scholarly journals Research on Financial Systemic Risk in ASEAN Region

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1131
Author(s):  
Hong Fan ◽  
Renyun Liu
Keyword(s):  
Systemic Risk ◽  
Closeness Centrality ◽  
Weak Links ◽  
Density Method ◽  
Minimum Density ◽  
Regulatory Authorities ◽  
Node Centrality ◽  
Risk Areas ◽  
Asean Countries ◽  
Systemically Important Banks

The research of financial systemic risk is an important issue, however the research on the financial systemic risk in ASEAN region lacks. This paper uses the minimum density method to calculate the interbank network of ASEAN countries and uses the node centrality to judge the systemically important banks of various countries. Then the DebtRank algorithm is constructed to calculate the systemic risk value based on the interbank network. By comparing the systemic risk values obtained through the initial impact on the system important banks and non-important banks, we find that the systemic risk tends to reach the peak in the case of the initial impact on the system important banks. Furthermore, it is found that countries with high intermediary centrality and closeness centrality have higher systemic risk. It suggests that the regulatory authorities should implement legal supervision, strict supervision, and comprehensive supervision for key risk areas and weak links.

Harmonized Regulations and Systemic Risk: Evidence from Global-Systemically Important Banks

2015 ◽  
Author(s):  
Kathryn L. Dewenter ◽  
Alan C. Hess
Keyword(s):  
Systemic Risk ◽  
Systemically Important Banks

scholarly journals Systemic risk measurement: bucketing global systemically important banks

2021 ◽  
Author(s):  
Marina Brogi ◽  
Valentina Lagasio ◽  
Luca Riccetti
Keyword(s):  
Systemic Risk ◽  
Financial System ◽  
Capital Requirements ◽  
Insurance Premium ◽  
Risk Measurement ◽  
Marginal Contribution ◽  
General Consensus ◽  
Systemically Important Banks

AbstractThe general consensus on the need to enhance the resilience of the financial system has led to the imposition of higher capital requirements for certain institutions, supposedly based on their contribution to systemic risk. Global Systemically Important Banks (G-SIBs) are divided into buckets based on their required additional capital buffers ranging from 1% to 3.5%. We measure the marginal contribution to systemic risk of 26 G-SIBs using the Distressed Insurance Premium methodology proposed by Huang et al. (J Bank Financ 33:2036–2049, 2009) and examine ranking consistency with that using the SRISK of Acharya et al. (Am Econ Rev 102:59–64, 2012). We then compare the bucketing using the two academic approaches and supervisory buckets. Because it leads to capital surcharges, bucketing should be consistent, irrespective of methodology. Instead, discrepancies in the allocation between buckets emerge and this suggests the complementary use of other methodologies.

scholarly journals Banks behavior patterns as a response to the population financial activity in the macroeconomic shocks in Russia

2021 ◽  
Vol 50 (2) ◽  
pp. 74-95
Author(s):  
Yu.S. Evlakhova ◽  
◽  
E.N. Alifanova ◽  
A.A. Tregubova ◽  
◽  
...  
Keyword(s):  
Systemic Risk ◽  
Banking Sector ◽  
Behavior Pattern ◽  
Behavior Patterns ◽  
Economic Shocks ◽  
Macroeconomic Shocks ◽  
Financial Activity ◽  
Risk Research ◽  
Systemically Important Banks

This paper finds out the behavior patterns of the Russian banking sector and systemically important banks in response to changes in the population financial activity under the economic shocks. The results show that the Russian banking sector has a behavior pattern that includes the sequence of actions: the outflow of deposits — vulnerability to non-repayment of loans — deposit bubble — credit bubble. We find no consistent evidence that systemically important banks show the same sequence of actions during the crises. We also find that the banking sector behavior and systemically important banks’ behavior varied in 2008–2009, but became the same in the crisis of 2014–2015. The coincidence of behavior patterns of the banking sector and systemically important banks increases the systemic risk. Research on intragroup differences between systemically important banks will allow finding solutions to reduce the risk.

