scholarly journals Systemic Risk Assessment: Aggregated and Disaggregated Analysis on Selected Indian Banks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Mohammed Arshad Khan ◽  
Preeti Roy ◽  
Saif Siddiqui ◽  
Abdullah A. Alakkas
Keyword(s):  
Systemic Risk ◽  
Value At Risk ◽  
Banking Sector ◽  
Global Financial Crisis ◽  
Conditional Value At Risk ◽  
Public Confidence ◽  
State Variables ◽  
Global Risk ◽  
Private Banks ◽  
Indian Banks

Exposure of the banking system to the Global Financial Crisis attracted attention to the study of riskiness and spillover. This paper studies the pattern of systemic risk and size effect in the Indian banking sector. Based on market capitalization, three public sector banks and three from the private sector were taken. Data are taken from the year 2007 to 2020. The analysis is done through quantile- CoVaR  (Conditional Value at Risk) and TENET (Tail-Event-Driven Network) measure. State variables like Indian market volatility and global risk measures negatively influence the Indian banks’ returns. Liquidity risk is a crucial aspect of private banks. Public banks experience public confidence even in the distress period. Large banks like HDFC and SBI bank offer the highest degree of systemic risk contribution. The role of private banks in transmitting systemic risk has been intensifying since 2015. Small-sized banks like PNB and BOB have become significant receivers and transmitters of risk.

scholarly journals On Identifying the Systemically Important Tunisian Banks: An Empirical Approach Based on the △CoVaR Measures

Risks ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 122 ◽  
Author(s):  
Wided Khiari ◽  
Salim Ben Sassi
Keyword(s):  
Systemic Risk ◽  
Value At Risk ◽  
Banking Sector ◽  
Financial Institution ◽  
Herd Behavior ◽  
Financial Difficulties ◽  
Private Banks ◽  
Close Supervision ◽  
The Difference ◽  
Public Banks

The aim of this work is to assess systemic risk of Tunisian listed banks. The goal is to identify the institutions that contribute the most to systemic risk and that are most exposed to it. We use the CoVaR that considered the systemic risk as the value at risk (VaR) of a financial institution conditioned on the VaR of another institution. Thus, if the CoVaR increases with respect to the VaR, the spillover risk also increases among the institutions. The difference between these measurements is termed △CoVaR, and it allows for estimating the exposure and contribution of each bank to systemic risk. Results allow classifying Tunisian banks in terms of systemic risk involvement. They show that public banks occupy the top places, followed by the two largest private banks in Tunisia. These five banks are the main systemic players in the Tunisian banking sector. It seems that they are the least sensitive to the financial difficulties of existing banks and the most important contributors to the distress of the other banks. This work aims to add a broader perspective to the micro prudential application of regulation, including contagion, proposing a macro prudential vision and strengthening of regulatory policy. Supervisors could impose close supervision for institutions considered as potentially systemic banks. Furthermore, regulations should consider the systemic contribution when defining risk requirements to minimize the consequences of possible herd behavior.

Systemic Risk-Driven Portfolio Selection

2022 ◽  
Author(s):  
Agostino Capponi ◽  
Alexey Rubtsov
Keyword(s):  
At Risk ◽  
Portfolio Selection ◽  
Systemic Risk ◽  
Value At Risk ◽  
Global Financial Crisis ◽  
Risk Measures ◽  
Conditional Value At Risk ◽  
The Face ◽  
Financial Index ◽  
The Global Financial Crisis

How can we construct portfolios that perform well in the face of systemic events? The global financial crisis of 2007–2008 and the coronavirus disease 2019 pandemic have highlighted the importance of accounting for extreme form of risks. In “Systemic Risk-Driven Portfolio Selection,” Capponi and Rubtsov investigate the design of portfolios that trade off tail risk and expected growth of the investment. The authors show how two well-known risk measures, the value-at-risk and the conditional value-at-risk, can be used to construct portfolios that perform well in the face of systemic events. The paper uses U.S. stock data from the S&P500 Financials Index and Canadian stock data from the S&P/TSX Capped Financial Index, and it demonstrates that portfolios accounting for systemic risk attain higher risk-adjusted expected returns, compared with well-known benchmark portfolio criteria, during times of market downturn.

scholarly journals What Kind Of Systemic Risks Do We Face In The European Banking Sector? The Approach Of CoVaR Measure

