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1 – 10 of 114Anurag Chaturvedi and Archana Singh
The paper models the financial interconnectedness and systemic risk of shadow banks using Granger-causal network-based measures and takes the Indian shadow bank crisis of…
Abstract
Purpose
The paper models the financial interconnectedness and systemic risk of shadow banks using Granger-causal network-based measures and takes the Indian shadow bank crisis of 2018–2019 as a systemic event.
Design/methodology/approach
The paper employs pairwise linear Granger-causality tests adjusted for heteroskedasticity and return autocorrelation on a rolling window of weekly returns data of 52 financial institutions from 2016 to 2019 to construct network-based measures and calculate network centrality. The Granger-causal network-based measure ranking of financial institutions in the pre-crisis period (explanatory variable) is rank-regressed with the ranking of financial institutions based on maximum percentage loss suffered by them during the crises period (dependent variable).
Findings
The empirical result demonstrated that the shadow bank complex network during the crisis is denser, more interconnected and more correlated than the tranquil period. The closeness, eigenvector, and PageRank centrality established the systemic risk transmitter and receiver roles of institutions. The financial institutions that are more central and hold prestigious positions due to their incoming links suffered maximum loss. The shadow bank network also showed small-world phenomena similar to social networks. Granger-causal network-based measures have out-of-sample predictive properties and can predict the systemic risk of financial institutions.
Research limitations/implications
The study considers only the publicly listed financial institutions. Also, the proposed measures are susceptible to the size of the rolling window, frequency of return and significance level of Granger-causality tests.
Practical implications
Supervisors and financial regulators can use the proposed measures to monitor the development of systemic risk and swiftly identify and isolate contagious financial institutions in the event of a crisis. Also, it is helpful to policymakers and researchers of an emerging economy where bilateral exposures' data between financial institutions are often not present in the public domain, plus there is a gap or delay in financial reporting.
Originality/value
The paper is one of the first to study systemic risk of shadow banks using a financial network comprising of commercial banks and mutual funds. It is also the first one to study systemic risk of Indian shadow banks.
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Xiaodan Li, Edward M. H. Lin and Min-Teh Yu
We employ three systemic risk measures of banks, including the systemic risk index (SRISK) and marginal expected shortfall (MES) of Brownlees and Engle (2017) and the conditional…
Abstract
We employ three systemic risk measures of banks, including the systemic risk index (SRISK) and marginal expected shortfall (MES) of Brownlees and Engle (2017) and the conditional Value-at-Risk (ΔCoVaR) of Adrian and Brunnermeier (2016), to analyze bank's exposure and contribution to systemic risk in the banking system when a financial crisis occurs. We find evidence that time-varying systemic risk exists, and systemic risk exposures escalate with the interconnectedness of banks. We also find revenue diversification is another significant factor that reduces a bank's exposure to systemic risk but not for banks in Taiwan and Singapore.
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While previous literature has emphasized the causal relationship from liquidity to capital, the impact of interbank network characteristics on this relationship remains unclear…
Abstract
Purpose
While previous literature has emphasized the causal relationship from liquidity to capital, the impact of interbank network characteristics on this relationship remains unclear. By applying the interbank network simulation, this paper aims to examine whether the causal relationship between capital and liquidity is influenced by bank positions in the interbank network.
Design/methodology/approach
Using the sample of 506 commercial banks established in 28 European countries from 2001 to 2013, the author adopts the generalized method of moments simultaneous equations approach to investigate whether interbank network characteristics influence the causal relationship between bank capital and liquidity.
Findings
Drawing on a sample of commercial banks from 28 European countries, this study suggests that the interconnectedness of banks within interbank loan and deposit networks shapes their decisions to establish higher or lower regulatory capital ratios in the face of increased illiquidity. These findings support the implementation of minimum liquidity ratios alongside capital ratios, as advocated by the Basel Committee on Banking Regulation and Supervision. In addition, the paper underscores the importance of regulatory authorities considering the network characteristics of banks in their oversight and decision-making processes.
Originality/value
This paper makes a valuable contribution to the current body of research by examining the influence of interbank network characteristics on the relationship between a bank’s capital and liquidity. The findings provide insights that add to the ongoing discourse on regulatory frameworks and emphasize the necessity of customized approaches that consider the varied interbank network positions of banks.
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Dhulika Arora and Smita Kashiramka
Shadow banks or non-bank financial intermediaries (NBFIs) are facilitators of credit, especially in emerging market economies (EMEs). However, there are certain risks associated…
Abstract
Purpose
Shadow banks or non-bank financial intermediaries (NBFIs) are facilitators of credit, especially in emerging market economies (EMEs). However, there are certain risks associated with them, such as their unchecked leverage and interconnectedness with the rest of the financial system. In light of this, the present study analyses the impact of the growth of shadow banks on the stability of the banking sector and the overall stability of the financial system. The authors further examine the effect of the growth of finance companies (a type of NBFIs) on financial stability.
