VaR minimization is a complex problem playing a critical role in many actuarial and financial applications of mathematical programming. The usual methods of convex programming do not apply due to the lack of sub-additivity. The usual methods of differentiable programming do not apply either, due to the lack of continuity. Taking into account that the CVaR may be given as an integral of VaR, one has that VaR becomes a first order mathematical derivative of CVaR. This property will enable us to give accurate approximations in VaR optimization, since the optimization VaR and CVaR will become quite closely related topics. Applications in both finance and insurance will be given
This thesis presents the Conditional Value-at-Risk concept and combines an analysis that covers its ...
Value-at-Risk (VaR ) is an industrial standard for monitoring market risk in an investment portfo...
The paper discuss the sensitivity to the presence of outliers of the portfolio optimization procedur...
VaR minimization is a complex problem playing a critical role in many actuarial and financial appli...
The Value at Risk (VaR) is a very important risk measure for practitioners, supervisors and research...
Value at risk (VaR) and conditional value at risk (CVaR) are the most frequently used risk measures...
Risk measures are subject to many scientific papers and monographs published on financial portfolio ...
It is unrealistic to formulate the problems arising under uncertain environments as deterministic op...
Abstract. Value at risk (VaR) and conditional value at risk (CVaR) are the most frequently used risk...
LP computable risk measures can be solved using LP solver and become more popular recently. CVaR is ...
In times of great insecurity and turbulence on every major stock exchange, it is evident that contro...
Using the risk measure CV aR in �nancial analysis has become more and more popular recently. In thi...
Linearization of portfolio optimization plays a central role in financial studies, since linear prob...
We show how to reduce the problem of computing VaR and CVaR with Student T return distributions to e...
Conditional value at risk (CVaR) has been widely used as a risk measure in finance. When the confide...
This thesis presents the Conditional Value-at-Risk concept and combines an analysis that covers its ...
Value-at-Risk (VaR ) is an industrial standard for monitoring market risk in an investment portfo...
The paper discuss the sensitivity to the presence of outliers of the portfolio optimization procedur...
VaR minimization is a complex problem playing a critical role in many actuarial and financial appli...
The Value at Risk (VaR) is a very important risk measure for practitioners, supervisors and research...
Value at risk (VaR) and conditional value at risk (CVaR) are the most frequently used risk measures...
Risk measures are subject to many scientific papers and monographs published on financial portfolio ...
It is unrealistic to formulate the problems arising under uncertain environments as deterministic op...
Abstract. Value at risk (VaR) and conditional value at risk (CVaR) are the most frequently used risk...
LP computable risk measures can be solved using LP solver and become more popular recently. CVaR is ...
In times of great insecurity and turbulence on every major stock exchange, it is evident that contro...
Using the risk measure CV aR in �nancial analysis has become more and more popular recently. In thi...
Linearization of portfolio optimization plays a central role in financial studies, since linear prob...
We show how to reduce the problem of computing VaR and CVaR with Student T return distributions to e...
Conditional value at risk (CVaR) has been widely used as a risk measure in finance. When the confide...
This thesis presents the Conditional Value-at-Risk concept and combines an analysis that covers its ...
Value-at-Risk (VaR ) is an industrial standard for monitoring market risk in an investment portfo...
The paper discuss the sensitivity to the presence of outliers of the portfolio optimization procedur...