Financial Firms Research Articles

Economic environment uncertainty and financialization of real estate firms

This paper investigates the impact of economic environment uncertainty on real estate firms' financialization and explores the underlying mechanisms. This paper utilizes data from listed real estate firms from 2011 to 2021, focusing on the rationale for firms' financialization. In contrast to prior literature, this study employs the macro-level economic uncertainty index and the micro-level uncertainty perception measures to gauge economic environment uncertainty. The findings indicate that an increase in economic environment uncertainty leads to a greater inclination of firms to engage in financialization, driven by the "precautionary savings" motivation. Furthermore, this effect is primarily driven by the firm-level perception of uncertainty in the external environment. Mechanisms tests demonstrate that when there is uncertainty in the economic environment, corporations are more likely to engage in financialization, primarily due to decreased CEO overconfidence and reduced corporate risk-taking. Moreover, the level of financing constraints and executives with financial expertise contribute to the heterogeneous effects of uncertain economic conditions on real estate firms' financialization. Firms with high financing constraints and financial background executives are more likely to engage in and enlarge investments in financial assets, while firms without financial background executives are not. Furthermore, there is no notable correlation between the level of financialization of state-owned enterprises and policy fluctuations in the economic environment. The findings provide valuable insights for businesses to explore alternative paths for growth, raising awareness among government regulators about the risks associated with financialization.

Cross-sectional financial conditions, business cycles and the lending channel

I document business cycle properties of the cross-sectional distributions of U.S. stock returns and credit spreads. The skewness of returns of financial firms (SRF) best predicts economic activity, while being a barometer for the lending channel—credit supply shifts beyond what is explained by borrowers’ conditions. SRF also predict firm-level investment beyond firms’ balance sheets. Using a structural model, I estimate that while SRF is highly cyclical, shocks to the cross-sectional skewness of financial firms’ asset quality help explain GDP growth in historical episodes. These results point to the cross-section of financial firms playing a prominent role in business cycles.

CSR in the banking industry: A longitudinal analysis of the impact on financial performance and risk-taking

Building on the stakeholder influence capacity theory we propose a non-linear relationship between CSR investments and financial performance and between CSR investments and risk-taking behavior in financial firms. We study the impact of ESG scores on both the financial performance and risk-propensity of European banks using panel data from 2005 to 2022. Given the role of Swiss banks as frontrunners regarding the implementation of CSR-related regulations in the financial industry, we also shed light on the Swiss case. Controlling for bank and time fixed effects we confirm a U-shaped relationship between ESG and financial performance, and an inverted U-shaped relationship between ESG and risk for Swiss banks. Remarkably, we find no relationship between CSR initiatives and financial performance for European banks and find a direct negative effect of CSR on risk density. These results indicate the need to consider institutional differences in the CSR debate. Moreover, we show that promoting ESG initiatives in the financial industry might lead to adverse effects (i.e. lower financial performance and higher risk) if banks do not commit sufficiently to those CSR investments.

Inventor CEOs and financing of innovation: Evidence from IPOs

We examine the role of inventor CEOs—those with personal hands-on experience of innovation—in the financing of innovation. Using a sample of technology initial public offerings (IPOs) in the US, we document that inventor CEOs are associated with lower underpricing at the time of the IPOs. Inventor CEOs also appear more capable of taking their firms public during “cold” IPO market periods when financing conditions are more difficult. Analyses based on regulatory changes and a founder-only sample suggest that these relationships are causal. Further, inventor-led firms appear to invest the IPO proceeds more productively, as reflected in the firms’ superior innovation outcomes in the post-IPO period. The stock market fails to fully understand these relationships, and IPOs led by inventor CEOs produce large positive abnormal returns in the three years following the offering. Our findings are consistent with inventor CEOs facilitating innovation financing for startup firms by effectively reducing information asymmetry and valuation uncertainty of firm's innovation capital for outside investors.