Design/methodology/approach
The study employs data of 11 EMEs (monitored by the Financial Stability Board (FSB)) for the period 2002–2020 to examine the above relationships. Panel-corrected standard errors method and Driscoll–Kray standard error estimation are deployed to conduct the analysis.
Findings
The results signify that the growth of the shadow banking sector and the growth of lending to the shadow banking sector are negatively associated with the stability of the banking sector and increases the vulnerability of the financial system (overall instability). This implies that the higher the growth of the shadow banks, the higher the financial fragility. Finance companies are also found to negatively affect financial stability. These findings are validated by different estimation methods and point out the risks posed by the NBFI sector.
Originality/value
The extant study builds a composite index (Financial Vulnerability Index (FVI)) to measure financial stability; thus, the findings contribute to the evolving literature on shadow banks.
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Yanqi Wang, Muhammad Ali, Asadullah Khaskheli, Komal Akram Khan and Chin-Hong Puah
The objective is to assess the relationship between financial inclusion and bank profitability in emerging economies, i.e. “Bangladesh, Egypt, Indonesia, Mexico, Nigeria…
Abstract
Purpose
The objective is to assess the relationship between financial inclusion and bank profitability in emerging economies, i.e. “Bangladesh, Egypt, Indonesia, Mexico, Nigeria, Pakistan, Philippines, and Vietnam”.
Design/methodology/approach
The second-generation econometrics of panel data has been applied to examine the cross-section independence and control the heterogeneity between cross sections. Additionally, the authors employ the following tests for the analysis: “the unit root test, Westerlund's (2007) bootstrap cointegration, Pedroni cointegration, fully modified ordinary least square (FMOLS), and heterogeneous panel causality techniques”. The annual data consist of the period from 2000 to 2019.
Findings
The findings reveal that financial inclusion fosters bank profitability. Therefore, easier access to financial services and products will maximize banks' profitability. Additionally, the association between financial inclusion and bank profitability is unidirectional.
Originality/value
This research is a first attempt to bring a novel contribution to the subject of emerging economies by investigating the association between financial inclusion and bank profitability. Another unique addition to the literature is the use of a novel financial inclusion index. At last, a panel cointegration technique, FMOLS and heterogeneous panel non-causality tests are taken into consideration for the in-depth analysis.
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Vikas Sharma, Munish Gupta and Kshitiz Jangir
Introduction: Commercial banks play a vital role in the global economy, facilitating economic growth and providing essential financial services. As key intermediaries between…
Abstract
Introduction: Commercial banks play a vital role in the global economy, facilitating economic growth and providing essential financial services. As key intermediaries between savers and borrowers, these institutions operate in a dynamic and complex environment characterised by various risk factors that can significantly impact their profitability and overall stability. Understanding the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability is crucial for effective risk management strategies and the development of appropriate regulatory frameworks.
Purpose: Commercial banks play a critical role in the global economy by facilitating economic growth and providing financial services. This study examines the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability in commercial banking.
Methodology: The sample consists of licenced scheduled commercial banks on the Bombay Stock Exchange (BSE) from 2015 to 2022. Using the Smart PLS-SEM 3.0 path analysis technique, the study evaluates the combined influence of these risk factors on profitability and provides evidence-based recommendations for risk management strategies.
Findings: The findings can assist banks in enhancing their risk management practices, and regulators in developing appropriate regulatory frameworks. By understanding the key risk factors and their impact on profitability, banks and regulators can mitigate risks, enhance transparency, and promote stability within the banking sector.
Significance/value: The value of this study lies in its focus on the interconnectedness of risk factors, profitability, and the potential implications for decision-making, risk management strategies, regulatory frameworks, and the overall stability of the commercial banking sector.
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Divya Verma and Yashika Chakarwarty
Nowadays, the competition is not only emerging from within the banking sector, but nonbanking companies like nonbanking financial companies (NBFCs) and FinTech are also growing in…
Abstract
Purpose
Nowadays, the competition is not only emerging from within the banking sector, but nonbanking companies like nonbanking financial companies (NBFCs) and FinTech are also growing in size and numbers, offering innovative financial products and services, giving a stiff competition to Indian banks. Thus, this study aims to investigate whether competition from within and outside the banking sector enhances or reduces the financial stability of the banking industry.
Design/methodology/approach
The study uses Herfindahl–Hirschman index to measure market share and Z score to measure financial stability. The study further examines the role of NBFCs and FinTech companies in impacting the financial stability by introducing variables like innovation, cybercrimes, systemically important institutions, etc. Thereafter, panel regression has been applied.
Findings
Empirical results show a positive relation of market share with financial stability, implying that increased competition in the Indian banking industry erodes the market power, adversely affecting the profit margins which encourages banks to take more risk and which may impact financial stability. The study shows a positive impact of innovation on financial stability which implies that the competition is acting as an enabler for banks. The authors find a negative relation of systemic important NBFCs with financial stability. The authors observe a negative association of cybercrimes with financial stability, reflecting that competition emerging from FinTech sector has exposed banks to new risks.
