Fitting random cash management models to data

[EN] Organizations use cash management models to control balances to both avoid overdrafts and obtain a profit from short-term investments. Most management models are based on control bounds which are derived from the assumption of a particular cash flow probability distribution. In this paper, we relax this strong assumption to fit cash management models to data by means of stochastic and linear programming. We also introduce ensembles of random cash management models which are built by randomly selecting a subsequence of the original cash flow data set. We illustrate our approach by means of a real case study showing that a small random sample of data is enough to fit sufficiently good bound-based models.Salas-Molina, F. (2019). Fitting random cash management models to data. Computers & Operations Research. 106:298-306. https://doi.org/10.1016/j.cor.2018.04.00729830610

Selecting the best risk measure in multiobjective cash management

[EN] In this paper, we consider cash management from a multidimensional perspective in which cost and risk are desired goals to minimize. Cash managers interested in minimizing risk need to select the most appropriate risk measure according to their particular needs. In order to assess the quality of alternative risk measures, we empirically compare eight different risk measures in terms of the combined cost-risk performance of a cash management model. To this end, we rely on goal programming to derive optimal solutions for cash management models. Our results show that risk measures based on cost deviations better capture risk in comparison to those based on a reference cash balance. The methodology proposed in this paper allows cash managers to propose and evaluate new risk measures.Salas-Molina, F. (2019). Selecting the best risk measure in multiobjective cash management. International Transactions in Operational Research. 26(3):929-945. https://doi.org/10.1111/itor.1258092994526

Risk-sensitive control of cash management systems

[EN] Firms manage cash for operational, precautionary and speculative purposes. Stat-of-the-art cash management models usually focus on cost minimization by means of a set of controlling bounds. In this paper, we propose a multiobjective model to control cash management systems with multiple accounts characterized by generalized cash flow processes. In addition, we replace the customary use of bounds with cash balance reference trajectories. The model considers two objectives such as cost minimization, measured by the sum of transaction and holding costs, and risk control, measured by the sum of deviations from a given cash balance reference. We also present theoretical results on the stability of the model for deterministic, predictable and purely random cash flow processes. By means of numerical examples, we analyze the robustness of different risk-sensitive models to mean-variance misspecifications. The results show that tuning a parameter of our model can be of help to find more robust cash management policies. Finally, we present a case study showing how our risk-sensitive model can be used to adjust policies according to risk preferences.Salas-Molina, F. (2020). Risk-sensitive control of cash management systems. Operational Research. 