Bank Geographic Diversification and Systemic Risk

2019 ◽  
Vol 33 (10) ◽  
pp. 4811-4838 ◽  
Author(s):  
Yongqiang Chu ◽  
Saiying Deng ◽  
Cong Xia
Keyword(s):  
Systemic Risk ◽  
Value At Risk ◽  
Financial Integration ◽  
Causal Effect ◽  
Conditional Value At Risk ◽  
Geographic Diversification ◽  
Banking Deregulation ◽  
Exogenous Shocks ◽  
Interstate Banking ◽  
The Impact

Abstract Exploiting staggered interstate banking deregulation as exogenous shocks to bank geographic expansion, we examine the causal effect of geographic diversification on systemic risk. Using the gravity-deregulation approach, we find that bank geographic diversification leads to higher systemic risk measured by the change in conditional value at risk ($\Delta$CoVaR) and financial integration (Logistic($R^{2}))$. Furthermore, we document that geographic diversification affects systemic risk via its impact on asset similarity. The impact of geographic diversification on systemic risk is stronger in BHCs located in states comoving less with the U.S. aggregate economy.

Bank Geographic Diversification and Corporate Innovation: Evidence from the Lending Channel

2020 ◽  
pp. 1-32
Author(s):  
Saiying Deng ◽  
Connie X. Mao ◽  
Cong Xia
Keyword(s):  
Causal Effect ◽  
Economic Value ◽  
Operational Flexibility ◽  
Geographic Diversification ◽  
Banking Deregulation ◽  
Lending Channel ◽  
Interstate Banking ◽  
Model Following ◽  
Corporate Innovation ◽  
Underlying Mechanisms

By integrating staggered interstate banking deregulation into a gravity model following Goetz, Laeven, and Levine (2013), (2016), we construct a time-varying, bank-specific instrument for geographic diversification and investigate its causal effect on corporate innovation via the lending channel. We find that bank geographic diversification spurs corporate innovation and enhances the economic value of innovation. We identify relaxing debt covenants and alleviating borrowers’ financial constraints as the two underlying mechanisms explaining the documented effects. Moreover, by offering lenient covenants, geographically diversified banks provide greater financial and operational flexibility to borrowing firms, enabling them to engage in future mergers and acquisitions.

scholarly journals Impact of diversification on systemic risk of conventional banks listed on the Indonesia Stock Exchange

2020 ◽  
Vol 15 (4) ◽  
pp. 80-87
Author(s):  
Musa Fresno ◽  
Dewi Hanggraeni
Keyword(s):  
Systemic Risk ◽  
Value At Risk ◽  
Financial Stability ◽  
Stock Exchange ◽  
Conditional Value At Risk ◽  
Revenue Diversification ◽  
Variable Approach ◽  
Systemic Risks ◽  
Conventional Banks ◽  
The Impact

It is believed that bank diversification increases financial stability. However, several theories argue that diversification can trigger the spread of failure because of the increased interconnectivity between institutions. The aim of this study is to determine the impact of diversification on the systemic risk of banks. The sample of the study consists of 21 conventional banks listed on the Indonesia Stock Exchange from 2009 to 2018. The study uses firm-year fixed effect panel regression and an instrumental variable approach to examine how firm-specific variables determine the level of systemic risk. Diversification is measured by bank assets, funding, and revenue diversification. To measure the systemic risk, the Conditional Value-at-Risk (ΔCoVaR) methodology is applied. The results show that an increase in funding diversification leads to a decrease in ΔCoVaR, indicating that funding diversification exacerbates the level of systemic risk, whereas asset diversification and revenue diversification do not have significant effects on the level of systemic risk. The empirical findings suggest that the interconnectivity between banks should be reduced by limiting the diversification of funding in the banks to minimize their systemic risks.

scholarly journals How We Predict the Stability of Financial Sector: The Conditional Value at Risk Technique Approach

2020 ◽  
Author(s):  
David Kaluge
Keyword(s):  
At Risk ◽  
Systemic Risk ◽  
Value At Risk ◽  
Negative Impact ◽  
Stock Exchange ◽  
Banking System ◽  
Conditional Value At Risk ◽  
Negative Contribution ◽  
The Stability ◽  
The Impact