An online fuzzy fraud detection framework for credit card transactions

Credit card transaction fraud is one of the challenging security concerns for financial firms globally. The continuously changing environment of fraud characteristics and the class imbalance and complete separation issues in fraud data create difficulties in accurately and efficiently predicting fraudulent transactions and implementing fraud detection systems in real-time. The study aims to develop a new real-time fraud detection framework that can efficiently be implemented online and address the issues caused by non-stationary changes in transaction and fraud characteristics, class imbalance, and complete separation. We propose a new approach to handle the impact of non-stationary changes in fraud transaction patterns. It enables efficiency in model training, given the sheer size of datasets. By implementing a robust fuzzy logistic regression model against class imbalance and separation problems, we address the challenge of having a very low rate of fraudulent transactions in the dataset and having separation issues due to specific characteristics of transactions. The analysis of the performance versus efficiency nexus of the proposed methodology reveals that the proposed framework shows strong performance results with specificity and sensitivity greater than 0.90 and Matthew’s correlation coefficient greater than 0.80 even on small sample sizes and produces highly accurate results in identifying fraudulent and non-fraudulent transactions with an accuracy greater than 0.99. Benchmarking with machine learning and other fraud detection approaches reveals that the proposed framework provides better detection performance while maintaining a higher rate of identifying non-fraudulent transactions than the alternative approaches. Improved classification performance leads to detecting fraudulent transactions with higher precision while avoiding misclassifying legitimate transfers, resulting in lower financial losses and improved customer satisfaction.

Factors Influencing the Use of Account Information Systems and its Impact on Small and Medium Enterprises Performance: Systematic Literature Review

The viability of Small and Medium Enterprises is heavily reliant on effectively managed firm finance management. Utilizing technology and information through an Accounting Information System is beneficial for businesses as it aids in the management of financial transactions, financial reporting, and financial decision-making. This article employs the Systematic Literature Review research methodology, utilizing several papers indexed by Scopus from 2015 to 2024. Researchers investigate the characteristics that facilitate the adoption of Accounting Information Systems in Small and Medium Enterprises (SMEs) and their influence on corporate performance to ensure the long-term viability of SMEs in the face of business challenges and advancements. An Accounting Information System is crucial for assessing the progress of SME businesses and obtaining assistance from internal and external stakeholders. This is particularly important given the significant influence that Small and Medium Enterprises have on the national economy

So different and yet so alike: A comparative analysis of firms' connectedness in the stock and corporate bond markets

AbstractWe study firms' return and volatility connectedness in the stock and corporate bond markets. Our approach to capturing firm‐specific return and volatility time series in the corporate bond market is based on a repeat‐sales index at the firm level. Measuring the pairwise connectedness of firms, we show that the two markets share similar dynamics in the connectedness of their firms. Firms tend to cluster within their own sectors and ties between firms in the corporate bond market are proportionally weaker. Financial firms play a critical role in the propagation of shocks, but this role differs markedly in the two markets.

A regression model for determinants of foreign ownership ratio of listed financial firms: Evidence from the Vietnam stock exchange

Foreign ownership in financial enterprises is a crucial characteristic that impacts the activities of these enterprises. Therefore, the topic of foreign ownership ratio in these enterprises and factors that affect this ratio has drawn the attention of many researchers both domestically and internationally. Based on previous research findings along with qualitative research methods, this study provides an overview of theoretical foundations and practical considerations in order to propose a model to investigate the factors influencing the foreign ownership ratio in financial enterprises. The novelty of this research lies in its focus on listed financial enterprises in the Vietnam stock market, specifically in the context of significant fluctuation due to the impact of the COVID-19 pandemic. The proposed model serves as a premise and reference for future studies aiming to evaluate the influence of various factors on the foreign ownership ratio in listed financial enterprises on the Vietnam stock exchange.

Corporate Social Responsibility and Firm Financial Performance of Public Listed Company in Malaysia

Corporate Social Responsibility and Firm Financial Performance of Public Listed Company in Malaysia

A theory of debt maturity and innovation

The financing of innovative firms must balance two competing goals. First, the entrepreneur must be adequately protected from failure to encourage innovation. However, if the attempt to innovate fails, the entrepreneur's firm should be liquidated and its assets redeployed elsewhere. Meeting these two goals is inherently challenging when contracts are incomplete and shaped by ex-post renegotiation. I investigate how firms can choose the maturity of their debt to motivate innovation. The theory highlights a novel interaction between low-powered incentives, renegotiation, and debt maturity.

Leveraging intellectual property: The value of harmonized enforcement regimes

This paper examines the role of intellectual property (IP) law as a determinant for external debt financing of innovative firms. For identification, we exploit exogenous variation in patent right enforcement arising from the 2004 EU Enforcement Directive. This major policy reform strengthened IP rights and, thus, raised patent owners' asset position. We find that patenting firms significantly increase their use of debt and benefit from lower interest rates in response to the amendment, especially if they own valuable patent portfolios. These effects are most pronounced for relatively small and financially constrained firms, emphasizing the importance of the legal framework in fostering debt financing activities of innovation-oriented firms.

