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Inicio Revista Iberoamericana de Automática e Informática Industrial RIAI Modelado Matemático de un Sistema de Concentración de Fondos y Desembolsos
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Vol. 13. Núm. 3.
Páginas 338-349 (julio - septiembre 2016)
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Vol. 13. Núm. 3.
Páginas 338-349 (julio - septiembre 2016)
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Modelado Matemático de un Sistema de Concentración de Fondos y Desembolsos
Mathematical Modeling of a Cash Concentration and Disbursements System
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Carlos Antonio Herrera-Cáceresa,b,
Autor para correspondencia
, Asier Ibeasb
a Departamento de Ingeniería Informática. Universidad Nacional Experimental del Táchira. Avenida Universidad, Sector Paramillo. San Cristóbal, Venezuela
b Departament de Telecomunicació i d’Enginyeria de Sistemes. Universitat Autònoma de Barcelona. 08193 Bellaterra. Barcelona. Spain
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Este trabajo presenta un modelo de simulación para un sistema de concentración de fondos y desembolsos (SCFD) visto como un sistema de gestión de inventario, basado en ecuaciones en diferencias y técnicas de ingeniería de sistemas. El modelo asume la existencia de retardos por trámite o traslado bancario y analiza la aplicación del concepto de operación con cuentas de saldo cero. Se plantea el caso de una empresa genérica cuyas agencias o distribuidores geográficamente están dispersos en diferentes regiones. El modelo supone la existencia de una cuenta principal operada centralizadamente y política de saldo mínimo. Esta cuenta recibe las transferencias de los ingresos depositados en las cuentas de ingresos de cada agencia y, también, desde la cuenta principal son transferidos los fondos para cubrir los sobregiros ocasionados en las cuentas de egresos de las agencias. Existe una cuenta de inversión a la cual se transfiere el superávit de efectivo en la cuenta principal y una línea de crédito que cubre los déficits de saldo en esa cuenta. Se definen las reglas de operación del SCFD y se consideran los ingresos y costos involucrados. El modelo representa el flujo del dinero entre los elementos identificados del sistema y el flujo de requerimientos u órdenes de transferencia. Se deriva un modelo equivalente representado por ecuaciones algebraicas utilizando la transformada z con el fin de abrir perspectivas al uso riguroso de técnicas de control en el campo de las finanzas.

Palabras clave:
Simulación
Concentración de caja y desembolsos
Control de inventarios
Transferencia de dinero
Transformada z.
Abstract

This paper presents a simulation model for a cash concentration and disbursements system (CCDS) seen as an inventory management system, based on difference equations and systems engineering techniques. The model assumes the existence of delays due to banking procedures and analyzes the application of the zero balance accounts concept. The case of a generic company whose agencies are geographically distributed in different regions is proposed. The model assumes the existence of a centrally operated main account and minimum balance policy. This account receives money transfers from the revenues accounts of each agency and, also from the main account, money is transferred to the agencies’ expense accounts in order to cover overdrafts. There exist an investment account into which any cash surpluses of the main account are deposited and a credit line in order to avoid the cash deficits. The operating rules for the CCDS are defined, and income and financial costs involved are considered. The model represents the flow of money between the identified elements of the system and the flow of money requirements or transfer orders. An equivalent model represented by algebraic equations through the z-transform is derived, which opens perspectives for using rigorous control techniques in the field of finance.

