Portfolio optimization using Mixture Design of Experiments: Scheduling trades within electricity markets

Francisco Alexandre de Oliveira, Anderson Paulo de Paiva, José Wanderley Marangon Lima, Pedro Paulo Balestrassi and Ronã Rinston Amaury Mendes

Energy Economics, 2011, vol. 33, issue 1, 24-32

Abstract: Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy.

Keywords: Mixture; Design; of; Experiments; Portfolio; optimization; CVaR; and; electricity; markets (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:33:y:2011:i:1:p:24-32

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