Quantification of Structural Liquidity Risk in Banks
Quantification of Structural Liquidity Risk in Banks

Author: Christoph Wieser

Publisher: Springer Nature

Published: 2022-10-20

Total Pages: 75

ISBN-13: 3658395931

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Structural liquidity risk is a material risk resulting from the core banking business of taking in short-term deposits and lending out long-term loans, thus allowing a maturity mismatch between assets and liabilities. At some point the long-term loans will require refinancing and the institution is at risk of an adverse development of refinancing costs.This book proposes a model for the quantification of structural liquidity risk and describes the underlying methodology and assumptions for stressing the refinancing costs. The change in present value between closing open liquidity positions under stressed refinancing costs compared to current costs is the calculated impact on risk-bearing capacity.

Systemic Contingent Claims Analysis
Systemic Contingent Claims Analysis

Author: Mr.Andreas A. Jobst

Publisher: International Monetary Fund

Published: 2013-02-27

Total Pages: 93

ISBN-13: 1475557531

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The recent global financial crisis has forced a re-examination of risk transmission in the financial sector and how it affects financial stability. Current macroprudential policy and surveillance (MPS) efforts are aimed establishing a regulatory framework that helps mitigate the risk from systemic linkages with a view towards enhancing the resilience of the financial sector. This paper presents a forward-looking framework ("Systemic CCA") to measure systemic solvency risk based on market-implied expected losses of financial institutions with practical applications for the financial sector risk management and the system-wide capital assessment in top-down stress testing. The suggested approach uses advanced contingent claims analysis (CCA) to generate aggregate estimates of the joint default risk of multiple institutions as a conditional tail expectation using multivariate extreme value theory (EVT). In addition, the framework also helps quantify the individual contributions to systemic risk and contingent liabilities of the financial sector during times of stress.

Measuring and Managing Liquidity Risk
Measuring and Managing Liquidity Risk

Author: Antonio Castagna

Publisher: John Wiley & Sons

Published: 2013-09-03

Total Pages: 600

ISBN-13: 1119990246

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A fully up-to-date, cutting-edge guide to the measurement and management of liquidity risk Written for front and middle office risk management and quantitative practitioners, this book provides the ground-level knowledge, tools, and techniques for effective liquidity risk management. Highly practical, though thoroughly grounded in theory, the book begins with the basics of liquidity risks and, using examples pulled from the recent financial crisis, how they manifest themselves in financial institutions. The book then goes on to look at tools which can be used to measure liquidity risk, discussing risk monitoring and the different models used, notably financial variables models, credit variables models, and behavioural variables models, and then at managing these risks. As well as looking at the tools necessary for effective measurement and management, the book also looks at and discusses current regulation and the implication of new Basel regulations on management procedures and tools.

Stress Testing and Risk Integration in Banks
Stress Testing and Risk Integration in Banks

Author: Tiziano Bellini

Publisher: Academic Press

Published: 2016-11-26

Total Pages: 318

ISBN-13: 0128036117

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Stress Testing and Risk Integration in Banks provides a comprehensive view of the risk management activity by means of the stress testing process. An introduction to multivariate time series modeling paves the way to scenario analysis in order to assess a bank resilience against adverse macroeconomic conditions. Assets and liabilities are jointly studied to highlight the key issues that a risk manager needs to face. A multi-national bank prototype is used all over the book for diving into market, credit, and operational stress testing. Interest rate, liquidity and other major risks are also studied together with the former to outline how to implement a fully integrated risk management toolkit. Examples, business cases, and exercises worked in Matlab and R facilitate readers to develop their own models and methodologies. - Provides a rigorous statistical framework for modeling stress test in line with U.S. Federal Reserve FRB CCAR (Comprehensive Capital Analysis Review), U.K. PRA (Prudential Regulatory Authority), EBA (European Baning Authorithy) and comply with Basel Accord requirements - Follows an integrated bottom-up approach central in the most advanced risk modelling practice - Provides numerous sample codes in Matlab and R

Analyzing Banking Risk
Analyzing Banking Risk

Author: Hennie van Greuning

Publisher: World Bank Publications

Published: 2009-03-31

Total Pages: 442

ISBN-13: 0821378988

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This book provides a comprehensive overview of topics focusing on assessment, analysis, and management of financial risks in banking. The publication emphasizes risk-management principles and stresses that key players in the corporate governance process are accountable for managing the different dimensions of financial risk. This third edition remains faithful to the objectives of the original publication. A significant new edition is the inclusion of chapters on the management of the treasury function. Advances made by the Basel Committee on Banking Supervision are reflected in the chapters on capital adequacy, transparency, and banking supervision. This publication should be of interest to a wide body of users of bank financial data. The target audience includes persons responsible for the analysis of banks and for the senior management or organizations directing their efforts.

Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance
Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

Author: El Bachir Boukherouaa

Publisher: International Monetary Fund

Published: 2021-10-22

Total Pages: 35

ISBN-13: 1589063953

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This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Financial Risk Management
Financial Risk Management

Author: José A. Soler Ramos

Publisher: IDB

Published: 2000

Total Pages: 422

ISBN-13: 9781886938717

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"Drawing on practical methods used by successful risk managers in emerging and developed markets throughout the world, the book provides specific guidance on establishing a modern risk management framework and developing efficient approaches to increase the profitability of risk management activities in emerging market settings."--BOOK JACKET.

A Primer on Managing Sovereign Debt-Portfolio Risks
A Primer on Managing Sovereign Debt-Portfolio Risks

Author: Thordur Jonasson

Publisher: International Monetary Fund

Published: 2018-04-06

Total Pages: 133

ISBN-13: 1484350545

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This paper provides an overview of sovereign debt portfolio risks and discusses various liability management operations (LMOs) and instruments used by public debt managers to mitigate these risks. Debt management strategies analyzed in the context of helping reach debt portfolio targets and attain desired portfolio structures. Also, the paper outlines how LMOs could be integrated into a debt management strategy and serve as policy tools to reduce potential debt portfolio vulnerabilities. Further, the paper presents operational issues faced by debt managers, including the need to develop a risk management framework, interactions of debt management with fiscal policy, monetary policy, and financial stability, as well as efficient government bond markets.