This study aims to identify the level of systemic risk of each bank and the financial linkages between banks in Indonesia. In this study, researcher uses 41 banks that have been actively traded on the Indonesia Stock Exchange in the period 2013-2018. The data of stock capitalization of banks are used as prices in a portfolio of banking system. The method used in this study is the CVaR (Conditional Value at Risk) method which was introduced by Adrian and Brunerrmeir in 2008. The equilibrium of the system is assumed reached at optimum portfolio of the system. At this situation each bank contribution to systemic risk is analyzed, as well as its impact onto it when there is a change in capitalization of a certain bank. The result shows the impact of bank onto systemic risk is not always follow its size in contribution the systemic risk. Due to covariance’s among banks are some positive and others are negative, some banks have negative contribution to systemic risk while others’ are positive. There are 4 banks that have different behavior. These banks have negative contribution to the systemic risk. These banks are BMRI, PNBN, PNBS and NAGA. The negative impact to systemic risk is dominated by BMRI as much as -0.17%, and by PNBN as much as -0.04%. There are 2 major banks that have contribution to systemic risk; BBCA (3,01% or Rp 59,1 trillion) and BBRI (0,54% Rp 10,62 trillion). However their impact on systemic risk are different. The parameters of impact on systemic for BBCA and BBRI are 14,99% and 52,94% respectively. Thus the stability of the system is more sensitive to the volatility of Bank Rakyat Indonesia (BBRI) than of Bank Central Asia (BBCA). Keywords: Systemic Risk, Financial Linkage, Value at Risk, Conditional Value at Risk, covariance banking

Shadow banking's effects in the Chilean financial system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Diana López Avilés ◽  
Paula Piñeira ◽  
Víctor Andrés Roco Cáceres ◽  
Felipe Vergara ◽  
Nicolas Araya
Keyword(s):  
Systemic Risk ◽  
Value At Risk ◽  
Financial Stability ◽  
Financial System ◽  
Conditional Value At Risk ◽  
Shadow Banking ◽  
Content Type ◽  
Relevant Effect ◽  
New Research ◽  
The Impact

PurposeThe Financial Stability Board (FSB) determined that entities classified as shadow banking are of a credit nature because they are capable of affecting the financial system through the entry and exit of capital. This study aims at measuring the impact of shadow banking in the systemic risk in Chile. A sample of 91 institutions (Run) belonging to the mutual funds was used, with a series showing a continuous behaviour between 2004 and 2018.Design/methodology/approachThe measurement is carried out using the conditional value at risk (CoVaR) methodology, which analyses the behaviour of an institution in a regular state against the same institution in a state of stress.FindingsThe results obtained reflect that liquidity mismatches do not have a relevant effect on the systemic risk, while the 2008 crisis does contribute to its decline.Originality/valueThere are less number of literature studies that apply statistical models regarding shadow banking, at least at a quantitative level, so this research is a beginning for other studies, supporting future authors in their new research as a basis.

Does securitization escalate banks’ sensitivity to systemic risk?

2020 ◽  
Vol 21 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Katerina Ivanov ◽  
Julia Jiang
Keyword(s):  
Systemic Risk ◽  
Value At Risk ◽  
Supply And Demand ◽  
Conditional Value At Risk ◽  
Empirical Literature ◽  
Content Type ◽  
Holding Companies ◽  
Residential Mortgage ◽  
The Us ◽  
The Impact

Purpose The purpose of this paper is to test empirically the impact of asset securitization and sale activities as well as the holdings of sub-prime related securitized products on the US bank holding companies’ (BHC) exposure to systemic risk. Design/methodology/approach This paper adopts a robust econometric method to estimate the conditional value-at-risk as a measure of BHCs' institutional sensitivity to market crushes. Using the data over the period of 2004-2016, the study also uses OLS with robust standard errors and panel estimation with random effects as two alternative estimation techniques to assess the impact of securitization activities on the sensitivity of BHCs to systemic risk. Findings Residential mortgage and other forms of securitization activities are positively related to an increase in the US BHCs' sensitivity to systemic distress. The significant cross effects of both securitized loans and holdings of securitized products play a crucial role in determining risks in financial sector. Originality/value This study contributes to the empirical literature on the effects of securitization on BHCs' risk exposures in several ways. First, the paper considers the complexity of the bank's risk profile; it focuses on BHCs' individual sensitivity to systemic distress and its dependence on the size of securitization and assets sold activities considering both supply and demand sides of securitization. Second, the time horizon under investigation sheds a light on the relationship between securitization and banks' risk exposures including the pre-crisis, crisis and post-crisis periods.