2014 ◽  
Vol 14 (2) ◽  
pp. 114-124 ◽  
Author(s):  
Renata Karkowska
Keyword(s):  
Financial Institutions ◽  
Systemic Risk ◽  
Value At Risk ◽  
Banking Sector ◽  
Significant Risk ◽  
Conditional Value At Risk ◽  
The Public ◽  
Public Market ◽  
Systemic Risks ◽  
European Banking

Abstract We measure a systemic risk faced by European banking sectors using the CoVaR measure. We propose the conditional value-at-risk for measuring a spillover risk which demonstrates the bilateral relation between the tail risks of two financial institutions. The aim of the study is to estimate the contribution systemic risk of the bank i in the analyzed banking sector of a country in conditions of its insolvency. The study included commercial banks from 8 emerging markets from Europe, which gave a total of 40 banks, traded on the public market, which provided a market valuation of the bank’s capital. The conclusions are that the CoVaR seems to be a better measure for systemic risk in the banking sector than the VaR, which is more individual. And banks in developing countries in Europe do not provide significant risk for the banking sector as a whole. But it must be taken into account that some individuals that may find objectionable. Our results hence tend to a practical use of the CoVaR for supervisory purposes.

scholarly journals Early warning of systemic risk in global banking: eigen-pair R number for financial contagion and market price-based methods

2021 ◽  
Author(s):  
Sheri Markose ◽  
Simone Giansante ◽  
Nicolas A. Eterovic ◽  
Mateusz Gatkowski
Keyword(s):  
Early Warning ◽  
Systemic Risk ◽  
Value At Risk ◽  
Risk Measures ◽  
Market Price ◽  
System Stability ◽  
Conditional Value At Risk ◽  
Centrality Measures ◽  
Global Banking ◽  
Pair Method

AbstractWe analyse systemic risk in the core global banking system using a new network-based spectral eigen-pair method, which treats network failure as a dynamical system stability problem. This is compared with market price-based Systemic Risk Indexes, viz. Marginal Expected Shortfall, Delta Conditional Value-at-Risk, and Conditional Capital Shortfall Measure of Systemic Risk in a cross-border setting. Unlike paradoxical market price based risk measures, which underestimate risk during periods of asset price booms, the eigen-pair method based on bilateral balance sheet data gives early-warning of instability in terms of the tipping point that is analogous to the R number in epidemic models. For this regulatory capital thresholds are used. Furthermore, network centrality measures identify systemically important and vulnerable banking systems. Market price-based SRIs are contemporaneous with the crisis and they are found to covary with risk measures like VaR and betas.

scholarly journals MENGUKUR RISIKO SISTEMIK DAN KETERKAITAN FINANSIAL PERBANKAN DI INDONESIA

2014 ◽  
Vol 16 (2) ◽  
pp. 103-125 ◽  
Author(s):  
Sri Ayomi ◽  
Bambang Hermanto
Keyword(s):  
At Risk ◽  
Systemic Risk ◽  
Value At Risk ◽  
Jel Classification ◽  
Conditional Value At Risk ◽  
Probability Of Default ◽  
Insolvency Risk ◽  
Merton Model ◽  
Risk Probability

This paper measures the insolvency risk of bank in Indonesia. We apply Merton model to identify the probability of defaul tover 30 banks during the period of 2002-2013. This paper also identify role of financial linkage a cross banks on transmitting from one bank to another; which enable us to assess if the risk is systemic or not. The results showed the larger total asset of the bank, the larger they contribute to systemic risk. Keywords : Conditional Value at Risk; Probability of Default; systemic risk and financial linkages;Value at Risk. JEL Classification: D81, G21, G33

scholarly journals Systemic Risk Contribution and Contagion of Industrial Sectors in China: From the Global Financial Crisis to the COVID-19 Pandemic

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jianxu Liu ◽  
Yangnan Cheng ◽  
Yefan Zhou ◽  
Xiaoqing Li ◽  
Hongyu Kang ◽  
...  
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Systemic Risk ◽  
Banking Sector ◽  
Global Financial Crisis ◽  
Spillover Effect ◽  
Industrial Sectors ◽  
Risk Contribution ◽  
The Global Financial Crisis ◽  
Over Time

This paper investigates the risk contribution of 29 industrial sectors to the China stock market by using one-factor with Durante generator copulas (FDG) and component expected shortfall (CES) analyses. Risk contagion between the systemically most important sector and other sectors is examined using a copula-based ∆CoVaR approach. The data cover the 2008 global financial crisis and the beginning of the COVID-19 pandemic. The empirical results show that the banking sector contributed most to systemic risk before and during the global financial crisis. Nonbank finance became equally important in 2020, and the COVID-19 pandemic promoted the position of the computer and pharmaceuticals sectors. The spillover effect diminishes over time, but there remains risk contagion between sectors. The risk spillover trend is consistent with that of systemic risk.