20(2):1159-1176. https://doi.org/10.1007/s12351-017-0371-011591176202Abdelaziz FB, Aouni B, El Fayedh R (2007) Multi-objective stochastic programming for portfolio selection. Eur J Oper Res 177(3):1811–1823Aouni B, Colapinto C, La Torre D (2014) Financial portfolio management through the goal programming model: current state-of-the-art. Eur J Oper Res 234(2):536–545Baccarin S (2009) Optimal impulse control for a multidimensional cash management system with generalized cost functions. Eur J Oper Res 196(1):198–206Ballestero E, Garcia-Bernabeu A (2012) Portfolio selection with multiple time horizons: a mean variance-stochastic goal programming approach. Inf Syst Oper Res 50(3):106–116Baumol WJ (1952) The transactions demand for cash: an inventory theoretic approach. Q J Econ 66(4):545–556Bemporad A, Morari M (1999) Control of systems integrating logic, dynamics, and constraints. Automatica 35(3):407–427Ben-Tal A, Nemirovski A (1999) Robust solutions of uncertain linear programs. Oper Res Lett 25(1):1–13Ben-Tal A, El Ghaoui L, Nemirovski A (2009) Robust optimization. Princeton University Press, New JerseyCamacho EF, Bordons C (2007) Model predictive control. Springer, LondonConstantinides GM, Richard SF (1978) Existence of optimal simple policies for discounted-cost inventory and cash management in continuous time. Oper Res 26(4):620–636da Costa Moraes MB, Nagano MS (2014) Evolutionary models in cash management policies with multiple assets. Econ Model 39(1):1–7Emery GW (1981) Some empirical evidence on the properties of daily cash flow. Financ Manage 10(1):21–28Eppen GD, Fama EF (1969) Cash balance and simple dynamic portfolio problems with proportional costs. Int Econ Rev 10(2):119–133Gormley FM, Meade N (2007) The utility of cash flow forecasts in the management of corporate cash balances. Eur J Oper Res 182(2):923–935Gurobi Optimization, Inc (2016) Gurobi optimizer reference manual. http://www.gurobi.comHansen LP, Sargent TJ (2008) Robustness. Princeton University Press, New JerseyHerrera-Cáceres CA, Ibeas A (2016) Model predictive control of cash balance in a cash concentration and disbursements system. J Franklin Inst 353(18):4885–4923Homonoff R, Mullins DW (1975) Cash management: an inventory control limit approach. Lexington Books, LanhamKeerthi S, Gilbert EG (1988) Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: stability and moving-horizon approximations. J Optim Theory Appl 57(2):265–293Miller MH, Orr D (1966) A model of the demand for money by firms. Q J Econ 80(3):413–435Penttinen MJ (1991) Myopic and stationary solutions for stochastic cash balance problems. Eur J Oper Res 52(2):155–166Pindado J, Vico J (1996) Evidencia empírica sobre los flujos de caja. un nuevo enfoque en su tratamiento. Rev Esp Financ Contab 25(87):497–517Premachandra I (2004) A diffusion approximation model for managing cash in firms: an alternative approach to the Miller–Orr model. Eur J Oper Res 157(1):218–226Ross SA, Westerfield R, Jordan BD (2002) Fundamentals of corporate finance, 6th edn. McGraw-Hill, New YorkSalas-Molina F, Pla-Santamaria D, Rodriguez-Aguilar JA (2016) A multi-objective approach to the cash management problem. Ann Oper Res. https://doi.org/10.1007/s10479-016-2359-1Salas-Molina F, Martin FJ, Rodriguez-Aguilar JA, Serra J, Arcos JL (2017) Empowering cash managers to achieve cost savings by improving predictive accuracy. Int J Forecast 33(2):403–415Stone BK (1972) The use of forecasts and smoothing in control-limit models for cash management. Financ Manage 1(1):72–84Tobin J (1956) The interest elasticity of transactions demand for cash. Rev Econ Stat 38(3):241–24

