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

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 portfol...

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Veröffentlicht in:Annals of operations research Jg. 313; H. 1; S. 341 - 366
Hauptverfasser: Henriques, Carla Oliveira, Neves, Maria Elisabete, Castelão, Licínio, Nguyen, Duc Khuong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.06.2022
Springer
Springer Nature B.V
Schlagworte:
Analysis
Business and Management
Combinatorics
Data envelopment analysis
Economic aspects
Energy industry
Exchange traded funds
Linear programming
Literature reviews
Mathematical programming
Methods
Multiple objective analysis
Natural gas industry
Nuclear energy
Nuclear reactors
Operations research
Operations Research/Decision Theory
Optimization
Original - OR Modeling/Case Study
Portfolio management
Theory of Computation
Portugal
Energy sector
DEA
ETF
Multi-objective portfolio models
ISSN:0254-5330, 1572-9338
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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 portfolios do not contain any ETFs related to the renewable energy sector; and (iii) natural gas and oil are the sectors that have the most ETFs represented in efficient portfolios.
AbstractList 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 portfolios do not contain any ETFs related to the renewable energy sector; and (iii) natural gas and oil are the sectors that have the most ETFs represented in efficient portfolios.
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 portfolios do not contain any ETFs related to the renewable energy sector; and (iii) natural gas and oil are the sectors that have the most ETFs represented in efficient portfolios. The online version contains supplementary material available at 10.1007/s10479-021-04323-6.
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 portfolios do not contain any ETFs related to the renewable energy sector; and (iii) natural gas and oil are the sectors that have the most ETFs represented in efficient portfolios.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 portfolios do not contain any ETFs related to the renewable energy sector; and (iii) natural gas and oil are the sectors that have the most ETFs represented in efficient portfolios.The online version contains supplementary material available at 10.1007/s10479-021-04323-6.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10479-021-04323-6.
Audience Academic
Author Henriques, Carla Oliveira
Castelão, Licínio
Neves, Maria Elisabete
Nguyen, Duc Khuong
Author_xml – sequence: 1
  givenname: Carla Oliveira
  orcidid: 0000-0003-4045-6101
  surname: Henriques
  fullname: Henriques, Carla Oliveira
  email: chenriques@iscac.pt
  organization: Polytechnic of Coimbra, Coimbra Business Research Centre|ISCAC, INESC Coimbra - DEEC, University of Coimbra, Faculty of Economics, CeBER, University of Coimbra
– sequence: 2
  givenname: Maria Elisabete
  orcidid: 0000-0002-6250-1113
  surname: Neves
  fullname: Neves, Maria Elisabete
  organization: Polytechnic of Coimbra, Coimbra Business Research Centre|ISCAC, University of Trás-Os-Montes and Alto Douro|CETRAD
– sequence: 3
  givenname: Licínio
  surname: Castelão
  fullname: Castelão, Licínio
  organization: Polytechnic of Coimbra, Coimbra Business Research Centre|ISCAC
– sequence: 4
  givenname: Duc Khuong
  orcidid: 0000-0002-7796-8787
  surname: Nguyen
  fullname: Nguyen, Duc Khuong
  organization: IPAG Business School, International School, Vietnam National University
BackLink https://www.ncbi.nlm.nih.gov/pubmed/35095151$$D View this record in MEDLINE/PubMed
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Issue 1
Keywords Energy sector
DEA
ETF
Multi-objective portfolio models
Language English
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Snippet This paper proposes a two-step approach to build portfolio models. The first step employs the Data Envelopment Analysis (DEA) to select assets attaining...
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StartPage 341
SubjectTerms Analysis
Business and Management
Combinatorics
Data envelopment analysis
Economic aspects
Energy industry
Exchange traded funds
Linear programming
Literature reviews
Mathematical programming
Methods
Multiple objective analysis
Natural gas industry
Nuclear energy
Nuclear reactors
Operations research
Operations Research/Decision Theory
Optimization
Original - OR Modeling/Case Study
Portfolio management
Theory of Computation
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Title Assessing the performance of exchange traded funds in the energy sector: a hybrid DEA multiobjective linear programming approach
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