Project Portfolio Selection of Solar Energy by Photovoltaic Generation Using Gini-CAPM Multi-Criteria and Considering ROI Covariations

José Claudio Isaias, Pedro Paulo Balestrassi, Guilherme Augusto Barucke Marcondes, Wesley Vieira da Silva, Carlos Henrique Pereira Mello and Claudimar Pereira da Veiga
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José Claudio Isaias: Institute of Industrial Engineering and Management, Federal University of Itajubá, Itajubá 37500-903, Brazil
Pedro Paulo Balestrassi: Institute of Industrial Engineering and Management, Federal University of Itajubá, Itajubá 37500-903, Brazil
Guilherme Augusto Barucke Marcondes: Department of Computer Science, National Institute of Telecommunications, Santa Rita do Sapucaí 37504-000, Brazil
Wesley Vieira da Silva: Faculty of Economics, Administration and Accounting, Federal University of Alagoas, Maceió 57072-970, Brazil
Carlos Henrique Pereira Mello: Institute of Industrial Engineering and Management, Federal University of Itajubá, Itajubá 37500-903, Brazil
Claudimar Pereira da Veiga: Department of General and Applied Administration, Federal University of Parana, Curitiba 80210-170, Brazil

Energies, 2021, vol. 14, issue 24, 1-21

Abstract: For some time, renewable solar energy generations using cellular photovoltaic panels have stood out among the options, especially in the segment of micro and small companies, where the return on investment is usually higher. In this context, when micro and small companies do not have the capital for the enterprises, several others, mainly small ones, have emerged to finance. However, significant difficulties occur for financiers in selecting investment portfolios, especially when considering the trade-off between return and risk and the covariations of return on investment, which are very common. In this type of selection, the Capital Asset Pricing Model criteria using the Gini risk can help significantly because this one is a more robust risk coefficient for assessments of non-normal probability distributions. However, searches for methods that meet the selection needs using the adjacent criteria are unsuccessful. Thus, this work seeks to help minimize the gap by presenting a new method for selection using the criteria. Historical and simulations data stochastic evaluations indicate that the portfolios selected by the method are attractive options for implementations. These portfolios have reasonable probabilistic expectations and satisfactory protection to avoid mistakes caused for not considering covariations in return on investment, which indicates a significant advance on the current knowledge frontier and will likely allow the increased use of the concept. The method also presents theoretical contributions in adaptations of the benchmark models, which help to minimize the adjacent literary gap of similar methods.

Keywords: project portfolios selection; trade-off between Gini risk and return considering covariations; renewable energy sources; photovoltaic solar energy microgeneration; financial feasibility; social welfare (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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