Cost efficiency analysis of scheduled commercial banks: empirical evidence from India

2018 ◽  
Vol 37 (7) ◽  
pp. 586-602
Author(s):  
Aparna Bhatia ◽  
Megha Mahendru
Keyword(s):  
Cost Efficiency ◽  
Commercial Banks ◽  
Banking Sector ◽  
Global Financial Crisis ◽  
Allocative Efficiency ◽  
Specific Reference ◽  
Tobit Regression ◽  
Content Type ◽  
Cost Inefficiency ◽  
Indian Banks

Purpose The purpose of this paper is to analyze and evaluate cost efficiency (CE) scores of Indian Scheduled Commercial Banks (SCBs) in India over a period of 22 years, i.e. 1991–1992 to 2012–2013. Design/methodology/approach Data envelopment analysis (DEA) – a non-parametric approach is used to calculate efficiency scores of banks. Further the efficiency scores are decomposed into technical and allocative efficiency. The differences in the efficiency scores across ownership as well as across reformatory and post-reformatory era are examined by applying Panel Tobit Regression. Findings The paper also identifies the reason for cost inefficiency among Indian banks. In addition, the nature of their return to scale of all SCBs has also been evaluated. The results of the paper depict that Indian SCBs have never achieved full CE score of 1 in any of the years of study. The dominant reason identified behind cost inefficiency is allocative inefficiency. Surprisingly, the results also highlight that SCBs exhibit higher CE scores in reformatory era as compared to the post-reformatory era. Originality/value With specific reference to India, even lesser literature is found on CE. Indian banking sector has witnessed many changes on account of liberalization, privatization and globalization (LPG). Before banks adapted to the new environment, the global financial crisis acted as a fuel to fire affecting the performance of banks. Thus, a reassessment over a longer period would help to know a wholistic view of the issue of cost inefficiency, which has always been a troubling factor for Indian banks.

Lehren aus der Krise – Notwendige Änderungen der Finanzmarktregeln und zur Begrenzung systemischer Risiken

2009 ◽  
Vol 58 (3) ◽  
Author(s):  
Otmar Issing ◽  
Stephany Griffith-Jones ◽  
Stefano Pagliari ◽  
Claudia M. Buch ◽  
Katja Neugebauer
Keyword(s):  
Financial Crisis ◽  
Systemic Risk ◽  
Financial Stability ◽  
Market Failure ◽  
Banking Sector ◽  
Global Financial Crisis ◽  
Systemic Risks ◽  
State And Market ◽  
Bank For International Settlements ◽  
The International Monetary Fund

AbstractThe latest financial crisis has been caused by a mixture of state and market failure, argues Otmar Issing. To avoid future crises, more transparency is needed - not by gathering more information, but by gathering it systematically and thereby creating “intelligent transparency”. Furthermore, regulation has to be global, he states. The necessary institutions are in place: The International Monetary Fund, the Financial Stability Board and the Bank for International Settlements.Stephany Griffith-Jones and Stefano Pagliari point out, that containing “systemic risk” is one of the most important rationales for regulating financial markets. Our understanding of the sources of systemic risk has repeatedly been challenged by major episodes of financial instability. The crisis that started in the summer of 2007 has been no exception. They discuss how the latest global financial crisis urges analysts and regulators to rethink the origin of systemic risk beyond a narrow focus on the banking sector, beyond the “too big to fail problem”, and beyond a narrow micro-prudential focus. They focus on two regulatory principles: comprehensiveness and countercyclicality.Claudia Buch und Katja Neugebauer review the existing empirical evidence on whether the increase in cross-border activities has allowed banks to diversify risks and to what extent it has increased banks’ exposure to systemic risks.

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