Important Financial Institutions Research Articles

Does macroprudential policy have any side effects on the shadow economy?

Purpose This paper aims to examine the impacts of macroprudential policy on the shadow economy worldwide. Design/methodology/approach We compile a panel dataset covering 125 countries from 1990 to 2018. This paper mitigates potential endogeneity issues via two-stage least squares and the two-step generalized method of moments (GMM). Findings The robust results show that the overall tightening of macroprudential policies exerts an expansion impact on the shadow economy. Further examination of the 16 individual macroprudential policy instruments finds that loan restrictions, countercyclical buffers, surcharges for systemically important financial institutions and capital conservation buffers have positive and statistically significant effect on the shadow economy. This relationship is only present during tightening episodes of macroprudential policy as loosening episodes do not exhibit any significant impact. Finally, this paper documents the nonlinear effects of macroprudential policy. Practical implications The results suggest that the supervisory authorities may need to consider another parameter, which is the development of the shadow economy, when devising the optimal macroprudential policy responses. Originality/value To the best of the authors’ knowledge, this paper is likely the first to empirically document the impact of macroprudential policy on the shadow economy. It contributes to the growing literature on the potential side effects of macroprudential policy on the macro-economy.

The Role of Financial Cooperatives in Building Trust: A Gender Wise Global Analysis

Financial institutions are crucial for economic development. Lack of trust in financial institutions such as banks can have catastrophic consequences, as observed during past financial crises and the COVID-19 pandemic. Considering the importance of financial institutions, we examine the major factors influencing trust in financial institutions among the female population at a global sample. We explore the potential impact of contextual factors, such as institutional performance and country-level trust, on trust in financial institutions by employing logit and Probit models in a global data set. We find that women tend to trust banks more than men on average. We propose that greater gender equality in society and financial inclusion can decrease the gender gap in trust in banks at the country level.

Article: The Systemic Importance of Asset Managers: A Case Study for the Future of SIFI Regulation

The nexus between financial stability and the asset management industry remains understudied. I question whether asset managers and/or investment funds could be systemically important, and if so, how financial regulation in the EU and US should cope with this. From a review of the available economic literature and policy standpoints, it emerges that asset managers and the funds that they manage can create systemic risk through fire sales. While in some cases nonbanks can be designated as systemically important under EU and US law, asset managers and investment funds do not fit well in this framework. Consequently, the current rules, concerning both designation and subsequent regulation, fall short. Instead, a simple designation rule could directly address the way in which asset managers can cause or amplify systemic risk. Regulation and supervision should equally address this fire sale risk. I propose a market-based prudential measure, complemented by centralised supervision, that does so. The case of systemically important asset managers shows that current SIFI regulation does not sufficiently account for the systemic risks that can and will be caused by nonbank financial institutions. I therefore advocate a rethink, such that it has a wider institutional scope but more accurately addresses sectoral differences. Financial stability, systemic risk, systemically important financial institutions, nonbank financial institutions, asset management, investment funds, SIFI regulation, fire sales, EU law, US law.

The Impact of COVID-19 on Banking Sector Returns, Profitability, and Liquidity in South Africa

The COVID-19 pandemic, which initially started as a health crisis, has had widespread economic impacts on various industries in the global economy. The banking sector, in particular, was significantly impacted by fiscal and monetary responses which were implemented to reduce the closure of several businesses and stabilize markets. Given that banks are regarded as systemically important financial institutions, this heightened uncertainty increased the possibility of a financial crisis because instabilities in the banking sector could have further detrimental effects on national and global economies. Therefore, the objective of this study was to explore the effect of the COVID-19 pandemic on the South African banking sector. To achieve this objective, the study analysed the returns, profitability, and liquidity of banks listed on the Johannesburg Stock Exchange using a panel regression approach. Together, the results of the study revealed that the profitability and liquidity of banks were negatively impacted by the COVID-19 pandemic, however, the excess bank stock returns generated by investors were not affected. These findings may serve as reference to policymakers when developing policies which regulate the banking sector in order to improve performance and ensure liquidity during periods of increased market uncertainty.

Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model

Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model

Ranking systemically important financial institutions of the Chinese financial system: evidence from the higher-order temporal network

ABSTRACT Identifying systemically important financial institutions (SIFIs) plays a key role in regulating systemic risk. We construct higher-order temporal causal networks based on daily stock return data and rank the systemic importance of 45 listed financial institutions. The constructed networks provide evidence that financial institutions become more interrelated during crisis periods, and capture the higher-order dynamic characteristics of interconnectedness among institutions. The ranking results show that not only the largest financial institutions, but also smaller, highly interconnected institutions are systemically important and need to be regulated. Our findings highlight the importance of considering higher-order interconnectedness among financial institutions when labelling SIFIs.

