Browsing by Subject "Conditional value-at-risk"

Now showing 1 - 3 of 3

Open Access
A risk-averse approach for the planning of a hybrid energy system with conventional hydropower
(Elsevier BV, 2021-02) Çavuş, Özlem; Kocaman, Ayşe Selin; Yılmaz, Özlem
We present a risk-averse two-stage stochastic programming model for the planning of a hybrid energy system with conventional hydropower component. Using Conditional Value-at-Risk as our measure of risk-aversion, we take into consideration the dispersion of the random total cost arising due to uncertain streamflow amount. We propose an exact solution approach based on scenario decomposition to solve our large scale problem. We then present a case study for the Mediterranean Region in Turkey and gen erate scenarios using a modified k-nearest neighbor algorithm for bootstrapping the historical time series data of Manavgat River. The results of our computational study show how an optimal solution differs based on the degree of risk-aversion and demonstrate the computational power of our solution approach. Our algorithm is able to solve instances that cannot be solved by CPLEX, furthermore, CPLEX requires 5.84 times more computation time than our algorithm.
Open Access
Robust portfolio choice with CVaR and VaR under distribution and mean return ambiguity
(Springer, 2014-01-09) Paç, A. B.; Pınar, M. Ç.
We consider the problem of optimal portfolio choice using the Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR) measures for a market consisting of n risky assets and a riskless asset and where short positions are allowed. When the distribution of returns of risky assets is unknown but the mean return vector and variance/covariance matrix of the risky assets are fixed, we derive the distributionally robust portfolio rules. Then, we address uncertainty (ambiguity) in the mean return vector in addition to distribution ambiguity, and derive the optimal portfolio rules when the uncertainty in the return vector is modeled via an ellipsoidal uncertainty set. In the presence of a riskless asset, the robust CVaR and VaR measures, coupled with a minimum mean return constraint, yield simple, mean-variance efficient optimal portfolio rules. In a market without the riskless asset, we obtain a closed-form portfolio rule that generalizes earlier results, without a minimum mean return restriction.
Open Access
Shelter site location under multi-hazard scenarios
(Elsevier, 2019) Özbay, Ekmel; Çavuş, Özlem; Kara, Bahar Y.
Natural disasters may happen successively in close proximity of each other. This study locates shelter sites and allocates the affected population to the established set of shelters in cases of secondary disaster(s) following the main earthquake, via a three-stage stochastic mixed-integer programming model. In each stage, before the uncertainty in that stage, that is the number of victims seeking a shelter, is resolved, shelters are established, and after the uncertainty is resolved, affected population is allocated to the established set of shelters. The assumption on nearest allocation of victims to the shelter sites implies that the allocation decisions are finalized immediately after the location decisions, hence both location and allocation decisions can be considered simultaneously. And, when victims are allocated to the nearest established shelter sites, the site capacities may be exceeded. To manage the risk inherit to the demand uncertainty and capacities, conditional value-at-risk is utilized in modeling the risk involved in allocating victims to the established shelter sites. Computational results on Istanbul dataset are presented to emphasize the necessity of considering secondary disaster(s), along with a heuristic solution methodology to improve the solution qualities and times.