Systemic risk in ASEAN-6: a new empirical investigation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Trung Hai Le
Keyword(s):  
Empirical Evidence ◽  
Systemic Risk ◽  
Business Models ◽  
Financial Integration ◽  
Global Financial Crisis ◽  
Macroprudential Policy ◽  
Content Type ◽  
Risk Dynamics ◽  
Asean Countries ◽  
Book Values

PurposeThe authors provide a comprehensive study on systemic risk of the banking sectors in the ASEAN-6 countries. In particular, they investigate the systemic risk dynamics and determinants of 49 listed banks in the region over the 2000–2018 period.Design/methodology/approachThe authors employ the market-based SRISK measure of Brownlees and Engle (2017) to investigate the systemic risk of the ASEAN-6's banking sectors.FindingsThe authors find that the regional systemic risk fluctuates significantly and currently at par or higher level than that of the recent global financial crisis. Systemic risk is generally associated with banks that have bigger size, more traditional business models, lower quality in their loan portfolios, less profitable and with lower market-to-book values. However, these relationships vary significantly between ASEAN countries.Research limitations/implicationsThe research focuses on the systemic risk of ASEAN-6 countries. Therefore, the research results may lack generalizability to other countries.Practical implicationsThe authors’ empirical evidence advocates the use of capital surcharges on the systemically important financial institutions. Although the region has been pushing to higher financial integration in recent years, the authors encourage the regional regulators to account for the idiosyncratic characteristics of their banking sectors in designing effective macroprudential policy to contain systemic risk.Originality/valueThis paper provides the first study on the systemic risk of the ASEAN-6 region. The empirical evidence on the drivers of systemic risk would be of interest to the regional regulators.

scholarly journals Bank Networks and Systemic Risk: Evidence from the National Banking Acts

2019 ◽  
Vol 109 (9) ◽  
pp. 3125-3161 ◽  
Author(s):  
Haelim Anderson ◽  
Mark Paddrik ◽  
Jessie Jiaxu Wang
Keyword(s):  
Network Model ◽  
Network Structure ◽  
Systemic Risk ◽  
Financial Stability ◽  
Balance Sheets ◽  
Unique Data ◽  
Financial Center ◽  
Bank Balance Sheets ◽  
The City ◽  
Systemically Important Banks

The National Banking Acts (NBAs) of 1863–1864 established rules governing the amounts and locations of interbank deposits, thereby reshaping the bank networks. Using unique data on bank balance sheets and detailed interbank deposits in 1862 and 1867 in Pennsylvania, we study how the NBAs changed the network structure and quantify the effect on financial stability in an interbank network model. We find that the NBAs induced a concentration of interbank deposits at both the city and bank levels, creating systemically important banks. Although the concentration facilitated diversification, contagion would have become more likely when financial center banks faced large shocks. (JEL E44, G01, G21, G28, L14, N21)

scholarly journals Systemic risk in the banking system: measuring and interpreting the results

2019 ◽  
Vol 14 (3) ◽  
pp. 34-47
Author(s):  
Olena Bezrodna ◽  
Zoia Ivanova ◽  
Yulia Onyshchenko ◽  
Volodymyr Lypchanskyi ◽  
Serhii Rymar
Keyword(s):  
Systemic Risk ◽  
Financial Risk ◽  
Banking System ◽  
Cumulative Effect ◽  
Risk Indicators ◽  
Risk Indicator ◽  
Regime Types ◽  
Systemic Crisis ◽  
Integral Assessment ◽  
Systemically Important Banks

Highly concentrated banking system risks and the cumulative effect due to their accumulation act as a driver for improving the macro-prudential policy implemented by central banks. For this reason, an effectively and comprehensively assessed systemic risk in the banking system is declared an express condition for the early detection of its production sources and blocking of potential spreading channels, reducing the possible implementation. In light of this, the article develops an approach to the aggregated systemic risk assessment and interpretation of its results. The proposed approach is based on the considered influence exerted by financial risks of systemically important banks on the destabilized banking system and interconnections between banks in the context of the possible crisis impulse spreading. The following steps should be accomplished to form an aggregated systemic risk indicator in the banking system. Firstly, the differentiation of systemically important banks by the degree of their systemic importance; secondly, an integral assessment of the bank operation riskiness within certain bank groups; thirdly, the cumulative composition of the corresponding integral indicators, taking into account their weighting coefficients based on two criteria, namely values of the systemic importance indicator differentiating the bank groups, and the correlation of their risks. Interpreting the quantitative measurement results with regard to the systemic risk in the banking system is followed by the recommendations below: the systemic risk grading into high, medium and low levels and the respective definition of the threshold aggregated systemic risk indicator value which informs about the possible systemic crisis when approached; justification of the selected supervision regime types (strengthened, moderate or weakened) for systemically important banks, depending on the riskiness level specific for their operation and the systemic importance degree. The developed approach to measuring the systemic risk by means of constructing an aggregated indicator and interpreting the obtained results was being tested considering the financial risk indicators of the systemically important banks in Ukraine during 2009–2018.