Volatility spillover features in financial industries and identification of systemically important financial institutions: A new perspective

We study the spillover effects between financial industries and the identification of systemically important financial institutions (SIFIs) from a new perspective. The total volatility is decomposed into two categories, i.e., good volatility triggered by positive returns and bad volatility triggered by negative returns, which are applied to the volatility spillover index (the DY spillover index) model (Diebold and Yilmaz, 2012; 2014) to study the volatility spillover effects between different financial industries based on different types of volatility. We construct the total, good, and bad volatility spillover networks and use PageRank to measure the systemic importance of financial institutions based on the three networks and compare them with the risks of financial institutions obtained by the three risk measurement methods of ΔCoVaR, MES, and SRISK. By decomposing total volatility into good volatility triggered by positive returns and bad volatility triggered by negative returns, the positive and negative impacts of different financial industries during different periods can be effectively identified to accurately evaluate the risk levels of different financial industries. The results indicate that the PageRank rankings of financial institutions calculated by the bad volatility spillover network have the highest correlation with the risk rankings of financial institutions calculated by ΔCoVaR, MES, and SRISK. The findings suggest the necessity of decomposing the spillover effects between financial industries into good spillover effects triggered by positive returns and bad spillover effects triggered by negative returns, providing a new way of identifying SIFIs.

Regulation of the Financial System in the Republic of Congo

After the 2008 subprime crisis, financial institutions in the Congo (Brazzaville) underwent a series of significant adjustments and reforms in line with their regulatory traditions of systemically important financial institutions, the evolution of the regulatory system, and the country’s financial development needs. This paper needs to analyze and study financial regulation in the Republic of Congo. This paper mainly analyzes the current situation of the financial regulatory system of the Republic of the Congo (Brazzaville), finds the problems in the financial regulatory system, collects accessible financial data and financial indicators, and constructs the financial regulatory system of the Republic of the Congo (Brazzaville) with principal component analysis. This paper uses the GARCH-CoVaR model to assess the contribution of banks’ systemic risk in Congo Brazzaville. Then, it constructs a risk assessment system for Congo based on the indicator method. The results show that banks’ systemic risk is not limited to the systemic risk of individual banks. The systemic risk of banks in the Republic of Congo mainly originates from six major banks: the Central Bank of the State of Congo, the Bank of Congo, the Bank of Commerce and Credit of Congo, the Savings Bank of Congo, the Central Bank for the Development of Central African States, the Central Bank of Africa, and the Central Bank of Africa.

Friend or foe? The impact of macroprudential policy on economic growth

ABSTRACT In this paper, we examine the impact of macroprudential policy on economic growth. The results show that the implementation of macroprudential policies contributes to fostering economic growth, especially in the period following the onset of the global financial crisis. In particular, we show that tightening loan loss provisions, loan-to-value, lending restriction, liquidity requirements and systemically important financial institutions measures all lead to higher economic growth. However, we also find that, while tightening macroprudential policy is generally beneficial for the economy, excessive tightening policy can exert a negative growth impact.

The impact of risk spillover network-based multidimensional systemic risks on the real economy

ABSTRACT Multidimensional systemic risk measures are constructed based on dynamic risk spillover networks to quantify the level, transmission speed, and transmission breadth. To investigate the significance, direction, magnitude, and persistence of the impacts of systemic risks on future real economic distribution, we combine the quantile regression model and Bootstrap quantile t test method. Finally, the heterogeneity of the impacts of systemic risks and SIFIs (systemically important financial institutions) risks is analysed. Our empirical results find that 1) most bank companies take the role of risk drivers in the financial system, while most security, insurance, trust, and real estate companies take the role of risk distributors and risk receivers. 2) the total spillover index, average shortest path length, and average clustering coefficient have significant impacts on the left tail and central tendency of future real economy, and the latter two measures also have significant impacts on the right tail. 3) SIFIs risks have earlier and greater impacts than Non-SIFIs (non-systemically important financial institutions) risks. Multidimensional systemic risks contain additional information to identify financial risks earlier than single institutions risks. 4) the impacts of financial risks on the real economy are persistent. The superimposition of impacts may trigger extreme risks.