DATA-DRIVEN DECISION-MAKING AND ITS APPLICATION TO THE CORPORATE CASH MANAGEMENT PROBLEM

Esta tesis investiga el problema de gestión de tesorería desde un punto de vista multidimensional. La gestión de tesorería trata de equilibrar la cantidad que se mantiene en efectivo y la que se dedica a inversiones a corto plazo. Normalmente, los tesoreros toman decisiones basándose en el nivel óptimo de tesorería por motivos operativos y de precaución. En esta tesis exploramos las oportunidades para mejorar la toma decisiones derivadas de modelar la incertidumbre presente en los flujos de caja con la ayuda de procedimientos basados en datos en un entorno multiobjetivo. Por un lado, los tesoreros pueden conseguir ahorros a través de la previsión de tesorería. Para ello, realizamos un estudio empírico con el objetivo de aprovechar las más recientes técnicas de aprendizaje automático como paso clave para conectar el análisis de los datos disponibles con los procesos de optimización en la gestión de tesorería. Por otro lado, los tesoreros pueden estar interesados no solo en el coste sino también en al riesgo asociado a sus decisiones. Por esta razón, tratamos el problema de gestión de tesorería desde una perspectiva multiobjetivo, considerando tanto el coste como el riesgo. Además, debido a la cambiante situación financiera actual, exploramos la selección de modelos de gestión de tesorería en función de diferentes condiciones operativas y de su robustez. También demostramos la utilidad de las previsiones a través de un nuevo modelo de gestión de tesorería que mejora el estado del arte al garantizar soluciones óptimas. Como la mayoría de las empresas trabaja con sistemas de tesorería con múltiples cuentas bancarias, desarrollamos un marco para la formulación y solución del problema de gestión de tesorería con múltiples cuentas bancarias. Finalmente, en un intento de acercar teoría y práctica, también ofrecemos una librería de software en Python para usuarios interesados en la construcción de sistemas de ayuda a la toma de decisiones en gestión de tesorería.This thesis investigates the cash management problem from a multidimensional perspective. Cash management focuses on finding the balance between cash holdings and short-term investments. Typically, cash managers make decisions based usually on a firm's optimal cash balance for operational and precautionary purposes. We here explore the opportunities for improved decision-making derived from modeling cash flow uncertainty with the help of data-driven procedures within a multiobjective context. On the one hand, cash managers may achieve cost savings by forecasting future cash flows. To this end, we perform an empirical analysis of daily cash flow time-series to take advantage of modern machine learning techniques as a key step to connect data analysis and optimization methods in cash management. On the other hand, cash managers may be interested not only in the cost but also in the risk associated to decision-making. Thus, we address the cash management problem from a multiobjective perspective focusing on both cost and risk. In addition, under the current situation of time-varying financial circumstances, the selection of cash management models according to operating conditions and its robustness are worth considering questions. We also show the utility of forecasts through a new cash management model which outperforms the state-of-the-art by guaranteeing optimal solutions. Since most firms usually deal with cash management systems with multiple accounts, we develop a framework to formulate and solve the multiple bank accounts cash management problem. Finally, in an attempt to fill the gap between theory and practice, we also provide a software library in Python for practitioners interested in building decision support systems for cash management.Esta tesi investiga el problema de gestió de tresoreria des d'un punt de vista multidimensional. La gestió de tresoreria tracta d'equilibrar la quantitat que es manté en efectiu i la que es dedica a inversions a curt termini. Normalment, el tresorers prenen decisions basant-se en el nivell òptim de tresoreria per motius operatius i de precaució. En aquesta tesi explorem les oportunitats per millorar la presa de decisions derivades de modelitzar la incertesa present en els fluxos de caixa amb l'ajuda de procediments basats en dades. Per un costat, els tresorers poden aconseguir estalvis de costos mitjançant la previsió de tresoreria. Per tal d'aconseguir-ho, realitzem d'un estudi empíric amb l'objectiu d'aprofitar les més recents tècniques d'aprenentatge automàtic per connectar l'anàlisi de les dades disponbiles amb els procesos d'optimització en la gestió de tresoreria. Per altra banda, els tresorers poden estar interessats no sols en el cost sinó també en el risc associat a les seues decisions. Per tant, tractem el problema de gestió de tresoreria des d'un punt de vista multiobjectiu, fixant-se tant en el cost com en el risc. A més a més, degut a la canviant situació financera actual, explorem la selecció de models de gestió de tresoreria en funció de diferents condicions operatives i de la seua robustesa. També demostrem la utilitat de les previsions mitjançant un nou model de tresoreria que millora l'estat de l'art al garantir solucions òptimes. Com que la majoria d'empreses treballa amb sistemes de tresoreria amb múltiples comptes bancaris, desenvolupem un marc per a la formulació i solució del problema de gestió de tresoreria amb múltiples comptes bancaris. Finalment, en un intent d'apropar teoria i pràctica, també oferim un llibreria en Python per a usuaris interessats en la construcció de sistemes d'ajuda a la presa de decisions en la gestió de tresoreria.Salas Molina, F. (2017). DATA-DRIVEN DECISION-MAKING AND ITS APPLICATION TO THE CORPORATE CASH MANAGEMENT PROBLEM [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/95408TESI

Non-linear Neutrosophic Numbers and Its Application to Multiple Criteria Performance Assessment

