QUANTITATIVE METHODS FOR DECISION MAKING CourseCode: 3533Degree: Master's in Advanced Accounting and FinanceFaculty of Social and Legal Sciences of ElcheYear: Year 1 of Master's in Advanced Accounting and FinanceSemester: SpringType: RequiredLanguage: SpanishECTS credits: 6Lecture: 3Laboratory: 3Hours: 150Directed: 45Shared: 26Autonomous: 79Subject matter: Mathematics and Quantitative Methods for BusinessModule: Calculation Tools for BusinessDepartment: Course instructors are responsible for the course content descriptions in English.DescriptionStatistical sampling applied to the classic business and on a monetary basis. Advanced techniques for multiple variable analysis, linear and quadratic programming applied to portfolio management.FacultyNameCoordinatorLectureLaboratorySEGURA HERAS, JOSÉ VICENTE■■■MONGE IVARS, JUAN FRANCISCO■■LANDETE RUIZ, MERCEDES■■Professional interestCompetencies and learning outcomesGeneral competenciesCapacity to analyze and synthesize the available information: Study the problems associated with a financial/accounting case, article, or situation, summarize and compile that most relevant, and assess the possible strategic alternatives and its tax incidence in a changing environment.Ability to organize and plan the available resources: Know how to establish the organizational and functional structure of the entity, as well as the strategic management process designed to optimize the entity's economic/financial resources.Capability of expressing technical and ethical opinions on professional activity: Know how to apply acquired knowledge to professional practice such that economic/financial information allows making technical judgments that include reflection on social and ethical responsibilities linked to the tasks of accounting and financial management.Ability to identify, interpret, and resolve problems in unfamiliar environments: Cope with relative ease in complex situations within the business environment and characterized by changes in financial markets and adaptation to accounting and tax regulations, providing solutions and making decisions.Communication and teamwork skills: Clearly communicate financial strategies, accounting criteria, the taxation consequences of the profession, as well as the rationale and knowledge sustaining them, to specialized and unspecialized audiences. Collaborate and cooperate with the team, providing the best knowledge on financial/accounting matters, and accept and appreciate differences of accounting criteria and financial strategies with others.Specific competenciesUnderstand advances in the mathematics of financial operations and their application to accounting and finance.Understand new techniques in actuarial calculation applicable to business accounting and finance.Ability to identify relationships and associations in data analysis in a business environment.Ability to design, construct, validate, and criticize simple and composite indicators in an economic and business environment that facilitate the decision making process.Ability to apply statistical sampling techniques in auditing annual accounts.Objectives (Learning outcomes)El estudiante podrá utilizar las técnicas de muestreo estadístico empleadas en la auditoría de los estados contables.El estudiante conocerá y aplicará las herramientas de la programación matemática básicas para la gestión de una cartera de valoresEl estudiante debe ser capaz de aplicar las principales técnicas de simulación y análisis multivariante a los datos de una empresa.ContentsLecture topicsTeaching unitsMuestreo estadístico clásico y en base monetaria.Programación lineal y cuadrática aplicada a la gestión de carterasTécnicas avanzadas de Análisis Estadístico: Una aplicación a los Indicadores de Coyuntura EconómicaCourse contentsBasic bibliographyFabozzi, Frank J. / Markowitz, H. (Harry), 1927-. "The theory and practice of investment management [electronic resource] asset allocation, valuation, portfolio construction, and strategies". Hoboken, N.J. Wiley c2011. Peña, Daniel 1948-. "Análisis de datos multivariantes". Madrid [etc.] McGraw-Hill 2002. Arriaza Gómez, A.J. "Estadística básica con R y R-Commander". Cádiz Universidad de Cádiz, Servicio de Publicaciones 2008. Chapados, Nicolas, 1972-. "Portfolio choice problems [electronic resource] : an introductory survey of single and multiperiod models /". New York : Springer, c2011. Complementary bibliographyBrentani, Christine. "Portfolio management in practice [electronic resource] /". Oxford : Elsevier Butterworth-Heinemann, 2004. Michaud, Richard O., 1941-. Michaud, Robert O. "Efficient asset management: a practical guide to stock portfolio optimization and asset allocation [electronic resource] /". New York : Oxford University Press, 2008. LinksGeert Molenberghs, Survey Methods (UHasselt) and Sampling Techniques (G0B72a, KU Leuven), Universiteit Hasselt and KU Leuven, Belgium ( OpenCourseWare KU Leuven) https://ocw.kuleuven.be/all-courses/sampling/course.pdf (Accessed September 27, 2014). License: Creative Commons BY-NC-SA 2. SoftwareMicrosoft Office 2010R CommanderRStudioSPSS 22Methodology and gradingMethodologyCase studies: Learning through the analysis of actual or simulated cases in order to interpret and resolve them by employing various alternative solution procedures.Lecture: Pass on knowledge and activate cognitive processes in students, encouraging their participation.Problem-based learning: Develop active learning strategies through problem solving that promote thinking, experimentation, and decision making in the student.Solving exercises and problems: Exercise, test, and apply previous knowledge through routine repetition.GradingPor cada agrupación de contenidos dentro de la materia, la evaluación se realizará mediante un sistema que estará formado por dos componentes:1. Parte práctica: Consistirá en la resolución de un supuesto práctico al terminar una agrupación concreta de contenidos de la materia, calificando esta parte con una puntuación máxima de 7 puntos en función del grado de realización del ejercicio y de la importancia de los errores cometidos. 2. Parte teórica: la parte de teoría tendrá dos orientacionesa) Evaluación teórica continua: En el tiempo de impartición de la materia se realizarán test de autoevaluación. La evaluación continua se considerará aprobada o suspendida a la hora de su consideración en la calificación final, de tal forma que la puntuación final será de 3 para las evaluaciones aprobadas y de cero para las suspendidas.b) Evaluación teórica final: Para aquellos estudiantes que no hayan superado la evaluación continua, al terminar una agrupación concreta de contenidos de la materia, se realizará un test de autoevaluación en los mismos términos que los descritos anteriormente. La calificación de este apartado será como máximo 3 puntosPara superar la asignatura es necesario obtener una calificación final en la parte práctica de 4.La suma de calificaciones en la parte práctica y en la teórica, con las condiciones establecidas, determinará la nota final.