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Distributionally robust reinsurance with Value-at-Risk and Conditional Value-at-Risk
Insurance: Mathematics and Economics, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liu, Haiyan, Mao, Tiantian
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The Journal of Derivatives, 1997 In the wake of recent failures of risk management, there has been a widespread call for improved quantification of the financial risks facing firms. At the forefront of this clamor has been Value at Risk. Previous research has identified differences in models, or Model Risk, as an important impediment to developing a Value at Risk standard. By contrast,
Christopher Marshall, Michael Siegel
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SSRN Electronic Journal, 1999
Abstract Value-at-risk methods which employ a linear (“delta only”) approximation to the relation between instrument values and the underlying risk factors are unlikely to be robust when applied to portfolios containing non-linear contracts such as options.
Britten-Jones, Mark +1 more
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Abstract Value-at-risk methods which employ a linear (“delta only”) approximation to the relation between instrument values and the underlying risk factors are unlikely to be robust when applied to portfolios containing non-linear contracts such as options.
Britten-Jones, Mark +1 more
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Integrated Risk Management for Newsvendors with Value-at-Risk Constraints
Manufacturing & Service Operations Management, 2019We study a newsvendor problem with profit risk control using value-at-risk (VaR) constraints. When a firm’s demand correlates with the price of a tradable financial asset, both financial tools (der...
P. Kouvelis, Rong Li
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The Management Accountant Journal, 2022
This article attempts to outline the conceptual under pinning, uses, advantages and limitations of “Value At Riskâ€, a popular risk metric, being used by banks and other financial institutions as a tool for risk management.
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This article attempts to outline the conceptual under pinning, uses, advantages and limitations of “Value At Riskâ€, a popular risk metric, being used by banks and other financial institutions as a tool for risk management.
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Generalized value at risk forecasting
Communications in Statistics - Theory and Methods, 2018In this paper, using estimating function approach, a new optimal volatility estimator is introduced and based on the recursive form of the estimator a data-driven generalized EWMA model for value at risk (VaR) forecast is proposed.
A. Thavaneswaran, Alex Paseka, J. Frank
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Financial Analysts Journal, 2000
This article is a self-contained introduction to the concept and methodology of value at risk (VAR), a recently developed tool for measuring an entity's exposure to market risk. We explain the concept of VAR and then describe in detail the three methods for computing it—historical simulation, the delta-normal method, and Monte Carlo simulation. We also
Thomas J. Linsmeier, Neil D. Pearson
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This article is a self-contained introduction to the concept and methodology of value at risk (VAR), a recently developed tool for measuring an entity's exposure to market risk. We explain the concept of VAR and then describe in detail the three methods for computing it—historical simulation, the delta-normal method, and Monte Carlo simulation. We also
Thomas J. Linsmeier, Neil D. Pearson
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PRINCIPAL COMPONENT VALUE AT RISK
International Journal of Theoretical and Applied Finance, 2000Value at risk (VaR) is an industrial standard for monitoring financial risk in an investment portfolio. It measures potential losses within a given confidence interval. The implementation, calculation, and interpretation of VaR contains a wealth of mathematical issues that are not fully understood.
Brummelhuis, R. +3 more
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2004
The capital requirement from financial institutions is based on the amount of risk carried in their portfolios.
Jürgen Franke +2 more
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The capital requirement from financial institutions is based on the amount of risk carried in their portfolios.
Jürgen Franke +2 more
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Expected Shortfall is jointly elicitable with Value at Risk - Implications for backtesting
, 2015In this note, we comment on the relevance of elicitability for backtesting risk measure estimates. In particular, we propose the use of Diebold-Mariano tests, and show how they can be implemented for Expected Shortfall (ES), based on the recent result of
Tobias Fissler, J. Ziegel, T. Gneiting
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