Conditional Value-at-Risk Constrained Optimization of a Power Portfolio Published in International Journal of Applied Decision Sciences • A predictive and risk analytics tool guiding cash management of warranty reserves, covering contingent liabilities. • Finding a balance between excess reserves causing opportunity cost, and not enough reserves necessitating emergency funds. • The decision mak...

The concept of Conditional Value-at-Risk (CVaR) is used in various applications in uncertain environment. This paper introduces CVaR norm for a random variable, which is by de nition CVaR of absolute value of this random variable. It is proved that CVaR norm is indeed a norm in the space of random variables. CVaR norm is de ned in two variations: scaled and non-scaled. L-1 and L-in nity norms a...

We examine the stability of a portfolio management model based on the conditional valueat-risk (CVaR) measure; the model controls risk exposure of international investment portfolios. We use a moment-matching method to generate discrete distributions (scenario sets) of asset returns and exchange rates so that their statistical properties match corresponding values estimated from historical data...

Based on the method of copulas, we construct a parametric family of multivariate distributions using mixtures of independent conditional distributions. The new family of multivariate copulas is a convex combination of products of independent and comonotone subcopulas. It fulfills the four most desirable properties that a multivariate statistical model should satisfy. In particular, the bivariat...

In ‎the ‎portfolio ‎optimization, ‎the ‎goal ‎is ‎to ‎distribute ‎the ‎ fixed capital ‎on a‎ ‎set ‎of‎investment ‎opportunities ‎to ‎maximize ‎return ‎while ‎managing ‎risk. ‎Risk ‎and ‎return ‎are ‎quantiti es ‎that ‎are ‎used ‎as ‎input ‎paramete‎rs ‎for ‎the ‎optimal ‎allocation ‎of ‎the ‎capital ‎in ‎the ‎suggested ‎models. ‎ But ‎these ‎quantities ‎are ‎not ‎known ‎at ‎the ‎time ‎of ‎the ‎...

Recognizing the drawbacks of Value-at-Risk (VaR), researchers have advocated the use of Conditional Value-at-Risk (CVaR). However, the current popularity of VaR and Stress Testing (ST) among bank regulators raises the question of whether a risk management system based on both VaR and ST constraints is an effective alternative to a system based on CVaR. We show that when the VaR and ST bounds ar...

We study the discrete optimization problem under the distributionally robustframework. We optimize the Entropic Value-at-Risk, which is a coherentrisk measure and is also known as Bernstein approximation for the chanceconstraint. We propose an efficient approximation algorithm to resolve theproblem via solving a sequence of nominal problems. The computationalresults show...

Financial returns exhibit stylized facts such as leptokurtosis, skewness and heavy-tailness. Regarding this behavior, in this paper, we apply multivariate generalized hyperbolic (mGH) distribution for portfolio modeling and performance evaluation, using conditional value at risk (CVaR) as a risk measure and allocating best weights for portfolio selection. Moreover, a robust portfolio optimizati...

the purpose of this study is estimation of daily value at risk (var) for total index of tehran stock exchange using parametric, nonparametric and semi-parametric approaches. conditional and unconditional coverage backtesting are used for evaluating the accuracy of calculated var and also to compare the performance of mentioned approaches. in most cases, based on backtesting statistics results, ...