[EN] The concept of fuzzy set has been extended by neutrosophic fuzzy sets to represent sets whose elements have different degrees of membership characterized by a truth-membership function, an indeterminacy-membership function and a falsity-membership function. It is usually assumed that these functions are linear, hence excluding the possibility of non-linearity in many decision-making situations. From an alternative definition of non-linear neutrosophic numbers, we develop the concepts of (alpha, beta, gamma)-cuts, possibility mean, variance, skewness and a new possibility score function. These concepts are useful to deal with multiple criteria decision making problems. We illustrate the practical use of these concepts by means of a real case study in supply chain risk management in the motor industry. Due to the fact that neutrosophic sets have been used in several areas of decision-making, finance and economics, we argue that our proposal contributes to enhance the application of neutrosophic numbers.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Reig-Mullor, J.; Salas-Molina, F. (2022). Non-linear Neutrosophic Numbers and Its Application to Multiple Criteria Performance Assessment. International Journal of Fuzzy Systems. 24(6):2889-2904. https://doi.org/10.1007/s40815-022-01295-y2889290424

Shared value economics: an axiomatic approach

The concept of shared value was introduced by Porter and Kramer as a new conception of capitalism. Shared value describes the strategy of organizations that simultaneously enhance their competitiveness and the social conditions of related stakeholders such as employees, suppliers and the natural environment. The idea has generated strong interest, but also some controversy due to a lack of a precise definition, measurement techniques and difficulties to connect theory to practice. We overcome these drawbacks by proposing an economic framework based on three key aspects: coalition formation, sustainability and consistency, meaning that conclusions can be tested by means of logical deductions and empirical applications. The presence of multiple agents to create shared value and the optimization of both social and economic criteria in decision making represent the core of our quantitative definition of shared value. We also show how economic models can be characterized as shared value models by means of logical deductions. Summarizing, our proposal builds on the foundations of shared value to improve its understanding and to facilitate the suggestion of economic hypotheses, hence accommodating the concept of shared value within modern economic theory.Comment: 22 pages, 4 figure

A general approach for computing a consensus in group decision making that integrates multiple ethical principles

[EN] We tackle the problem of computing a consensus according to multiple ethical principles - which can include, for example, the principle of maximum freedom associated with the Benthamite doctrine and the principle of maximum fairness associated with the Rawlsian principles - among the preferences of different individuals in the context of Group Decision-Making (GDM). More formally, we put forward a novel formalisation of the above-mentioned problem based on a multi-lp-norm approximation problem that aims at minimising multiple p-metric distance functions, where each parameter p represents a given ethical principle. Our contribution incurs obvious benefits from a social-choice perspective. Firstly, our approach significantly generalises stateof-the-art approaches that were limited to only two ethical principles (p = 1, for maximum freedom, and p = & INFIN;, for maximum fairness). Secondly, our experimental results considering an established test case demonstrate that our approach is capable, thanks to a novel re-weighting scheme, to compute a multi-norm consensus that takes into account each ethical principle in a balanced way, in contrast with state-of-the-art approaches that were heavily biased towards the p =1 ethical principle.Research supported by projects: CI-SUSTAIN, Spain (PID2019-104156GB-I00) ; TAILOR, Spain (H2020-952215) ; 2021 SGR 00754 funded by Generalitat de Catalunya, Spain; VAE TED2021-131295B-C31, funded by MCIN/AEI, Spain/10.13 039/501100011033 and NextGenerationEU/PRTR, Spain; and VALAWAI, Spain (Horizon Europe #101070930) . Funding for open access charge: CRUE-Universitat Politecnica de Valencia.Salas-Molina, F.; Bistaffa, F.; Rodríguez-Aguilar, JA. (2023). A general approach for computing a consensus in group decision making that integrates multiple ethical principles. Socio-Economic Planning Sciences. 89. https://doi.org/10.1016/j.seps.2023.1016948

Sustainability performance assessment with intuitionistic fuzzy composite metrics and its application to the motor industry

The performance assessment of companies in terms of sustainability requires to find a balance between multiple and possibly conflicting criteria. We here rely on composite metrics to rank a set of companies within an industry considering environmental, social and corporate governance criteria. To this end, we connect intuitionistic fuzzy sets and composite programming to propose novel composite metrics. These metrics allow to integrate important environmental, social and governance principles with the gradual membership functions of fuzzy set theory. The main result of this paper is a sustainability assessment method to rank companies within a given industry. In addition to consider multiple objectives, this method integrates two important social principles such as maximum utility and fairness. A real-world example is provided to describe the application of our sustainability assessment method within the motor industry. A further contribution of this paper is a multicriteria generalization of the concept of magnitude of a fuzzy number

