David Pla-Santamaria

Socially responsible investment: A multicriteria approach to portfolio selection combining ethical and financial objectives

In a context of Socially Responsible Investment (SRI), this paper deals with portfolio selection for investors interested in ethical policies. In the opportunity set there are ethical assets and other assets which are not characterized as ethical. Two goals are considered, the traditional financial goal in the classical utility theory under uncertainty and an ethical goal in the same utility framework. A new financial-ethical bi-criteria model is proposed with absolute risk aversion coefficients and targets depending on the investor’s ethical profile. This approach is relevant as an increasing number of mutual funds are becoming interested in SRI strategies. From the proposed model, an actual case on green investment is developed. Concerning this case (without generalizing to other contexts), an analysis of the numerical results shows that efficient portfolios obtained by the traditional E-V model outperform the strong green portfolios in terms of expected return and risk, but this does not significantly occur with weak green investment.

Portfolio selection under strict uncertainty: A multi-criteria methodology and its application to the Frankfurt and Vienna Stock Exchanges

Abstract In modern portfolio theory, it is common practice to first compute the risk-reward efficient frontier and then to support an individual investor in selecting a portfolio that meets his/her preferences for profitability and risk. Potential flaws include (a) the assumption that past data provide sufficient evidence for predicting the future performances of the securities under consideration and (b) the necessity to mathematically determine or approximate the investor’s utility function. In this paper, we propose a methodology whose initial phase filters portfolios that are inefficient from a historical perspective. While this is consistent with traditional approaches, the second phase differs from the standard approach as it uses a decision table constructed by considering multiple scenarios assuming strict uncertainty. The table cells measure consequences by a multi-criteria linear performance index of simulated future returns, which avoids difficulties with performance ratios. The real world applicability is illustrated through two studies based on data from the stock exchanges in Frankfurt and Vienna.

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

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.

Grading the performance of market indicators with utility benchmarks selected from Footsie: a 2000 case study

The suitable choice of a benchmark portfolio is a critical problem prior to using the information ratio, as the performance ranking of funds depends on this choice. In this paper, a method to optimize benchmark selection taking account of the investors preferences is proposed and applied to a case study of performance for 29 market indicators on stock exchanges throughout the world. The method that relies on recent results in optimization theory requires defining the opportunity set to select the benchmarks, this set being Footsie in the case study. The computational process and numerical results are presented through tables and figures, the accuracy of the method being also numerically tested.

A multi-objective approach to the cash management problem

Cash management is concerned with optimizing costs of short-term cash policies of a company. Different optimization models have been proposed in the literature whose focus has been only placed on a single objective, namely, on minimizing costs. However, cash managers may also be interested in risk associated to cash policies. In this paper, we propose a multi-objective cash management model based on compromise programming that allows cash managers to select the best policies, in terms of cost and risk, according to their risk preferences. The model is illustrated through several examples using real data from an industrial company, alternative cost scenarios and two different measures of risk. As a result, we provide cash managers with a new tool to allow them deciding on the level of risk to take in daily decision-making.

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

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.

Empowering Cash Managers Through Compromise Programming

Typically, the cash management literature focuses on optimizing cost, hence neglecting risk analysis. In this chapter, we address the cash management problem from a multiobjective perspective by considering not only the cost but also the risk of cash policies. We propose novel measures to incorporate risk analysis as an additional goal in cash management. Next, we rely on compromise programming as a method to minimize the sum of weighted distances to an ideal point where both cost and risk are minimum. These weights reflect the particular preferences of cash managers when selecting the best policies that solve the multiobjective cash management problem. As a result, we suggest three alternative solvers to cover a wide range of possible situations: Monte Carlo methods, linear programming, and quadratic programming. We also provide a Python software library with an implementation of the proposed solvers ready to be embedded in cash management decision support systems. We finally describe a framework to assess the utility of cash management models when considering multiple objectives.

Portfolio Selection by Compromise Programming

CP is a deterministic model like WGP in this aspect. Therefore, CP seems inappropriate to select stock portfolios from the Eu(R) maximization theory. In contrast to MV-SGP model, CP does not generalize Markowitz M-V model to multiple objectives. This lack of strictness is mitigated by the linkage between CP and utility theory established in Chap. 8. This linkage allows us to extend utility properties to CP approaches. We show the CP setting for portfolio selection by establishing and graphing its main elements: profitability-safety efficient frontier, ideal point and the bounds of Yu compromise set, which is the landing area on which the profitability-safety utility function reaches its maximum. From these variables, expected return and safety, the portfolio selection problem is defined in terms of CP.

Evaluating Loan Performance for Bank Offices: A Multicriteria Decision-Making Approach

Abstract This paper aims at evaluating loan performance of bank offices. For this purpose, a multicriteria decision support model given uncertainty is developed, in which the criteria to evaluate loan performance are the different discount rates which can be potentially used to compute the net present value (NPV) of each loan outflow and repayment inflow. This proposal is motivated by the fact that the true discount rate (opportunity cost of capital) is uncertain. The bank offices are classified in non-dominated and dominated by other bank offices in terms of loan performance from the multiple NPV criteria. As a further result, a complete ranking of the bank offices from their performance indexes is obtained. This ranking relies on a principle of moderate pessimism to solve uncertainty tables. Although the proposed method is applicable to various types of loans, the special class of personal loans is emphasised in the paper. As an actual case, a set of bank offices are evaluated from their loans and repayments during the period 2001–2010. Numerical data are tabulated together with the computing process and the results.

A decision approach to competitive electronic sealed-bid auctions for land

Electronic markets for land are innovative techniques potentially advantageous to buyers and private sellers, the latter being interested in sealed-bid auctions assuring high levels of competition among many bidders so that coalitions and cooperative games are ruled out. Land electronic tendering requires sufficient online information for bidders such as valuation reports by prestigious surveyors. To help the bidder make his best choice, we propose a decision model for moderately pessimistic players facing tenders where competition among a great number of independent antagonists excludes the use of cooperative games and involves strict uncertainty. A worked example concerning farmland in Spain is presented.