Keywords:
Simulation
Cash concentration and disbursement
Inventory control
Money transfer
z Transform
Referencias
[Albanese et al., 2004]
C. Albanese, K. Jackson, P. Wiberg.
A new Fourier transform algorithm for value-at-risk.
Quantitative Finance, 4 (2004), pp. 328-338
[Anvari, 1981]
M. Anvari.
An application of inventory theoretical models to cash collection.
Decision Sciences, 12 (1981), pp. 126-135
[Anvari, 1986]
M. Anvari.
Efficient scheduling of cross-border cash transfers.
Financial Management, 15 (1986), pp. 40-49
[Anvari, 1987]
M. Anvari.
Cash transfer scheduling for concentrating noncentral receipts.
Management Science, 33 (1987), pp. 25-38
[Anvari and Goyal, 1985]
M. Anvari, S.K. Goyal.
Optimization of the decentralized cash management problem.
European Journal of Operational Research, 20 (1985), pp. 198-205
[Anvari and Mohan, 1980]
M. Anvari, N. Mohan.
A computerized cash concentration system.
Omega-International Journal of Management Science, 8 (1980), pp. 459-464
[Baccarin, 2009]
S. Baccarin.
Optimal impulse control for a multidimensional cash management system with generalized cost functions.
European Journal of Operational Research, 196 (2009), pp. 198-206
[Bar-Ilan et al., 2004]
A. Bar-Ilan, D. Perry, W. Stadje.
A generalized impulse control model of cash management.
Journal of Economic Dynamics & Control, 28 (2004), pp. 1013-1033
[Baumol, 1952]
W.J. Baumol.
The transactions demand for cash: an inventory theoretic approach.
Journal of Finance, LXVI (1952),
[Beyer and Sethi, 1999]
D. Beyer, S.P. Sethi.
The Classical Average-Cost Inventory Models of Iglehart and Veinott-Wagner Revisited.
Journal of Optimization Theory and Applications, 101 (1999), pp. 523-555
[Boissard, 2012]
Boissard, J., 2012. Applications and uses of digital filters in finance. Master's thesis, Swiss Federal Institute of Technology (ETHZ).
[Buser, 1986]
S.A. Buser.
Laplace Transforms as Present Value Rules: A Note.
The Journal of Finance, 41 (1986), pp. 243-247
[Cagan, 1956]
P. Cagan.
The monetary dynamics of hyperinflation.
Studies in the Quantity Theory of Money.,
[Carr and Madan, 1999]
P. Carr, D. Madan.
Option valuation using the fast Fourier transform.
The Journal of Computational Finance, 2 (1999), pp. 61-73
[Carr and Wu, 2004]
P. Carr, L.R. Wu.
Time-changed Levy processes and option pricing.
Journal of Financial Economics, 71 (2004), pp. 113-141
[Cerny, 2004]
Cerny, A., 2004. The risk of optimal, continuously rebalanced hedging strategies and its efficient evaluation via Fourier transform. London: Tanaka Business School, Series: Tanaka Business School discussion papers, pp. 1-41, ISSN 1744-6783 http://ssrn.com/abstract=559417.
[Cerny, 2006]
A. Cerny.
Introduction to Fast Fourier Transform in Finance.
Cass Business School Research Paper, (2006), pp. 1-29
[Cerny, 2009]
Cerny, A., 2009. Mathematical Techniques in Finance: Tools for Incomplete Markets (Second Edition). Princeton University Press, Princeton and Oxford, pp. xxii + 390.
[Cerqueti, 2012]
R. Cerqueti.
Financing policies via stochastic control: a dynamic programming approach.
Journal of Global Optimization, 53 (2012), pp. 539-561
[Chourdakis, 2005]
K. Chourdakis.
Option pricing using the fractional FFT.
The Journal of Computational Finance, 8 (2005), pp. 1-18
[Christev, 2005]
A. Christev.
The hyperinflation model of money demand: Some new empirical evidence from the 1990s.
Centre for Economic Reform and Transformation, (2005), pp. 1-34
[Cui et al., 2013]
X.Y. Cui, L.T. Gong, X.J. Zhao, H.F. Zou.
The Z-transform method for multidimensional dynamic economic systems.
Applied Economics Letters, 20 (2013), pp. 1081-1088
[Dempster and Hong, 2002]
Dempster, M.A. H., Hong, S.S. G., 2002. Spread option valuation and the fast Fourier transform. Mathematical Finance - Bachelier Congress 2000, Springer Finance, pp. 203-220.
[Dennis, 2009]
S.B. Dennis.
Matrix mathematics: Theory facts and formulas (Second Edition).
Princeton University Press, (2009), pp. xlii+1139
[Duffy, 2006]
D.J. Duffy.
Finite difference methods in financial engineering: A Partial differential equation approach.
John Wiley & Sons, Ltd, (2006), 9780470858820, pp. 442
[Eppen and Fama, 1968]
G.D. Eppen, E.F. Fama.
Solutions for cash-balance and simple dynamic-portfolio problems.
Journal of Business, 41 (1968), pp. 94-112
[Eppen and Fama, 1969]
G.D. Eppen, E.F. Fama.
Cash balance and simple dynamic portfolio problems with proportional costs.
International Economic Review, 10 (1969), pp. 119-133
[Fusai and Roncoroni, 2008]
Fusai, G., Roncoroni, A., 2008. Implementing models in quantitative finance: Methods and cases. Springer, Series: Springer Finance, p.p. xxiii + 607.
[Fusai et al., 2012]
G. Fusai, D. Marazzina, M. Marena, M. Ng.
Z-transform and preconditioning techniques for option pricing.
Quantitative Finance, 12 (2012), pp. 1381-1394
[García et al., 2012]
C.A. García, A. Ibeas, J. Herrera, R. Vilanova.
Inventory control for the supply chain: An adaptive control approach based on the identification of the lead-time.
Omega-International Journal of Management Science, 40 (2012), pp. 314-327
[García Salcedo et al., 2013]
C.A. García Salcedo, A. Ibeas Hernández, R. Vilanova, J. Herrera Cuartas.
Inventory control of supply chains: Mitigating the bullwhip effect by centralized and decentralized Internal Model Control approaches.
European Journal of Operational Research, 224 (2013), pp. 261-272
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