Identification of systemically important banks in India using SRISK

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Juhi Gupta ◽  
Smita Kashiramka
Keyword(s):  
Systemic Risk ◽  
Banking Sector ◽  
Global Financial Crisis ◽  
Balance Sheet ◽  
Data Set ◽  
Content Type ◽  
Long Run ◽  
Marginal Expected Shortfall ◽  
The Global Financial Crisis ◽  
Systemically Important Banks

Purpose Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019. Design/methodology/approach In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk. Findings This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank. Originality/value Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.

scholarly journals The parallel computing of node centrality based on GPU

2022 ◽  
Vol 19 (3) ◽  
pp. 2700-2719
Author(s):  
Siyuan Yin ◽  
◽  
Yanmei Hu ◽  
Yuchun Ren
Keyword(s):  
Parallel Computing ◽  
Network Analysis ◽  
Parallel Algorithms ◽  
Betweenness Centrality ◽  
Large Scale ◽  
Rapid Development ◽  
Closeness Centrality ◽  
Node Centrality ◽  
Speed Up ◽  
Large Scale Networks

<abstract> <p>Many systems in real world can be represented as network, and network analysis can help us understand these systems. Node centrality is an important problem and has attracted a lot of attention in the field of network analysis. As the rapid development of information technology, the scale of network data is rapidly increasing. However, node centrality computation in large-scale networks is time consuming. Parallel computing is an alternative to speed up the computation of node centrality. GPU, which has been a core component of modern computer, can make a large number of core tasks work in parallel and has the ability of big data processing, and has been widely used to accelerate computing. Therefore, according to the parallel characteristic of GPU, we design the parallel algorithms to compute three widely used node centralities, i.e., closeness centrality, betweenness centrality and PageRank centrality. Firstly, we classify the three node centralities into two groups according to their definitions; secondly, we design the parallel algorithms by mapping the centrality computation of different nodes into different blocks or threads in GPU; thirdly, we analyze the correlations between different centralities in several networks, benefited from the designed parallel algorithms. Experimental results show that the parallel algorithms designed in this paper can speed up the computation of node centrality in large-scale networks, and the closeness centrality and the betweenness centrality are weakly correlated, although both of them are based on the shortest path.</p> </abstract>

scholarly journals Leverage and Risk Taking under Moral Hazard

2021 ◽  
Author(s):  
Christian Hott
Keyword(s):  
Moral Hazard ◽  
Risk Taking ◽  
Systemic Risk ◽  
Basel Iii ◽  
Capital Regulations ◽  
Systemically Important Banks

AbstractIn this paper, I analyze the effectiveness of different capital regulations in mitigating the effects of moral hazard that exists only for systemically important banks. Leverage restrictions have the potential to reduce the fraction of banks that are systemically important but do not mitigate moral hazard for those that are. Risk adjusted requirements could mitigate moral hazard (of banks with low leverage) but do not affect (endogenous) systemic risk. A combination of both requirements as proposed by the Basel III framework can be successful, although only under restrictive conditions.

scholarly journals Development of a methodology for assessing systemically important Ukrainian banks and a Z-score

2020 ◽  
Vol 15 (2) ◽  
pp. 230-242
Author(s):  
Oleksandra Hirna ◽  
Vira Druhova ◽  
Lidiia Dudynets ◽  
Olha Vernei ◽  
Dariusz Wawrzyniak
Keyword(s):  
Systemic Risk ◽  
State Ownership ◽  
Assessment Methodology ◽  
International Banking ◽  
Z Score ◽  
Asset Return ◽  
Leading Role ◽  
Domestic Capital ◽  
Banking Business ◽  
Systemically Important Banks

The indicator-based method recommended by the Basel Committee is one of the most common approaches to identifying systemically important banks. National authorities often establish their own methodology by adding modern tools that, in their opinion, adequately capture systemic risk in their domestic economy. The paper shows that the updated methodology for assessing systemically important Ukrainian banks can be verified on publicly available data. The analysis confirms that the updated version of the National Bank’s assessment methodology is in line with those recommended by international banking institutions, but does not fully capture the current systemic risk factors. Systematization of literary and statistical sources indicates that one of the main sources of systemic risk in Ukraine is the establishment of a state monopoly in the banking market. Thus, the assessment methodology should be supplemented by instruments to evaluate the performance of the banking business. The indicator-based method and the minus one bank Z-score approach were tested to identify Ukrainian systemically important banks from 2010 to 2017.The loss of the leading role of PrivatBank in ensuring banking stability after the transition to state ownership since 2016, as well as the equalization of the systemic risk contribution of banks with state, foreign and domestic capital, was discovered. The study empirically confirms that Z-index, which combines the positive characteristics of the static asset return ratio and bankruptcy probability, can be used to determine the methodology as an indicator of the performance of systemically important banks, primarily state-owned banks.

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