowing from capital markets has a long history in U.S. urban government. With federal authorities withdrawing fiscal support since the 1980s, U.S. cities have become more entrepreneurial and increased their reliance on borrowing. Some now claim that this reliance has grown since the Great Recession. Despite the significance of borrowing to U.S. urban governments, municipal indebtedness remains a relatively understudied topic within geography. This article examines post–Great Recession indebtedness changes (2006–2016) in the general funds of U.S. municipalities. We show that general fund indebtedness has not generally increased since the Great Recession, although a complex landscape of divergent borrowing and indebtedness is evident across cities with different populations. The article uses the Government Finance Database to collect and analyze U.S. Census Bureau data on municipal debt and budget health. We conclude by discussing the need to develop existing theories of postrecession urban governance to examine emerging debt and budgetary challenges across U.S. municipalities.

Data quality problems troubling business and financial researchers: A literature review and synthetic analysis

The data quality of commercial business and financial databases greatly affects research quality and reliability. The presence of data quality problems can not only distort research results, destroy a research effort but also seriously damage management decisions based upon such research. Although library literature rarely discusses data quality problems, business literature reports a wide range of data quality issues, many of which have been systematically tested with statistical methods. This article reviews a collection of the business literature that provides a critical analysis on the data quality of the most frequently used business and finance databases including the Center for Research in Security Prices (CRSP), Compustat, S&P Capital IQ, I/B/E/S, Datastream, Worldscope, Securities Data Company (SDC) Platinum, and Bureau van Dijk (BvD) Orbis and identifies 11 categories of common data quality problems, including missing values, data errors, discrepancies, biases, inconsistencies, static header data, standardization, changes in historic data, lack of transparency, reporting time issues and misuse of data. Finally, the article provides some practical advice for librarians to facilitate their scholarly communications with researchers on data quality problems.

548 The Economics of Burn Injuries Among Children Aged 0–4 Years

Abstract Introduction Children under the age of five years are particularly vulnerable to scalds and contact burns and have the highest rate of hospitalization and mortality from burns. Studies of costs associated with pediatric burns have included a limited number of patients and focused on inpatient and complication costs, limiting our understanding of the full economic burden of pediatric burns, including costs incurred through outpatient care and caregivers’ productivity loss. This study aimed to develop a societal costing model for burn injuries among children aged 0 to 4 years. Methods Children aged 0 to 4 years identified through the local Burn Registry with a burn injury between January 1, 2014 and March 15, 2018 were included in this study. Patients with inhalation injury, electrical, chemical and friction burns were excluded. An incidence-based cost-of-illness analysis with a human capital approach was used to quantify the cost of partial and full-thickness burns according to the percentage of total body surface area (%TBSA) involved. The cost of a burn injury was assessed from a societal perspective through the following cost categories: emergency department visits, inpatient, outpatient dressing changes, outpatient burnbaths, day surgeries, clinic visits and caregiver productivity losses. A list of resource items for each category were extracted from patient chart review, the local Burn Registry, and the local Hospital Finance Database, and assigned unit prices. Costs were discounted to a present value in 2017 dollars at 1.5% per annum. Results Burn injuries were observed for 342 children, of which 249 (73%) had their burn severity classified (%TBSA and partial/full thickness) and were included in this study. Burn severity categories (1–5%, 6–10%, 11–20%, and &amp;gt;20%) were developed based on the differential distribution of the costs allocated to each burn incident. The majority of children (60.8%) suffered from a 1–5% burn. A 1–5%, 6–10%, 11–20%, and &amp;gt;20% burn respectively cost an average of $2,229, $8,653, $13,663, and $98,634 to society. Costs incurred by the 1–5% burns were related mostly to emergency department visits and dressing changes, while costs incurred by the &amp;gt;20% were related mostly to inpatient and clinic visits (garments) costs. Conclusions This costing approach raises awareness about the important, yet preventable economic burden that pediatric burn injuries place on society. Applicability of Research to Practice This evidence may persuade policymakers and clinicians to invest in pediatric burns prevention programs in order to decrease pediatric burns costs allowing for the allocation of funds towards other clinical initiatives. This costing model may also facilitate cost-effectiveness analyses of burn prevention programs in the coming years.

The lure of Chinese state capitalism in Latin America and the Caribbean

ABSTRACT This paper examines the attractiveness of contemporary China's state-directed economic system beyond China's borders. It considers the political and economic affinities between China and Latin America and the Caribbean (LAC) in order to understand the allure of Chinese state capitalism in the region. Employing six broad governance variables, this project develops an empirically grounded tool – the Neoliberal–Dirigiste Continuum – to estimate the allure of Chinese state capitalism in 25 countries within the region. Drawing on data from the Varieties of Democracy database, the Database of Political Institutions, the United Nations Comtrade database, the Academic Network of Latin America and the Caribbean on China Monitor (RED ALC-China), and the Inter-American Dialogue's China–Latin America Finance Database, this paper examines the relationship between LAC countries’ political and economic organization and trade, Chinese outbound foreign direct investment, and the issuance of Chinese policy bank loans to LAC countries from 2005 to 2017. While the allure of Chinese state capitalism and its spread across the Global South over the last three decades is not specific to any one world region, examining the China–LAC political economic relationship in this context is useful because it represents a blending of the global and the contextual.

Blockchain innovative technology as a communication basis for the digital economy formation

The innovative blockchain technology is still in its infancy, and some researchers still treat it with a degree of distrust. However, among the features of its application and its inherent features, one can identify a severe potential that eliminates the current level of such distrust. Note that the “blockchain” concept has been actively discussed along with the cryptocurrency growing popularity. There is a strong belief that this technology can be a real breakthrough in economics, finance, and secure databases. The blockchain consists of a chain of blocks being stored on different computers containing a timestamp and a link to the previous block.