STATISTICAL ANALYSIS OF ECONOMIC SERIES CourseCode: 2186Degree: Bachelor's in Business Administration and ManagementFaculty of Social and Legal Sciences of ElcheYear: Year 4 of Bachelor's in Business Administration and ManagementSemester: SpringType: ElectiveLanguage: SpanishECTS credits: 6Lecture: 3Laboratory: 3Hours: 150Directed: 60Shared: 20Autonomous: 70Subject matter: Program ElectivesModule: Transversal and Professional CompetenciesDepartment: Statistics, Mathematics and InformaticsArea: STATISTICS AND OPERATIONS RESEARCHCourse instructors are responsible for the course content descriptions in English.DescriptionIntroduction to time series. Moving averages and exponential smoothing models. ARIMA models. Heteroscedastic models for finance: ARCH and GARCH. Structural equation modeling.FacultyNameCoordinatorLectureLaboratoryBARBER VALLES, JOSEP XAVIER■MARTIN GONZALEZ, CRISTINA■■Professional interestCompetencies and learning outcomesGeneral competenciesAbility to use the tools and instruments needed to properly observe the systems under study.Ability to implement efficient tools for troubleshooting within the branch of social and legal sciences.Critical and analytical skills in the relevant specialty area.Capacity to evaluate, optimize, and compare criteria in decision making.Ability to communicate in formal, graphic, and symbolic styles, as well as with oral and written forms of expression.Ability to work with multidisciplinary and multicultural teams.Specific competenciesAbility to analyze general problems within the field of microeconomics and macroeconomics.Capacity to perceive and value the importance of new technologies within the business environment and its economic surroundings.Capacity to analyze general problems in the field of business and markets.Capacity to use and interpret business data and information for specialized reporting and decision making.Capacity for quantitative problem solving.Objectives (Learning outcomes)01Conocer los elementos básicos y estudios consecutivos en la modelización de un banco de datos.02Aprender a descubrir pistas que orientan a la modelización de un problema, en función de los objetivos propuestos y la representación de los datos.03Conocer los fundamentos del análisis de series temporales.04Ajustar el modelo correspondiente sobre bancos de datos apropiados y extraer conclusiones.05Conocer los fundamentos del Estudio Clásico y Estudio Bob-Jenkins de series temporales.06Conocer los procedimientos básicos para evaluar la calidad del ajuste del modelo.07Capacidad para proponer transformaciones de un primer ajuste.08Conocer los fundamentos de las series multivariantes09Manejar con destreza el programa SPSS/R-Commander que permita obtener los objetivos propuestos010Saber interpretar los resultados y proponer predicciones para cualquier serie económica planteada.ContentsLecture topicsTeaching unitsU1INTRODUCCIÓN. MODELOS CLÁSICOSU2PROCESOS ESTOCÁSTICOS ESTACIONARIOS UNIVARIANTESU3MODELOS ESTACIONARIOS: MODELOS ARMAU4MODELOS NO ESTACIONARIOS: MODELOS ARIMAU5MODELOS ESTACIONALES: MODELOS SARIMAU6ANÁLISIS BOX-JENKINSU7INTRODUCCIÓN AL ANÁLISIS DE SERIES MULTIVARIANTESScheduleWeekTeaching unitsDirected hoursShared hoursAutonomous hoursTotal hours1U140042U142283U240264U242285U341496U3424107U340598U3425119U44151010U44251111U54061012U64281413U64081214U64281415U744614Course contentsBasic bibliographyPeña, Daniel. "Análisis de series temporales". Madrid Alianza Editorial 2005. Makridakis, Spyros. Wheelwright, Steven C., (1943-) / Hyndman, Rob J. "Forecasting methods and applications". New York [etc.] John Wiley and Sons cop1998. Uriel Jiménez, Ezequiel. "Análisis de series temporales modelos Arima". Madrid Paraninfo 1995. Pankratz, Alan. "Forecasting with dynamic regression models". New York [etc.] John Wiley & Sons cop. 1991. Wei, William W. S. "Time series analysis univariate and multivariate methods". Redwood City (Calif.) Madrid [etc.] Addison-Wesley cop. 1990. Complementary bibliographyPankratz, Alan. "Forecasting with univariate box-jenkins models : concepts and cases". New York [etc.] John Wiley and Sons cop. 1983. URIEL JIMÉNEZ, Ezequiel. "Estadística económica y empresarial teoría y ejercicios". Madrid AC D.L.1993. Linkshttp://SoftwareR-UCA (R y R-Commander)SPSS 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.Cooperative learning: Develop active learning through cooperative working strategies among students and promote shared responsibility to reach group goals.Lecture: Pass on knowledge and activate cognitive processes in students, encouraging their participation.Project-based learning: Realization of a project to solve a problem, applying acquired learning and promoting abilities related to planning, design, performing activities, and reaching conclusions.Solving exercises and problems: Exercise, test, and apply previous knowledge through routine repetition.GradingSe utilizará una evaluación continuada que estimule al estudiante a seguir el proceso de aprendizaje. El peso de la evaluación continua en el que se valorarán las actividades realizadas en las clases teóricas y prácticas, desarrollo del portafolio de prácticas (20%) y el trabajo en los seminarios y seguimiento de tutorías (15%) de la calificación final; será el 35 % de la asignatura.Se realizará un examen final, con preguntas objetivas sobre aspectos teóricos y prácticos de la asignatura en aula informática, que tendrá un peso en la calificación de un 65%.