Unveiling the Determinants of Islamic Mobile Banking Adoption: Evidence from Pakistan

Mobile Banking is a cutting-edge technological innovation in the banking industry that has greatly increased banking efficiency and boosted the overall quality of life for individuals. Financial firms are increasingly attracted to systems that enhance the quality of client service. This study aims to further our understanding of the adoption of Islamic mobile banking by utilizing the Technological Acceptance Model (TAM). This study presents a research approach that utilizes the Technology Acceptance Model (TAM) to investigate the factors that influence consumers' adoption of Islamic mobile banking. Consequently, it offers insights into the crucial factors that banking professionals must take into account to promote the integration of mobile technology in Islamic banking services. The data for this study were collected by a questionnaire survey and then analyzed using SPSS and Smart PLS 3.0, utilizing structural equation modeling (SEM). The study sample comprised 350 individuals who were customers of various branches of five Islamic banks, namely Meezan Bank Limited, Dubai Islamic Bank, Al-Baraka Bank Limited, MCB Islamic Bank Limited, and Bank AlFalah Islamic. After conducting data screening procedures, a final sample of 300 respondents was selected for analysis. The findings indicate that characteristics such as Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) have a positive influence on the Intention to Use (INT), supporting the notion that PU has a positive impact on PEOU according to the Technology Acceptance Model (TAM). The research findings suggest that customers' adoption of Islamic banking is positively influenced by their intentions to utilize it, and these intentions are further enhanced by social influence.

Application for Machine Learning Methods in Financial Risk Management

Financial risk management has significant importance and implications for individuals, businesses, investors, and even the whole nation. As the financial markets and institutes grow complex so does the risk associated with financial management. The spectrum of financial risks includes market risk, liquidity risk, credit risk, and a range of others. With a multitude of portfolios and sophisticated products, financial firms require apt tools that can accurately measure the risk, returns, and exposure. The growing complexity has also made statistical and simulation tools ineffective and there is a growing emergence of machine learning. Machine learning is a sub-category of artificial intelligence that uses algorithms. These algorithms analyze data and then learn from it so that a decision based on a certain experience or criteria can be made. Machine language tools provide data protection as the information is only accessible to the key decision-makers. Deep learning is modeled like a human brain and therefore it operates using multiple layers of artificial networks and can process and use a very vast amount of data.

The UK financial firms’ textual risk disclosure and market liquidity

The informativeness of textual risk disclosure (TRD) of financial firms is unexplored in the extant literature. Employing a sample of UK FTSE all-share financial firms, this paper fills this gap in the literature by providing the first empirical evidence on the relationship between TRD and market liquidity. Consistent with the convergence argument for TRD, we find that TRD decreases the financial firms’ market liquidity. However, consistent with the divergence argument for TRD, our further analysis shows that TRD increases the market liquidity of large financial firms. Overall, our results suggest that financial firms’ TRD is informative to market participants. In addition to the practical and policy implications of our results, this paper opens avenues for future research to use our textual method to measure the determinants and use risk information of financial firms in different contexts.

Tracking the sun: exposing India’s solar dispossessions

ABSTRACT Utility-scale solar development in India has dispossessed peasants of land and livelihoods. Smallholders alienated from land have not been equitably remunerated, rehabilitated, nor offered employment at new solar parks. Yet it remains unclear which modalities of dispossession are used across solar sites. Drawing on mixed methods fieldwork from the Gujarat Solar Park and the Kurnool Solar Park, this study advances research on the processes of land dispossession by examining the following research questions: 1) Which constellation of actors and institutions facilitate land dispossession for solar development in India; 2) Through which modalities do these actors and institutions conduct solar-induced land dispossessions? We find actors and institutions behind solar park development in India function as agents of dispossession. Wielding coercive inscription devices that include land acquisition laws, wasteland categorizations and iterative titling, they seize peasant land in service of private and financial firms to underwrite the rollout of large-scale solar interventions.

