Handling uncertainty in agricultural supply chain management: a state of the art

We deal with the buy-and-hold choice of fund portfolios by considering multiple states of nature (future market scenarios). These states are associated with goals in the sense that the investor pursues to optimize a classical financial objective function as much as possible whatever the states of nature. As this classical function is very cumbersome for handling, a satisficing proxy is used. This proxy is Stochastic Goal Programming (SGP), a recent uncertainty multiobjective model characterized as follows: (a) it relies on Von Neumann and Morgenstern's–Arrow's Eu(R) principles in a framework of bounded rationality; (b) its moderate computational burden allows easy application to large scale problems. In SGP, the variability matrices of goals are aggregated by Arrow's risk aversion coefficients. Concerning the case study, the states of nature are Eurostoxx market index scenarios defined from time series. As an opportunity set of assets, we use a large set of funds managed by an international consu...

Selecting Portfolios Given Multiple Eurostoxx-Based Uncertainty Scenarios: A Stochastic Goal Programming Approach from Fuzzy Betas

Socially Responsible Investment: A multicriteria approach to portfolio selection combining ethical and financial objectives

This paper provides an overview of the status quo in socially responsible investing (SRI) literature. We outline motives, history, and current best practice of SRI. We also provide a thorough analysis of a wide set of studies that cover two key topics in this field: the first research objective is to determine the relative performance of SRI vehicles in comparison to their conventional benchmarks. Our meta-analysis shows that most research studies find that socially responsible (SR) investments perform equal to conventional investments, but these findings are challenged by contradictory results from other studies. The second objective is to analyze SR behavior’s effects on a company’s financial results. We cover the period between 1986 and 2012. This paper provides future researchers with a well-documented and structured overview of the existing literature on SRI, thereby identifying gaps that might be closed by future research.

https://www.econstor.eu/bitstream/10419/156272/1/861681010.pdf

Ethical requirement and financial interest: a literature review on socially responsible investing

Socially responsible investment (SRI) encompasses both ethical and financial paradigms. This systematic literature review explores three key research themes within the SRI literature, identifying a significant disconnect between themes and a fixation on the financial (as opposed to ethical) paradigm. One of the foundations of SRI is environmental, social, and governance (ESG) metrics. This review confirms the importance of ESG metrics in the SRI field, as they play two crucial roles, namely, as a proxy for sustainability performance and an enabler of the SRI market. However, there are two main issues related to ESG metrics that undermine their reliability: a lack of transparency and a lack of convergence.

A systematic literature review of socially responsible investment and environmental social governance metrics

Applying stochastic goal programming: A case study on water use planning

To create efficient funds appealing to a sector of bank clients, the objective of minimizing downside risk is relevant to managers of funds offered by the banks In this paper, a case focusing on this objective is developed More precisely, the scope and purpose of the paper is to apply the mean-semivariance efficient frontier model, which is a recent approach to portfolio selection of stocks when the investor is especially interested in the constrained minimization of downside risk measured by the portfolio semivariance Concerning the opportunity set and observation period, the mean-semivariance efficient frontier model is applied to an actual case of portfolio choice from Dow Jones stocks with daily prices observed over the period 2005–2009 From these daily prices, time series of returns (capital gains weekly computed) are obtained as a piece of basic information Diversification constraints are established so that each portfolio weight cannot exceed 5 per cent The results show significant differences between the portfolios obtained by mean-semivariance efficient frontier model and those portfolios of equal expected returns obtained by classical Markowitz mean-variance efficient frontier model Precise comparisons between them are made, leading to the conclusion that the results are consistent with the objective of reflecting downside risk

/pdf/portfolio-optimization-based-on-downside-risk-a-mean-47m9ae5pgr.pdf

Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips

This paper deals with benchmark-based portfolio choice for buy-and-hold strategies of investing. Multiple benchmarks for returns are considered, which is more realistic than taking a unique benchmark – a unique aspiration difficult to select in practice among the various aspirations for returns that the investor has in mind. Portfolio selection with multiple benchmarks leads to a multi-objective problem, which is addressed by mean value – stochastic goal programming. In particular, two benchmarks are considered, which involves two goals. Weights for goals depend on investor's preferences and Arrow's absolute risk aversion coefficients. An efficient frontier of portfolios is obtained. Advantages of this stochastic method in our context are as follows: (i) Mean value-stochastic goal programming relies on classical utility theory under uncertainty and Arrow's absolute risk aversion, which ensures soundness and strictness, and (ii) the numerical model is easily solved by using available software such as mean–variance software. Numerical results are tabulated and discussed. Copyright © 2011 John Wiley & Sons, Ltd.

Portfolio Selection from Multiple Benchmarks: A Goal Programming Approach to an Actual Case

This paper proposes a compromise programming (CP) model to help investors decide whether to construct photovoltaic power plants with government financial support. For this purpose, we simulate an agreement between the government, who pursues political prices (guaranteed prices) as low as possible, and the project sponsor who wants returns (stochastic cash flows) as high as possible. The sponsor’s decision depends on the positive or negative result of this simulation, the resulting simulated price being compared to the effective guaranteed price established by the country legislation for photovoltaic energy. To undertake the simulation, the CP model articulates variables such as ranges of guaranteed prices, technical characteristics of the plant, expected energy to be generated over the investment life, investment cost, cash flow probabilities, and others. To determine the CP metric, risk aversion is assumed. As an actual application, a case study on photovoltaic power investment in Extremadura, western Spain, is developed in detail.

/pdf/photovoltaic-power-plants-a-multicriteria-approach-to-armpoiodyy.pdf

Mila Bravo

Papers

Socially Responsible Investment: A multicriteria approach to portfolio selection combining ethical and financial objectives

Applying stochastic goal programming: A case study on water use planning

Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips

Portfolio Selection from Multiple Benchmarks: A Goal Programming Approach to an Actual Case

Photovoltaic power plants: a multicriteria approach to investment decisions and a case study in western Spain