Approximating exact expected utility via portfolio efficient frontiers

Carleo, Alessandra; Cesarone, Francesco; Gheno, Andrea; Ricci, Jacopo Maria

doi:10.1007/s10203-017-0201-0

Cited by 19 publications

(6 citation statements)

References 27 publications

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“…In this work, we adopt a look-back approach, where the possible realizations of the discrete random variables are obtained from historical data. Furthermore, the investment decision is made assuming T equally likely historical scenarios, as it is common in portfolio optimization (see, e.g., Carleo et al [28], and references therein). In the case of long-only portfolios, we identify with the…”

Section: The Mean-variance-esg Modelmentioning

confidence: 99%

Does ESG Impact Really Enhance Portfolio Profitability?

2022

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Over the last few decades, growing attention to the topic of social responsibility has affected financial markets and institutional authorities. Indeed, recent environmental, social, and financial crises have inevitably led regulators and investors to take into account the sustainable investing issue; however, the question of how Environmental, Social, and Governance (ESG) criteria impact financial portfolio performances is still open. In this work, we examine a multi-objective optimization model for portfolio selection, where we add to the classical Mean-Variance analysis a third non-financial goal represented by the ESG scores. The resulting optimization problem, formulated as a convex quadratic programming, consists of minimizing the portfolio variance with parametric lower bounds on the levels of the portfolio expected return and ESG. We provide here an extensive empirical analysis on five datasets involving real-world capital market indexes from major stock markets. Our empirical findings typically reveal the presence of two behavioral patterns for the 16 Mean-Variance-ESG portfolios analyzed. Indeed, over the last fifteen years we can distinguish two non-overlapping time windows on which the inclusion of portfolio ESG targets leads to different regimes in terms of portfolio profitability. Furthermore, on the most recent time window, we observe that, for the US markets, imposing a high ESG target tends to select portfolios that show better financial performances than other strategies, whereas for the European markets the ESG constraint does not seem to improve the portfolio profitability.

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Section: The Mean-variance-esg Modelmentioning

confidence: 99%

Does ESG Impact Really Enhance Portfolio Profitability?

2022

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“…SQP combines an active set method and Newton's method for solving nonlinear optimization problems. Some works also use SQP to perform such optimization problems 32‐34 . The closing prices of the following assets trading in B3 are considered: VALE3, ITUB4, PETR4, B3SA3, BBDC4, PETR3, LAME3, JBSS3, WEGE3, and ODPV3.…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…Some works also use SQP to perform such optimization problems. [32][33][34] The closing prices of the following assets trading in B3 are considered: VALE3, ITUB4, PETR4, B3SA3, BBDC4, PETR3, LAME3, JBSS3, WEGE3, and ODPV3. The dataset is obtained from the Economatica © platform.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Investment portfolio tracking using model predictive control

Melo

Cardoso

Jesus

et al. 2022

Optim Control Appl Methods

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The composition of an investment portfolio aiming to increase the financial returns while reducing the exposure to risk is a topic of growing interest in the world. In this direction, we propose a model predictive control (MPC) strategy in order to optimize the investment portfolio selection taking into account the tracking of a reference portfolio with desired return. In addition, an analysis comparing different sizes of the prediction horizon according to VPH-MPC (Varying Predictive Horizon-MPC) and FPH-MPC (Fixed Predictive Horizon-MPC) algorithms is conducted. Finally, we propose an optimal control problem using the tracking error as a function of loss of CVaR (Conditional Value at Risk) measurement. Numerical experiments are run based on Brazilian Stock Exchange data. The experimental results are compared with the Markowitz portfolio optimization model, a conventional tracking strategy, and benchmarks from the Brazilian financial market. This comparison indicates a good tracking performance obtained by the proposed MPC in the two versions while satisfying the constraints.

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“…it/ docen ti/ cesar one/ DataS ets. htm, and have been used in other empirical analyses on portfolio selection(Carleo et al 2017;Cesarone et al 2020a;Benati and Conde 2022).…”

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Mean-Variance-VaR portfolios: MIQP formulation and performance analysis

2023

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Value-at-risk is one of the most popular risk management tools in the financial industry. Over the past 20 years, several attempts to include VaR in the portfolio selection process have been proposed. However, using VaR as a risk measure in portfolio optimization models leads to problems that are computationally hard to solve. In view of this, few practical applications of VaR in portfolio selection have appeared in the literature up to now. In this paper, we propose to add the VaR criterion to the classical Mean-Variance approach in order to better address the typical regulatory constraints of the financial industry. We thus obtain a portfolio selection model characterized by three criteria: expected return, variance, and VaR at a specified confidence level. The resulting optimization problem consists in minimizing variance with parametric constraints on the levels of expected return and VaR. This model can be formulated as a mixed-integer quadratic programming (MIQP) problem. An extensive empirical analysis on seven real-world datasets demonstrates the practical applicability of the proposed approach. Furthermore, the out-of-sample performance of the more binding optimal Mean-Variance-VaR portfolios seems to be generally better than that of the Equally Weighted and of the Mean-Variance-CVaR portfolios.

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Approximating exact expected utility via portfolio efficient frontiers

Cited by 19 publications

References 27 publications

Does ESG Impact Really Enhance Portfolio Profitability?

Does ESG Impact Really Enhance Portfolio Profitability?

Investment portfolio tracking using model predictive control

Mean-Variance-VaR portfolios: MIQP formulation and performance analysis

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