Does XBRL adoption increase financial information transparency in digital disclosure environment? Insights from emerging markets

The eXtensible Business Reporting Language (XBRL) is one of the global-level business reporting standards that accommodates all firms to report financial affairs in a convenient manner. The main objective of this study is to explain the impact of XBRL adoption on the transparency of financial information disclosure in Jordanian financial companies. The current study used a sample of 124 respondents including accounting managers, auditors, and financial managers with a background in XBRL who are working in Jordanian financial firms. The findings confirmed that the adoption of XBRL in Jordanian financial firms increases financial information transparency in the digital disclosure environment which leads to more relevant, reliable, and transparent financial statements disclosure. One main implication the current study heightened is the importance of turning to the implementation of the XBRL will support the process of decision making which will support and enhance both the performance and decision-making process. Lastly, this research effort is the first of its kind that examined the impact of XBRL on the transparency of financial information from the financial firms' perspective in Jordan as a developing country.

Debt Sustainability Assessment in the Biogas Sector: Application of Interest Coverage Ratios in a Sample of Agricultural Firms in Italy

The biogas sector in Europe and Italy is attracting growing investment, combining agricultural activity, the circular economy, and renewable energy production. Firms in the sector widely use debt capital and, for this reason, there is a need to evaluate the structure of investments, financing, and debt service capacity calculated by applying interest coverage ratios (ICRs). ICRs are widely used by banks in granting loans, and calculation of ICRs allows managers and policy makers to correctly evaluate firms’ performance in the sector. In this research, based on a sample of 160 observations, the structure of investments and sources of financing of firms in the biogas sector, operating in northern Italy, are analyzed. ICRs are calculated with different approaches to establish which ICRs provide the most reliable results in the application. The research analyzes the correlations and highlights significant differences between ICRs. The research highlights some important findings: (a) the NWC is negative in 109 out of 160 observations and, therefore, constitutes a source of financing in the majority of observations; (b) ICRs based on EBITDA and CF are above the threshold value of “1” in 143 and 145 observations, respectively, while ICRs based on EBIT, OCF, and UFCF are above the threshold value of “1” in 132, 133, and 122 observations, respectively. The research allows the conclusion that the ICRs based on EBITDA and CF tend to overestimate results; ICRs based on EBIT, OCF and UFCF are preferable, and can therefore be applied by managers, banks, and policy makers and be used as debt covenants. For the calculation of the repayment of the NFP, the research has highlighted that ICRs in which the cost of the debt is deducted from the numerator are preferable. The research can thus be usefully applied and expanded to other territories, or by considering a larger sample with the aim of inferring conclusions of general validity.

Reducing carbon emissions at the expense of firm physical capital investments and growing financialization? Impacts of carbon trading policy from a regression discontinuity design

This study examines the effects of China's carbon trading policy on firm emissions and explores its impact mechanisms through financial and physical asset investments. The empirical analysis utilizes a fuzzy regression discontinuity design based on a sample of 427 industrial firms in China between 2014 and 2019. The results indicate that China's carbon trading policy incentivized firms to increase their financial investments while simultaneously discouraging physical capital investments. These shifts in investment patterns helped firms achieve their emission reduction targets. The study reveals that carbon trading policy in China has contributed to the financialization of firms, resulting in the erosion of firm assets and a decline in their overall competitiveness. Based on these findings, some policy recommendations are put forward.

Tax Sheltering and Corporate Investment Expenditure of Listed Financial Firms in Nigeria

Tax Sheltering and Corporate Investment Expenditure of Listed Financial Firms in Nigeria

“Impact of ESG disclosure on firm performance and cost of debt: Empirical evidence from India”

Despite several research evaluating the connection between sustainability and the bottom line of firms, the existing research is inconclusive. In addition, most studies focus on multinational firms based in the United States or Europe, while research in the context of emerging economies is scant. This paper endeavours to investigate the strength of the association between Environment, Social and Governance (ESG) disclosure scores and the financial performance of 272 Indian firms listed on National Stock Exchange for the period 2015 to 2021 by employing panel data regression techniques. The results indicate that organisations having better ESG performance outperform their industry peers financially and are valued more by the market. Moreover, the data indicates that financial markets for lenders consider ESG disclosure when determining creditworthiness. In accordance with this, businesses can examine their operations and become more aligned with eco-friendly methods. Even though ESG disclosure appears to be associated with improved financial success, this is not the case across all industries and during COVID-19 pandemic. This study is relevant due to the growing significance of sustainability and the role of emerging nations in international commerce. It helps managers prioritize resource allocations to ESG-related activities that may affect financial performance differently across industry sectors, thus adding to the literature on the financial effects of ESG disclosures, particularly industry-specific aspects. This research represents a pioneering effort by assessing the impact of ESG disclosure on the profitability, market value, and cost of financing of Indian firms using both aggregation and disaggregation methods.