The trade-off frontier for ESG and Sharpe ratio: a bootstrapped double-frontier data envelopment analysis

Boubaker, Sabri; Le, Tu; Manita, Riadh; Ngo, Thanh Duc

doi:10.1007/s10479-023-05506-z

Cited by 6 publications

(1 citation statement)

References 109 publications

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“…Some of these attributes may include profitability, liquidity, systematic and non-systematic risks, financial ratios, market ratios, non-financial attributes (e.g. ethical, environmental, and social issues), skewness, and kurtosis, to name but a few (Aouni et al, 2018;Ballestero et al, 2012;Boubaker et al, 2023;Colapinto et al, 2019;Doumpos & Zopounidis, 2014;Peykani et al, 2020;Rahiminezhad Galankashi et al, 2020;Steuer et al, 2007;Wu et al, 2022;Yu & Lee, 2011).…”

Section: Introductionmentioning

confidence: 99%

Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA

Mohseny-Tonekabony,

Sadjadi,

Mohammadi

et al. 2024

Ann Oper Res

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This study presents a two-phase approach of Data Envelopment Analysis (DEA) and Goal Programming (GP) for portfolio selection, representing a pioneering attempt at combining these techniques within the context of portfolio selection. The approach expands on the conventional risk and return framework by incorporating additional financial factors and addressing data uncertainty, which allows for a thorough examination of portfolio outcomes while accommodating investor preferences and conservatism levels. The initial phase employs a super-efficiency DEA model to streamline asset selection by identifying suitable investment candidates based on efficiency scores, setting the stage for subsequent portfolio optimization. The second phase leverages the Extended GP (EGP) framework, which facilitates the comprehensive incorporation of investor preferences to determine the optimal weights of the efficient assets previously identified within the portfolio. Each goal is tailored to reflect specific financial factors spanning both technical and fundamental aspects. To tackle data uncertainty, robust optimization is applied. The research contributes to the robust GP (RGP) literature by analyzing new RGP variants, overcoming limitations of traditional and other uncertain GP models by incorporating uncertainty sets. Robust counterparts of the EGP models are accordingly developed using polyhedral and combined interval and polyhedral uncertainty sets, providing a flexible representation of uncertainty in financial markets. Empirical results, based on real data from the Tehran Stock Exchange comprising 779 assets, demonstrate the superiority of the proposed approach over traditional portfolio selection methods across various uncertainty settings. Additionally, a comprehensive sensitivity analysis investigates the impact of uncertainty levels on the robust EGP models. The proposed framework offers guidance to investors and fund managers through a pragmatic approach, enabling informed and robust portfolio decisions by considering efficiency, uncertainty, and extended financial factors.

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Section: Introductionmentioning

confidence: 99%

Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA

Mohseny-Tonekabony,

Sadjadi,

Mohammadi

et al. 2024

Ann Oper Res

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Short- and long-run cross-border European sustainability interdependences

Yfanti,

Karanasos,

et al. 2024

Ann Oper Res

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The increasing interest in climate change risks, environmental degradation, corporate social responsibility, and environmental, social, governance principles has motivated the recent soaring focus of policymakers, market practitioners, and academics on sustainable investments. In this vein, we investigate the cross-country interconnectedness among sustainability equity indices. Using a bivariate Dynamic Conditional Correlations-Mixed Data Sampling (DCC-MIDAS) specification, we study the short- and long-run time-varying dependence dynamics between European and five international (Australia, Brazil, Japan, US, and Canada) sustainability benchmarks. Our cross-country dynamic correlation analysis identifies the interdependence types and hedging characteristics in the short- and long-run across the business cycle. The significant macro- and crisis-sensitivity of the sustainability correlation pattern unveils strong countercyclical cross-country sustainability interlinkages for most index pairs and crisis periods. We further reveal the high- and low-frequency contagion transmitters or interdependence drivers in the macro environment during the 2008 global financial turmoil, the European sovereign debt crisis, and the recent pandemic-induced crash. Finally, we demonstrate that climate change risks and policy considerations are potent catalysts for both countercyclical and procyclical cross-border sustainability spillovers.

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