Stochastic evaluation of robust portfolios based on hierarchical clustering and worst-case scenarios

• Published in: Acta scientiarum. Technology Vol. 39; no. 5; p. 623
• Main Authors: Rotela Junior, Paulo, Rocha, Luiz Célio Souza, Aquila, Giancarlo, Pamplona, Edson De Oliveira, Balestrassi, Pedro Paulo, Paiva, Anderson Paulo de
• Format: Journal Article
• Language: English
• Published: Maringa Editora da Universidade Estadual de Maringá - EDUEM 01.01.2017
• Subjects: Cluster analysis; Clustering; Data envelopment analysis; Markets; Operations research; Robustness; Stock exchanges
• ISSN: 1806-2563; 1807-8664; 1806-2563
• DOI: 10.4025/actascitechnol.v39i5.30502

The objective of this paper is to present a proposal to form robust portfolios using a stochastic efficiency analysis of assets from companies in the Sao Paulo Stock Exchange, focusing on the worst market state. In order to do this, information about the market in all of its phases and information from low market periods were employed in a stochastic efficiency analysis using the Chance Constrained Data Envelopment Analysis method, along with a Hierarchical Clustering approach. Then, the portfolios underwent a capital allocation model to obtain the ideal participation of each share. The portfolios formed in both scenarios were analyzed and compared. The joint application of the approaches supplied with information about the worst market state was able to form robust portfolios that lead to a higher accumulated return in the validation period than portfolios optimized from information about the entire period, and still resulted in portfolios with smaller beta values.