arXiv subjects

Francisco Salas-Molina

Publications and source records attributed to Francisco Salas-Molina.

7 recordsLinked to original sources

arXiv2024

A General Approach for Computing a Consensus in Group Decision Making That Integrates Multiple Ethical Principles

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. More formally, we put forward a novel formalisation of the above-mentioned problem based on a multinorm 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 state-of-the-art approaches that were limited to only two ethical principles (p set to one, for maximum freedom, and p set to infinity, 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

econ.TH↗

arXiv2024

Fibonacci vector and matrix p-norms

This paper delves into vector and matrix norms of Fibonacci numbers. Two classes of Fibonacci vectors and a parametric p-norm are defined. From this definition, several properties of Fibonacci vector and matrix p-norms are described by varying parameter p. A closed-form expression is given to obtain the value of p, setting the difference between the p-norm and the infinite norm below a given threshold. A new class of symmetric k-Fibonacci matrix is defined such that a simple reorganization simplifies the computation of its p-norm. The analysis is extended to p-distances when considering the norm of the difference of two vectors (matrices) of the same size.

math.NT↗

arXiv2024

Fitting random cash management models to data

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.

q-fin.CP↗

arXiv2020

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.

cs.GT↗

arXiv2017

Empirical analysis of daily cash flow time series and its implications for forecasting

Cash managers make daily decisions based on predicted monetary inflows from debtors and outflows to creditors. Usual assumptions on the statistical properties of daily net cash flow include normality, absence of correlation and stationarity. We provide a comprehensive study based on a real-world cash flow data set from small and medium companies, which is the most common type of companies in Europe. We also propose a new cross-validated test for time-series non-linearity showing that: (i) the usual assumption of normality, absence of correlation and stationarity hardly appear; (ii) non-linearity is often relevant for forecasting; and (iii) typical data transformations have little impact on linearity and normality. Our results provide a forecasting strategy for cash flow management which performs better than classical methods. This evidence may lead to consider a more data-driven approach such as time-series forecasting in an attempt to provide cash managers with expert systems in cash management.

q-fin.ST↗

arXiv2017

PyCaMa: Python for cash management

Selecting the best policy to keep the balance between what a company holds in cash and what is placed in alternative investments is by no means straightforward. We here introduce PyCaMa, a Python module for multiobjective cash management based on linear programming that allows to derive optimal policies for cash management with multiple bank accounts in terms of both cost and risk of policies.

q-fin.CP↗

arXiv2016

Empowering cash managers to achieve cost savings by improving predictive accuracy

Cash management is concerned with optimizing the short-term funding requirements of a company. To this end, different optimization strategies have been proposed to minimize costs using daily cash flow forecasts as the main input to the models. However, the effect of the accuracy of such forecasts on cash management policies has not been studied. In this article, using two real data sets from the textile industry, we show that predictive accuracy is highly correlated with cost savings when using daily forecasts in cash management models. A new method is proposed to help cash managers estimate if efforts in improving predictive accuracy are proportionally rewarded by cost savings. Our results imply the need for an analysis of potential cost savings derived from improving predictive accuracy. From that, the search for better forecasting models is in place to improve cash management.

q-fin.GN↗