Modeling and Simulation in Engineering, Economics and by Raúl León, María Jesús Muñoz-Torres, Jose M. Moneva

By Raúl León, María Jesús Muñoz-Torres, Jose M. Moneva

This booklet comprises the refereed lawsuits of the foreign convention on Modeling and Simulation in Engineering, Economics and administration, MS 2016, held in Teruel, Spain, in July 2016. the development used to be co-organized by way of the AMSE organization and the collage of Zaragoza during the GESES examine team, with the help of the SoGReS-MF study workforce from collage Jaume I. This version of the convention paid specified cognizance to modeling and simulation in diversified fields of industrial management.
The 20 papers during this e-book have been conscientiously reviewed and chosen from fifty two submissions. they're geared up in topical sections on modeling and simulation in finance and accounting; modeling and simulation in company administration and economic climate; and engineering and different basic applications.

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The effect of earnings management on the value relevance of accounting information. J. Bus. Financ. Account. 31(3–4), 297–332 (2004) 8. : Understanding earnings quality: a review of the proxies, their determinants and their consequences. J. Account. Econ. 50(2–3), 127–466 (2010) 9. : The relative importance of firm and country characteristics for earnings quality around the world. Eur. Account. Rev. 19(4), 693–738 (2010) 10. : Corporate citizenship and earnings attributes. Adv. Account. 25(1), 40–48 (2009) 11.

An extended version of a generalized DE metaheuristic is also employed in optimizing a highly constrained POP by Ayodele and Charles [1]. The included constraints consist of bounds on holdings, cardinality, minimum transaction lots, and expert opinion. An expert can form an opinion based on indicators beyond the scope of the analyzed data and influence whether or not an asset should be included. Their methodology shows improved performance when compared to GA, TS, SA, and PSO. Lwin et al. [17] considered cardinality, quantity, pre-assignment and round lot constraints and developed a multi-objective evolutionary algorithm that is improved through a learning-guided solution generation strategy, which promotes efficient convergence (learning-guided multi-objective evolutionary algorithm with external archive, MODEwAwL).

Cálculo Estocástico y Calibración en Modelos de Tasa de Interés: Aplicación al Mercado LIBOR. Masters degree thesis, Facultad de Ciencias Económicas, Universidad de Buenos Aires (2015) 2. : The market model of interest rate dynamics. Math. Financ. 7, 127–155 (1997) 3. : Credit Risk Modeling Using Excel and VBA. Wiley, London (2007) 4. : Monte Carlo Methods in Financial Engineering, vol. 53. Springer Science & Business Media, New York (2003) The LIBOR Market Model Calibration with Separated Approach 21 5.

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