Systemically important financial institutions and drivers of systemic risk: Evidence from India

The aim of this study is twofold: (1) identify the systemically important financial institutions in India and their contributing role to Indian systemic risk during various global and domestic events; and (2) uncover the factors driving systemic risk in Indian financial institutions. To serve the first aim, we estimate financial institutions' involvement in the overall risk of the Indian financial market using the component expected shortfall approach. The results show that the State Bank of India, ICICI Bank, HDFC Bank, and HDFC Ltd. contribute more than 50% to the aggregate risk in India, demonstrating a significant systemic risk concentration. These financial institutions are also referred to as domestic systemically important banks (D-SIBs) by the Reserve Bank of India (the central bank in India). Financial institutions show an increased contribution to overall systemic risk after the systemic events considered in the study. Furthermore, results indicate that banks play a dominating role in contributing to systemic risk in India; however, the analysis also indicates the increasing contribution of non-banking financial companies and insurance firms to the gross risk of the Indian financial market in recent years. To serve the second aim, we apply panel data regressions and show that the probability of default, leverage, loan, liquidity, board size, and Basel norms are significant drivers of systemic risk. Besides the importance of our findings for investment and risk management decisions during crisis periods, our findings have implications for policymakers overseeing the financial system in India, assessing potential vulnerabilities and designing prudential regulatory and action plans to maintain financial stability.

Determinant Factors Analysis of Bank Profitability: Study On Indonesian Banks Period 2019-2022

The banking sector is one of the most important financial institutions in the Indonesian economy. Banks are the significant driver of economic growth by delivering capital toward productive investments. Thus, banks must be profitable to continue operating and support economic growth. This study investigates the relationship between bank-specific determinants of Bank Size (SIZE), Capital Adequacy Ratio (CAR), Loan Deposit Ratio (LDR), Operating Cost to Operating Income (OCOI), and Non-Performing Loans (NPL) toward Bank Profitability measured by Return on Asset (ROA). The research uses data from 10 Indonesian banks in KBMI 3 and 4 categories from 2019 – 2022. Classical assumption tests are run to ensure the data is considered BLUE. The study used Fixed Effect Model panel data regression. The research results show that CAR has a positive insignificant relationship toward ROA while LDR has a positive significant relationship toward ROA. In contrast, SIZE, OCOI, and NPL have a negative significant relationship toward ROA. Due to the SIZE, LDR, OCOI, and NPL showing a significant relationship with ROA, this study recommends that bank management pay more attention to these variables to maintain the banks' ROA.

Robust Risk Quantification via Shock Propagation in Financial Networks

Robust Risk Quantification via Shock Propagation in Financial Networks Despite the significance of risk contagion in financial networks, uncertainties arise in interbank network structures because of limited information. To address this, proposed is a robust optimization approach to estimate worst-case default probabilities and capital requirements for a specific group of banks (e.g., systemically important financial institutions). By applying this tool, we analyze the impact of different incomplete network information structures and gain regulatory insights into gathering actionable network information.

Struggle to survive: case of flood risk on US community banks

PurposeThe survivorship of firms under extreme weather poses an essential question about the local economy's health. Over 90% of agricultural banks are categorized as community banks, which are important financial institutions promoting local growth. While previous studies suggest that climate change and weather shocks adversely impact community banks' resiliency, studies on whether these institutions engage in risk-reducing management strategies have been limited. In this study, the authors examine strategic choices of local community banks when facing flood events which include (1) safety net increase, (2) portfolio diversification, and (3) branch opening. These strategic choices are the coping mechanisms banks can take to survive while affecting the local competitive lending market.Design/methodology/approachThe authors use panel-fixed effect regressions based on the storm data from National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) and the call reports from the Federal Deposit Insurance Corporation (FDIC). The authors focus on community banks' account variable characteristics and the number of offices to examine whether community banks take an active role in managing flood risk.FindingsResults suggest that community banks do employ the selected strategic choices to a certain degree, as it is found that there is an increase in the core capital that absorbs shocks and portfolio diversification. However, the magnitudes of these activities are rather small and not large enough to fully mitigate the climate risk. Also, the authors do not find any evidence of branch expansion associated with local floods.Originality/valueThis study contributes to the literature by examining different strategic choices of community banks in the face of natural uncertainty. Even though concerns of climate risk have been raised in the regulatory setting, a lack of guidance or assessment tools could contribute to the passive action of these community banks, even though climate risks can have a significant economic impact. Thus, the evidence documented from this study calls for further guidelines and the importance of highlighting climate risks on community banks so that they can actively engage in risk-reducing strategies.