Proprietary information and the cost of bank debt

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
HyunJun Na
Keyword(s):  
Least Square ◽  
Bank Loan ◽  
Content Type ◽  
Loan Contracts ◽  
Proprietary Information ◽  
Banking Deregulation ◽  
Interstate Banking ◽  
Innovative Firms ◽  
Bank Loan Contracts ◽  
The Impact

PurposeThis study explores how the firm’s proprietary information has an impact on the bank loan contracts. It explains the propensity of using the competitive bid option (CBO) in the syndicate loans to solicit the best bid for innovative firms and how it changes based on industry competition and the degree of innovations. This research also examines how the interstate banking deregulation (Interstate Banking and Branching Efficiency Act) in 1994 affected the private loan contracts for innovative borrowers.Design/methodology/approachThe study uses various econometric analyses. First, it uses the propensity score matching analysis to see the impact of patents on pricing terms. Second, it uses the two-stage least square (2SLS) analysis by implementing the litigation and non-NYSE variables. Finally, it studies the impact of the policy change of the Interstate Banking and Branching Efficiency Act of 1994 on the bank loan contracts.FindingsFirms with more proprietary information pays more annual facility fees but less other fees. The patents are the primary determinants of the usage of CBO in the syndicate loans to solicit the best bid. While innovative firms can have better contract conditions by the CBO, firms with more proprietary information will less likely to use the CBO option to minimize the leakage of private information and the severe monitoring from the banks. Finally, more proprietary information lowered the loan spread for firms dependent on the external capital after the interstate banking deregulation.Originality/valueThe findings of this research will help senior executives with responsibility for financing their innovative projects. In addition, these findings should prove helpful for the lawmakers to boost economies.

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.

OPTIMAL REINSURANCE FROM THE VIEWPOINTS OF BOTH AN INSURER AND A REINSURER UNDER THE CVAR RISK MEASURE AND VAJDA CONDITION

2021 ◽  
pp. 1-29
Author(s):  
Yanhong Chen
Keyword(s):  
Loss Function ◽  
Value At Risk ◽  
Numerical Study ◽  
Risk Measure ◽  
Convex Combination ◽  
Weighting Factor ◽  
Loss Functions ◽  
Conditional Value At Risk ◽  
Optimal Reinsurance ◽  
The Impact

ABSTRACT In this paper, we study the optimal reinsurance contracts that minimize the convex combination of the Conditional Value-at-Risk (CVaR) of the insurer’s loss and the reinsurer’s loss over the class of ceded loss functions such that the retained loss function is increasing and the ceded loss function satisfies Vajda condition. Among a general class of reinsurance premium principles that satisfy the properties of risk loading and convex order preserving, the optimal solutions are obtained. Our results show that the optimal ceded loss functions are in the form of five interconnected segments for general reinsurance premium principles, and they can be further simplified to four interconnected segments if more properties are added to reinsurance premium principles. Finally, we derive optimal parameters for the expected value premium principle and give a numerical study to analyze the impact of the weighting factor on the optimal reinsurance.

ASSET CORRELATIONS IN TURBULENT MARKETS AND THE IMPACT OF DIFFERENT REGIMES ON ASSET MANAGEMENT

2011 ◽  
Vol 28 (01) ◽  
pp. 1-23 ◽  
Author(s):  
GERMAN BERNHART ◽  
STEPHAN HÖCHT ◽  
MICHAEL NEUGEBAUER ◽  
MICHAEL NEUMANN ◽  
RUDI ZAGST
Keyword(s):  
Risk Aversion ◽  
Asset Management ◽  
Value At Risk ◽  
Conditional Value At Risk ◽  
Dependence Structure ◽  
The Us ◽  
The Mean ◽  
Asian Market ◽  
Asset Classes ◽  
The Impact

In this article, the dependence structure of the asset classes stocks, government bonds, and corporate bonds in different market environments and its implications on asset management are investigated for the US, European, and Asian market. Asset returns are modelled by a Markov-switching model which allows for two market regimes with completely different risk-return structures. Using major stock indices from all three regions, calm and turbulent market periods are identified for the time period between 1987 and 2009 and the correlation structures in the respective periods are compared. It turns out that the correlations between as well as within the asset classes under investigation are far from being stable and vary significantly between calm and turbulent market periods as well as in time. It also turns out that the US and European markets are much more integrated than the Asian and US/European ones. Moreover, the Asian market features more and longer turbulence phases. Finally, the impact of these findings is examined in a portfolio optimization context. To accomplish this, a case study using the mean-variance and the mean-conditional-value-at-risk framework as well as two levels of risk aversion is conducted. The results show that an explicit consideration of different market conditions in the modelling framework yields better portfolio performance as well as lower portfolio risk compared to standard approaches. These findings hold true for all investigated optimization frameworks and risk-aversion levels.

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