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Comparative Analyses of Expected Shortfall and VaR

Comparative Analyses of Expected Shortfall and VaR
Author: Yasuhiro Yamai
Publisher:
Total Pages: 56
Release: 2001
Genre: Financial futures
ISBN:

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Expected shortfall is compared with Value-at-Risk (VaR) in three aspects: estimation errors, decomposition into risk factors, and optimization. Advantages and disadvantages of expected shortfall over VaR are shown, and that expected shortfall is easily decomposed (needing a larger size of sample than VaR for the same level of accuracy) and optimized, while VaR is not.


On the Validity of Value-at-risk

On the Validity of Value-at-risk
Author: Yasuhiro Yamai
Publisher:
Total Pages: 46
Release: 2001
Genre: Investment analysis
ISBN:

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Probabilistic Constrained Optimization

Probabilistic Constrained Optimization
Author: Stanislav Uryasev
Publisher: Springer Science & Business Media
Total Pages: 319
Release: 2013-03-09
Genre: Mathematics
ISBN: 1475731507

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Probabilistic and percentile/quantile functions play an important role in several applications, such as finance (Value-at-Risk), nuclear safety, and the environment. Recently, significant advances have been made in sensitivity analysis and optimization of probabilistic functions, which is the basis for construction of new efficient approaches. This book presents the state of the art in the theory of optimization of probabilistic functions and several engineering and finance applications, including material flow systems, production planning, Value-at-Risk, asset and liability management, and optimal trading strategies for financial derivatives (options). Audience: The book is a valuable source of information for faculty, students, researchers, and practitioners in financial engineering, operation research, optimization, computer science, and related areas.


Systemic Contingent Claims Analysis

Systemic Contingent Claims Analysis
Author: Mr.Andreas A. Jobst
Publisher: International Monetary Fund
Total Pages: 93
Release: 2013-02-27
Genre: Business & Economics
ISBN: 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.