An Evaluation of the Banking System to End the Country's Financial Crisis

The current worldwide financial crisis is the result of a confluence of elements that have existed in previous financial crises as well as some fresh elements. Several flaws in financial architecture and regulation have come to light as a result of the crisis, particularly in how systemically important financial institutions are handled. Financial institutions, systemic risk and vulnerability assessments, and financial institution resolution. The fact that the financial crisis is a global phenomenon has demonstrated that, while financial integration markets provide many advantages, they can also carry a high risk of serious economic consequences. To ensure the stability of a world that is becoming more and more financially interconnected, significant modifications to the international financial architecture are obviously required

Customers as Friendly Shareholders: Uncovering the Complex Mutual Fund-Broker Relationship

This paper examines mutual funds’ dual role as both clients and shareholders of broker banks. Mutual funds are more likely to hold and significantly overweight stocks of their broker banks. In line with the portfolio decisions, fund voting is biased toward broker management in contentious proposals. Such voting bias is inconsistent with maximizing broker banks’ shareholder value yet significantly affects voting outcomes and the presence of contentious proposals at the banks’ shareholder meetings. Furthermore, we show that although client funds are rewarded with preferential initial public offering allocations from connected brokers for their voting support, fund managers’ engagement in reciprocal practices is ultimately determined by the economic tradeoffs they face. Our study not only uncovers a new mechanism—being brokers’ friendly shareholders—through which the two parties maintain their quid pro quo relationships but also raises a broader concern about governance of important financial institutions. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4820 .

Network effects on risk co-movements: A network quantile autoregression-based analysis

Interconnections and volatilities among financial institutions, notably during periods of extreme risk events, are fundamental factors in studies of financial markets. Utilizing tail-event-driven networks, we depict the risk interdependencies among financial institutions and introduce a novel ranking strategy for institutional influence based on network effects and quantile regression techniques. This interdependence is examined through the prism of joint extreme movements, utilizing bivariate extreme value theory and classification analysis. To validate their effectiveness and applicability in the real world, we deploy these methodologies on Systemically Important Financial Institutions (SIFIs). Additionally, we provide a ranking of the importance of eight U.S. institutions based on tail risks, offering regulators valuable insights and references.

Risk contagion in financial markets: A systematic review using bibliometric methods

AbstractWe explore evolving research trends and hotspots in financial contagion through keywords co‐occurrence and co‐citation network analyses. 2,071 articles have been collected from Web of Science Core Collection database from 2005 to 2021 and been analyzed by using bibliometric methods. The results indicate a tremendous growth in research on financial contagion, especially following the Global Finance Crisis. The current research mainly focuses on understanding the causes and consequences of past financial crises and recessions, examining the network effects of banks and other important financial institutions on risk contagion, developing new systematic approaches to modelling financial contagion, and providing empirical evidences for financial contagion among various asset classes and across different countries and regions. We find that there is still no consensus regarding the causes and measures of financial contagion, however, new promising perspectives have emerged to expand research in this area. We also propose several future directions for studies on financial contagion based on the research gap identified in this review.

A Hybrid Approach for the Assessment of Risk Spillover to ESG Investment in Financial Networks

In this paper, we present a framework for evaluating risk contagion by merging financial networks with machine learning techniques. The framework begins with building a financial network model based on the inter-institutional correlation network, followed by analyzing the structure and overall value changes of the financial network under the stress of a liquidation shock. We then examine the network’s evolution over time. We also use three machine learning techniques to assess the abnormal volatility of important financial institutions in the financial network. Finally, we evaluate the spillover effects of risk volatility in financial networks on ESG investments. The findings suggest that the financial network becomes more robust as the connections among financial institutions become more intricate. This leads to an improvement in the ability of the financial network to withstand systemic risk events. Overall, our study provides evidence of the negative impact of risk spillovers in financial networks on ESG investments, highlighting the need for a more sustainable and resilient financial system. This innovative framework combining financial network modeling and machine learning prediction provides a deeper understanding of the evolution of financial networks and a more accurate evaluation of abnormal volatility in financial networks.

Identifying influential financial stocks using simulation with a two-layer network

Risk spillover from one stock to another tends to create a contagion effect in the stock market. Fire sales due to the overlapping portfolios of mutual funds can amplify the contagion risks, leading to a downward spiral of stock prices. In this paper, we simulate this downward spiral phenomenon for the Chinese financial stocks based on a two-layer network structure and aim to identify the influential financial stocks based on their individual induced systemic risks. Our findings show that stock liquidity and the concentration of funds’ holding on stocks play important roles in determining systemically important financial institutions. Our results also confirm the statements of “too-big-to-fail” and “too-interconnected-to-fail” of financial institutions in the Chinese market. Our results show that a more sensitive flow-performance relationship of mutual funds can amplify the contagion risk by 41%. However, the magnitude can be more drastic in a low market liquidity scenario, where the contagion risk is boosted by 160%.