Assessing the performance of exchange traded funds in the energy sector: a hybrid DEA multiobjective linear programming approach.

ABSTRACT: This paper proposes a two-step approach to build portfolio models. The first step employs the Data Envelopment Analysis (DEA) to select assets attaining efficient financial performance according to a set of indicators used as inputs and outputs. The second step builds interval multiobjective portfolio models to obtain the optimal composition of efficient portfolios previously identified with respect to investor preferences. The usefulness of this proposed methodology is illustrated through a selected sample of diversified Exchange Traded Funds (ETFs) operating in the US energy sector. Our results with respect to all models and time horizons mainly show that: (i) ETFs related to nuclear energy are more often viewed as efficient according to all DEA models considered; (ii) the efficient port

SUBMITTER: Henriques CO 

PROVIDER: S-EPMC8783784 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature