A multicriteria approach to manage credit risk under strict uncertainty

Assessing the ability of applicants to repay their loans is generally recognized as a critical task in credit risk management. Credit managers rely on financial and market information, usually in the form of ratios, to estimate the quality of credit applicants. However, there is no guarantee that a given set of ratios contains the information needed for credit classification. Decision rules under strict uncertainty aim to mitigate this drawback. In this paper, we propose the use of a moderate pessimism decision rule combined with dimensionality reduction techniques and compromise programming. Moderate pessimism ensures that neither extreme optimistic nor pessimistic decisions are taken. Dimensionality reduction from a set of ratios facilitates the extraction of the relevant information. Compromise programming allows to find a balance between quality of debt and risk concentration. Our model produces two critical outputs: a quality assessment and the optimum allocation of funds. To illustrate our multicriteria approach, we include a case study on 29 firms listed in the Spanish stock market. Our results show that dimensionality reduction contributes to avoid redundancy and that quality-diversification optimization is able to produce budget allocations with a reduced number of firms

Boundless multiobjective models for cash management

"This is an Accepted Manuscript of an article published by Taylor & Francis in Engineering Economist on 31-05-2018, available online: https://doi.org/10.1080/0013791X.2018.1456596"[EN] Cash management models are usually based on a set of bounds that complicate the selection of the optimal policies due to nonlinearity. We here propose to linearize cash management models to guarantee optimality through linear-quadratic multiobjective compromise programming models. We illustrate our approach through a reformulation of the suboptimal state-of-the-art Gormley-Meade¿s model to achieve optimality. Furthermore, we introduce a much simpler formulation that we call the boundless model that also provides optimal solutions without using bounds. Results from a sensitivity analysis using real data sets from 54 different companies show that our boundless model is highly robust to cash flow prediction errors.Generalitat de Catalunya [2014 SGR 118]; Ministerio de Economia y Competitividad [Collectiveware TIN2015-66863-C2-1-R].Salas-Molina, F.; Rodriguez-Aguilar, JA.; Pla Santamaría, D. (2018). Boundless multiobjective models for cash management. Engineering Economist (Online). 63(4):363-381. https://doi.org/10.1080/0013791X.2018.1456596S363381634Artzner, P., Delbaen, F., Eber, J.-M., & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203-228. doi:10.1111/1467-9965.00068Baccarin, S. (2009). Optimal impulse control for a multidimensional cash management system with generalized cost functions. European Journal of Operational Research, 196(1), 198-206. doi:10.1016/j.ejor.2008.02.040Ballestero, E., & Romero, C. (1998). Multiple Criteria Decision Making and its Applications to Economic Problems. doi:10.1007/978-1-4757-2827-9Bar-Ilan, A., Perry, D., & Stadje, W. (2004). A generalized impulse control model of cash management. Journal of Economic Dynamics and Control, 28(6), 1013-1033. doi:10.1016/s0165-1889(03)00064-2Baumol, W. J. (1952). The Transactions Demand for Cash: An Inventory Theoretic Approach. The Quarterly Journal of Economics, 66(4), 545. doi:10.2307/1882104Bemporad, A., & Morari, M. (1999). Control of systems integrating logic, dynamics, and constraints. Automatica, 35(3), 407-427. doi:10.1016/s0005-1098(98)00178-2Ben-Tal, A., El Ghaoui, L., & Nemirovski, A. (2009). Robust Optimization. doi:10.1515/9781400831050Branke, J., Deb, K., Miettinen, K., & Słowiński, R. (Eds.). (2008). Multiobjective Optimization. Lecture Notes in Computer Science. doi:10.1007/978-3-540-88908-3Chelouah, R., & Siarry, P. (2000). Journal of Heuristics, 6(2), 191-213. doi:10.1023/a:1009626110229Chen, X., & Simchi-Levi, D. (2009). A NEW APPROACH FOR THE STOCHASTIC