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generation under consideration of risk. We include a reserve market, a day-ahead market and an intraday market in stochastic … modeling and develop a multi-stage stochastic Mixed Integer Linear Program. We assess the profitability as well as the risk … exposure, quantified by the conditional value at risk metric, of trading strategies following different risk preferences. We …
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Adjustable Robust Optimization (ARO) yields, in general, better worst-case solutions than static Robust Optimization (RO). However, ARO is computationally more difficult than RO. In this paper, we derive conditions under which the worst-case objective values of ARO and RO problems are equal. We...
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Decision-makers who usually face model/parameter risk may prefer to act prudently by identifying optimal contracts that … solved. Numerical experiments are run for various risk preference choices and it is found that for relatively large sample … the modeler puts on the tail risk when defining its objective function. These findings suggest that one should be very …
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divided for an improvement in the worst-case objective value. Based on this theory, we propose several splitting heuristics …
Persistent link: https://www.econbiz.de/10013005868
We study upper and lower bounds on the expectile risk measure of risky portfolios when the joint distribution of the … improved bounds when the bivariate distributions of each of the risky components and a risk factor are known. When the factor …, the unconstrained dependence uncertainty spreads of Expected Shortfall, Value-at-Risk and the expectile are compared …
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