A multi-objective approach to the cash management problem

[EN] 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.Work partially funded by projects Collectiveware TIN2015-66863-C2-1-R (MINECO/FEDER) and 2014 SGR 118.Salas-Molina, F.; Pla Santamaría, D.; Rodriguez Aguilar, JA. (2016). A multi-objective approach to the cash management problem. Annals of Operations Research. 1-15. https://doi.org/10.1007/s10479-016-2359-1S115Baccarin, S. (2009). Optimal impulse control for a multidimensional cash management system with generalized cost functions. European Journal of Operational Research, 196(1), 198–206.Ballestero, E. (1998). Approximating the optimum portfolio for an investor with particular preferences. Journal of the Operational Research Society, 49(9), 998–1000.Ballestero, E. (2005). Mean-semivariance efficient frontier: A downside risk model for portfolio selection. Applied Mathematical Finance, 12(1), 1–15.Ballestero, E., & Pla-Santamaria, D. (2004). Selecting portfolios for mutual funds. Omega, 32(5), 385–394.Ballestero, E., & Romero, C. (1998). Multiple criteria decision making and its applications to economic problems. Berlin: Springer.Bates, T. W., Kahle, K. M., & Stulz, R. M. (2009). Why do US firms hold so much more cash than they used to? The Journal of Finance, 64(5), 1985–2021.Baumol, W. J. (1952). The transactions demand for cash: An inventory theoretic approach. The Quarterly Journal of Economics, 66(4), 545–556.Chen, 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(04), 545–562.Constantinides, 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.da Costa Moraes, M. B., & Nagano, M. S. (2014). Evolutionary models in cash management policies with multiple assets. Economic Modelling, 39, 1–7.da Costa Moraes, M. B., Nagano, M.S., Sobreiro, V. A. (2015). Stochastic cash flow management models: A literature review since the 1980s. In P. Guarnieri (Ed.), Decision models in engineering and management. Decision engineering (pp. 11–28). Switzerland: Springer.Eppen, G. D., & Fama, E. F. (1969). Cash balance and simple dynamic portfolio problems with proportional costs. International Economic Review, 10(2), 119–133.Gao, H., Harford, J., & Li, K. (2013). Determinants of corporate cash policy: Insights from private firms. Journal of Financial Economics, 109(3), 623–639.Girgis, N. M. (1968). Optimal cash balance levels. Management Science, 15(3), 130–140.Gormley, 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.Gregory, G. (1976). Cash flow models: A review. Omega, 4(6), 643–656.Markowitz, H. (1952). Portfolio Selection. 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On the use of multiple criteria distance indexes to find robust cash management policies

[EN] Cash management decision-making can be handled from a multiobjective perspective by optimizing not only cost but also risk. Nevertheless, choosing the best policies under a changing context is by no means straightforward. To this end, we rely on compromise programming to incorporate robustness as an additional goal to cost and risk within a multiobjective framework. As a result, we propose to calculate robustness as a multiple criteria distance index that is able to identify the best compromise policies in terms of cost and risk. Such policies are also robust to cash flow regime changes. We show its utility by transforming the Miller and Orr s cash management model into its robust counterpart using real data from an industrial company.Ministerio de Economia y Competitividad [grant number Collectiveware TIN2015-66863-C2-1-R], [grant number 2014 SGR 118]. Work partially funded by projects Collectiveware TIN2015-66863-C2-1-R (MINECO/FEDER) and 2014 SGR 118.Salas-Molina, F.; Rodriguez-Aguilar, JA.; Pla Santamaría, D. (2019). On the use of multiple criteria distance indexes to find robust cash management policies. INFOR Information Systems and Operational Research. 57(3):345-360. https://doi.org/10.1080/03155986.2017.1282291S34536057