CASH BALANCE PROBLEM WITH FIXED COSTS. Probability in the Engineering and Informational Sciences, 23(4), 545-562. doi:10.1017/s0269964809000242Constantinides, G. M., & Richard, S. F. (1978). Existence of Optimal Simple Policies for Discounted-Cost Inventory and Cash Management in Continuous Time. Operations Research, 26(4), 620-636. doi:10.1287/opre.26.4.620Moraes, M. B. da C., & Nagano, M. S. (2014). Evolutionary models in cash management policies with multiple assets. Economic Modelling, 39, 1-7. doi:10.1016/j.econmod.2014.02.010Da Costa Moraes, M. B., Nagano, M. S., & Sobreiro, V. A. (2015). Stochastic Cash Flow Management Models: A Literature Review Since the 1980s. Decision Engineering, 11-28. doi:10.1007/978-3-319-11949-6_2De Avila Pacheco, J. V., & Morabito, R. (2011). Application of network flow models for the cash management of an agribusiness company. Computers & Industrial Engineering, 61(3), 848-857. doi:10.1016/j.cie.2011.05.018Girgis, N. M. (1968). Optimal Cash Balance Levels. Management Science, 15(3), 130-140. doi:10.1287/mnsc.15.3.130Golden, B., Liberatore, M., & Lieberman, C. (1979). Models and solution techniques for cash flow management. Computers & Operations Research, 6(1), 13-20. doi:10.1016/0305-0548(79)90010-8Gormley, F. M., & Meade, N. (2007). The utility of cash flow forecasts in the management of corporate cash balances. European Journal of Operational Research, 182(2), 923-935. doi:10.1016/j.ejor.2006.07.041Gregory, G. (1976). Cash flow models: A review. Omega, 4(6), 643-656. doi:10.1016/0305-0483(76)90092-xGurobi Optimization, Inc (2017) Gurobi optimizer reference manual, Houston.Keown, A. J., & Martin, J. D. (1977). A Chance Constrained Goal Programming Model for Working Capital Management. The Engineering Economist, 22(3), 153-174. doi:10.1080/00137917708965174Miller, M. H., & Orr, D. (1966). A Model of the Demand for Money by Firms. The Quarterly Journal of Economics, 80(3), 413. doi:10.2307/1880728Neave, E. H. (1970). The Stochastic Cash Balance Problem with Fixed Costs for Increases and Decreases. Management Science, 16(7), 472-490. doi:10.1287/mnsc.16.7.472PARK, C. S., & HERATH, H. S. B. (2000). EXPLOITING UNCERTAINTY—INVESTMENT OPPORTUNITIES AS REAL OPTIONS: A NEW WAY OF THINKING IN ENGINEERING ECONOMICS. The Engineering Economist, 45(1), 1-36. doi:10.1080/00137910008967534Penttinen, M. J. (1991). Myopic and stationary solutions for stochastic cash balance problems. European Journal of Operational Research, 52(2), 155-166. doi:10.1016/0377-2217(91)90077-9Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking & Finance, 26(7), 1443-1471. doi:10.1016/s0378-4266(02)00271-6Salas-Molina, F., Martin, F. 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Inverse malthusianism and recycling economics: the case of the textile industry

The current use of natural resources in the textile industry leads us to introduce a new economic concept called inverse Malthusianism describing a context in which population grows linearly and resource consumption grows exponentially. Inverse Malthusianism implies an exponential increase in environmental impact that recycling may contribute to reduce. Our main goal is to extend the analysis of materials selection under the principle of equimarginality proposed by Jevons. As a first result, we show the particular circumstances under which policies excluding recycled supplies are never optimal. We also aim to overcome the difficulties of reducing environmental aspects to monetary units. To this end, we propose a multicriteria approach to solve the conventional-recycled materials dilemma considering not only economic but also environmental criteria. Then, we allow producers to enrich their decision-making process with relevant information about the environmental impact of materials selection. Although we use examples of the textile industry to illustrate our results, most of the insights in this paper can be extended to other industries

La protección medioambiental como criterio en la selección de inversiones socialmente responsables: una aproximación multicriterio

