Banks’ Non-Interest Income and Systemic Risk

Banks' Non-Interest Income and Systemic Risk

SSRN Electronic Journal ◽

10.2139/ssrn.3328890 ◽

2019 ◽

Cited By ~ 15

Author(s):

Markus Konrad Brunnermeier ◽

Gang Nathan Dong ◽

Darius Palia

Keyword(s):

Systemic Risk ◽

Interest Income

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Banks’ Noninterest Income and Systemic Risk

The Review of Corporate Finance Studies ◽

10.1093/rcfs/cfaa006 ◽

2020 ◽

Cited By ~ 2

Author(s):

Markus K Brunnermeier ◽

Gang Nathan Dong ◽

Darius Palia

Keyword(s):

Economic Impact ◽

Systemic Risk ◽

Tail Risk ◽

Interest Income ◽

Editorial Decision ◽

Three Components

Abstract This paper finds noninterest income is positively correlated with the total systemic risk for U.S. banks. Decomposing total systemic risk into three components, we find that noninterest income is positively related to a bank’s tail risk, positively related to a bank’s interconnectedness risk, and an insignificantly related to a bank’s exposure to macroeconomic and finance factors. We also find that noninterest income is more volatile and negatively related to interest income. Finally, we find trading and other noninterest income to be positively correlated with systemic risk. Other noninterest income, compared with trading income, has a slightly larger economic impact. (JEL G01, G18, G20, G21, G32, G38) Received October 31, 2019; editorial decision February 3, 2020 by Editor Andrew Ellul.

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What Factors Drive the Banks Systemic Risk among South Asian Countries

Journal of Accounting and Finance in Emerging Economies ◽

10.26710/jafee.v7i4.2007 ◽

2021 ◽

Vol 7 (4) ◽

Author(s):

Raheel Mumtaz ◽

Quaisar Ijaz Khan ◽

M.Farooq Rehan

Keyword(s):

South Asian ◽

Systemic Risk ◽

Panel Data Analysis ◽

Banking System ◽

Annual Reports ◽

Asian Countries ◽

Leverage Ratio ◽

Interest Income ◽

Income Ratio ◽

Risk Contribution

Purpose: This study designs to examine the determinants (size, liquidity ratio, leverage ratio, deposit ratio, asset growth, net interest income ratio and return on asset ratio) of bank’s systemic risk. We use the data of listed commercial banks of the South Asian countries (Pakistan, Bangladesh, and India). Design/Methodology/Approach: The sample consists 30 banks from Bangladesh, 87 banks from India and 22 banks from Pakistan. This study covers the period from 2006 to 2018. The data is collected from the published annual reports of banks and stock exchanges of respective country. The panel data analysis is performed for the estimation of research models. Findings: The findings demonstrate that larger banks contribute lower in the systemic risk of banks. Additionally, highly liquid banks enhance the systemic risk of the banking system. Moreover, the banks with greater reliance on the deposits, net interest income and with high return on asset reduce the systemic risk contribution of the banks. Implications/Originality/Value: This study provides the justification to devise the banking policies like enhance the proportion of liquidity among assets, reliance on net interest income and promote the financing needs through deposits to limit the systemic risk contribution of the banking system.

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Determinants of Systemic Risk of Banks in India

Asian Journal of Finance & Accounting ◽

10.5296/ajfa.v11i1.14157 ◽

2019 ◽

Vol 11 (1) ◽

pp. 272

Author(s):

Mihir Dash

Keyword(s):

Public Sector ◽

Private Sector ◽

Systemic Risk ◽

Fixed Effects ◽

Capital Adequacy ◽

Return On Assets ◽

Book Value ◽

Public Sector Banks ◽

Interest Income ◽

Systemic Impact

This study examines the determinants of systemic risk for banks in India. The independent variables considered for the study include the sector, bank size, return on assets, beta, leverage, capital adequacy, non-performing assets, price to book value, deposits, loans & advances, investments, net interest income, and non-interest income. A mixed panel regression model was applied, with bank fixed effects and year random effects.The results of the study indicate that public sector banks have a much higher level of systemic impact than private sector banks. Further, the determinants of systemic impact are different for public sector and private sector banks. The systemic impact of public sector banks was positively related with size and negatively related with price to book value ratio and investments to total assets ratio, while the systemic impact of private sector banks was negatively related with return on assets and positively related with beta and net interest income to total funds ratio.

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Macroprudential Policy Instruments of Central Banks

Voprosy Ekonomiki ◽

10.32609/0042-8736-2012-8-32-47 ◽

2012 ◽

pp. 32-47

Author(s):

S. Andryushin ◽

V. Kuznetsova

Keyword(s):

Systemic Risk ◽

Financial Stability ◽

Financial System ◽

Policy Instruments ◽

Central Banks ◽

Macroprudential Policy ◽

Policy Studies ◽

The Future ◽

Financial Cycles

The paper analyzes central banks macroprudencial policy and its instruments. The issues of their classification, option, design and adjustment are connected with financial stability of overall financial system and its specific institutions. The macroprudencial instruments effectiveness is evaluated from the two points: how they mitigate temporal and intersectoral systemic risk development (market, credit, and operational). The future macroprudentional policy studies directions are noted to identify the instruments, which can be used to limit the financial systemdevelopment procyclicality, mitigate the credit and financial cycles volatility.

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Risk Factors of Collateralized Loan Obligations and Corporate Bonds

Zeitschrift für Bankrecht und Bankwirtschaft ◽

10.15375/zbb-2020-0604 ◽

2020 ◽

Vol 32 (6) ◽

pp. 347-355

Author(s):

Mark Wahrenburg ◽

Andreas Barth ◽

Mohammad Izadi ◽

Anas Rahhal

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Asset Pricing ◽

Systemic Risk ◽

Corporate Bonds ◽

Risk Exposure ◽

Expected Returns ◽

Yield Spreads ◽

Pricing Factors ◽

Return Difference

AbstractStructured products like collateralized loan obligations (CLOs) tend to offer significantly higher yield spreads than corporate bonds (CBs) with the same rating. At the same time, empirical evidence does not indicate that this higher yield is reduced by higher default losses of CLOs. The evidence thus suggests that CLOs offer higher expected returns compared to CB with similar credit risk. This study aims to analyze whether this return difference is captured by asset pricing factors. We show that market risk is the predominant risk factor for both CBs and CLOs. CLO investors, however, additionally demand a premium for their risk exposure towards systemic risk. This premium is inversely related to the rating class of the CLO.

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