Research limitations/implications
The policymakers should make sure that the competition of banks with other financial institutions, such as FinTech sector, remains healthy; otherwise, it can jeopardize the entire financial system. It is for the policymakers to define a boundary for FinTech sector, as the development of this sector has exposed the banking industry to new kinds of risks potential to create financial instability. The banks should do a comprehensive check on the company to which it is granting loans, and the government should amend laws. Though big banks have huge potential, consolidations can pose challenges at a macroeconomic level.
Originality/value
FinTech firms are a new entrant in the financial world which are providing immense competition to the banking sector, and thus radically changing the entire financial system. Therefore, it is extremely vital to study and explore the role of NBFCs and the FinTech industry as the main variable to analyze bank competition, which to the best of the authors’ knowledge is completely missing in the previous studies.
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Oswald A. J. Mascarenhas, Munish Thakur and Payal Kumar
Systems thinking calls for a shift of our mindset from seeing just parts to seeing the whole reality in its structured dynamic unity and interconnectedness. Systems thinking…
Abstract
Executive Summary
Systems thinking calls for a shift of our mindset from seeing just parts to seeing the whole reality in its structured dynamic unity and interconnectedness. Systems thinking fosters a sensibility to see subtle connections between components and parts of reality, especially the free enterprise capitalist system (FECS). It enables us to see ourselves as active participants or partners of FECS and not mere induced factors of its production–distribution–consumption processes. Systems thinking seeks to identify the economic “structures” that underlie complex situations in FECS that bring about high versus low leveraged changes. A system is strengthened and reinforced by feedback of reciprocal exchanges that makes the system alive, transparent, human, and humanizing.
In Part I, we explore basic laws or patterns of behaviors as understood by systems thinking; in Part II we examine the basic archetypes or structured behaviors of systems thinking; in both parts we strive to see reality through the lens of critical thinking to help us understand patterns and structures of behavior among systems and their component parts. In conclusion, we argue for compatibility and complementarity of critical thinking and systems thinking to identify and resolve management problems created by our flawed thinking, and sedimented by our wanton assumptions, presumptions, suppositions and presuppositions, biases, and prejudices. Such thinking will also identify unnecessary economic and political structures of the self-serving policies we create, which imprison us.
Mugabil Isayev, Farid Irani and Amirreza Attarzadeh
The purpose of this paper is to fill the momentous gap by explicitly investigating the asymmetric effects of monetary policy (MP) on non-bank financial intermediation (NBFI…
Abstract
Purpose
The purpose of this paper is to fill the momentous gap by explicitly investigating the asymmetric effects of monetary policy (MP) on non-bank financial intermediation (NBFI) assets.
Design/methodology/approach
The authors utilized panel data from 29 countries for the period of 2012–2020 and used the quantile regression estimation. In addition to simultaneous quantile regression (SQR), the authors also employ quantile regression with clustered data (Parente and Silva, 2016) and the generalized quantile regression (GQR) method (Powell, 2020).
Findings
The empirical results show a significant heterogeneous impact of MP. While there is a positive relationship between MP and NBFI assets (“waterbed effect”) at lower quantiles of NBFI assets, at middle and higher quantiles, MP has a negative impact on NBFI assets (“search for yield” effect). The authors further find that negative impact strengthens as the quantile levels of NBFI assets rise from mid to high. Findings also reveal that “procyclicality” (except higher quantile) and “institutional demand” hypotheses hold. However, regarding “regulatory arbitrage,” mixed results are observed indicating the impact of Basel III requirements.
Originality/value
Previous empirical studies have concentrated on either the Dynamic Stochastic General Equilibrium (DSGE) framework or conditional mean regression approaches and delivered mixed findings of the MP effects on NBFI. The current paper takes a step toward dealing with this issue by deploying quantile regression methodology, which shows the impact of MP on NBFI at different conditional distributions (quantiles) of NBFI assets instead of just NBFI's conditional mean distribution.
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Jaewon Choi and Jieun Lee
The authors estimate systemic risk in the Korean economy using the econometric measures of commonality and connectedness applied to stock returns. To assess potential systemic…
Abstract
The authors estimate systemic risk in the Korean economy using the econometric measures of commonality and connectedness applied to stock returns. To assess potential systemic risk concerns arising from the high concentration of the economy in large business groups and a few export-oriented sectors, the authors perform three levels of estimation using individual stocks, business groups, and industry returns. The results show that the measures perform well over the study’s sample period by indicating heightened levels of commonality and interconnectedness during crisis periods. In out-of-sample tests, the measures can predict future losses in the stock market during the crises. The authors also provide the recent readings of their measures at the market, chaebol, and industry levels. Although the measures indicate systemic risk is not a major concern in Korea, as they tend to be at the lowest level since 1998, there is an increasing trend in commonality and connectedness since 2017. Samsung and SK exhibit increasing degrees of commonality and connectedness, perhaps because of their heavy dependence on a few major member firms. Commonality in the finance industry has not subsided since the financial crisis, suggesting that systemic risk is still a concern in the banking sector.
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