[EN] A greater environmental and ethical awareness of companies and organizations is also ap-plied to portfolio selection. This note aims to put forward a multicriteria model of Goal Programming (GP) to design efficient portfolios considering classic financial criteria and environmental criteria[ES] La mayor concienciación medioambiental y ética de empresas y organizaciones se traslada también a la selección de carteras. En esta nota se propone un modelo multicriterio de programación por me-tas para la selección de carteras incorporando a los criterios clásicos financieros, criterios mediambientalesGarcía-Bernabeu, A.; Pla-Santamaria, D.; Bravo, M.; Pérez-Gladish, B. (2015). The Environmental Protection as a selection criterion in Socially Responsible Investments: A multicriteria approach. Economía Agraria y Recursos Naturales - Agricultural and Resource Economics. 15(1):101-112. doi:10.7201/earn.2015.01.06SWORD10111215

New decision rules under strict uncertainty and a general distance-based approach

Strict uncertainty implies a complete lack of knowledge about the probabilities of possible future states of the world. However, there is complete information about the set of alternatives under consideration, the set of future states, and the scalar evaluation of choosing every alternative if a given state occurs. The principle of insufficient reason by Laplace, the maximin rule by Wald, the Hurwicz criterion, or the minimax regret criterion by Savage are examples of decision rules under strict uncertainty. Within the context of strict uncertainty, moderate pessimism implies the existence of a decision-maker who cautiously assumes that the most favorable state will not occur when the action has been taken with no conjecture being made about the other states. The criterion of moderate pessimism proposed by Ballestero implies the use of the inverse of the range of evaluation for each state as a weight system. In this paper, we extend the notion of moderate pessimism under strict uncertainty to solve some of its limitations. First, we propose a new domination analysis that avoids removing dominated alternatives that are still relevant in the final ranking of alternatives. Second, we propose additional score functions using the inverse of the standard deviation and the mean absolute deviation instead of the range of evaluations for each future state to reduce the impact of the possible existence of outliers in the decision table. This partial result is later generalized through the concept of average deviation of a given order. Finally, we show that all the mentioned decision rules are special cases of a general ranking method based on the Minkowski distance function. We illustrate the use of distance-based decision rules through an application in the context of portfolio selection

Comments on: Multicriteria Decision Systems for Financial Problems

The final publication is available at Springer via http://dx.doi.org/10.1007/s11750-013-0280-1Pla Santamaría, D.; García Bernabeu, AM. (2013). Comments on: Multicriteria Decision Systems for Financial Problems. TOP. 21(2):275-278. doi:10.1007/s11750-013-0280-1S275278212Arrow KJ (1965) Aspects of the theory of risk-bearingBallestero E (2001) Stochastic goal programming: a mean-variance approach. Eur J Oper Res 131(3):476–481Copeland TE, Weston JF (1988) Financial theory and corporate policy. Addison-Wesley, ReadingDoumpos M, Zopounidis C (2010) A multicriteria decision support system for bank rating. Decis Support Syst 50(1):55–63Doumpos M, Zopounidis C (2011) A multicriteria outranking modeling approach for credit rating. Decis Sci 42(3):721–742Geanakoplos J (2001) Three brief proofs of arrow’s impossibility theorem. Yale Cowles Foundation discussion paper (1123RRR)Konno H, Yamazaki H (1991) Mean-absolute deviation portfolio optimization model and its applications to Tokyo Stock Market. Manag Sci 37(5):519–531Saaty TL, Ozdemir MS (2003) Why the magic number seven plus or minus two. Math Comput Model 38(3):233–244Sun S, Lu WM et al. (2005) A cross-efficiency profiling for increasing discrimination in data envelopment analysis. Inf Syst Oper Res 43(1):5

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

his 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, tech- nical 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 aver- sion is assumed. 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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 investor's 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.

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

Ballestero E, Günther M, Pla-Santamaria D, Stummer C. Portfolio selection under strict uncertainty: A multi-criteria methodology and its application to the Frankfurt and Vienna Stock Exchanges. European Journal of Operational Research. 2007;181(3):1476-1487