PREDICTIVE BUSINESS AND FINANCE

Anno accademico
2021/2022 Programmi anni precedenti
Titolo corso in inglese
PREDICTIVE BUSINESS AND FINANCE
Codice insegnamento
EM1415 (AF:339192 AR:180105)
Modalità
In presenza
Crediti formativi universitari
6
Livello laurea
Laurea magistrale (DM270)
Settore scientifico disciplinare
SECS-P/05
Periodo
1° Periodo
Anno corso
2
Sede
VENEZIA
Spazio Moodle
Link allo spazio del corso
This course is one of the teaching activities of the Master's Degree Programme in "Data Analytics for Business and Society". In tandem with the educational objectives of this course, students will be exposed to data analytic techniques and methods for handling economic-financial prediction related problems. Precisely, this activity seeks to present the main mathematical and statistical tools necessary for forecasting.
1. Visualize time series data
2. Specify appropriate metrics to assess forecasting models
3. Use smoothing methods with time series data (moving average, exponential smoothing)
4. Understand the different components of time series data5
5. Use regression methods for forecasting
Mathematical Tools:
Matrix Algebra
Differential Calculus
Integral Calculus

Statistical Tools:
Random Variables and Distribution Theory
Point and Interval Estimation
Hypothesis Testing
Least Squares and Standard Linear Model
1. Regression models
2. Time series models: ARIMA models.
3. Dynamic regression models
4. Advanced forecasting methods
Hyndman, R. J. and G. Athanasopoulos (2018): Forecasting: Principles and Practice (2nd Edition). https://otexts.com/fpp2/
By way of evaluation, two (i.e. mid and end of course) main examinations covering both the theory and application of the concepts developed in class will be conducted. However, I will also propose an end-of-course project (homework) that examines students' capability in developing a solution to a problem without limiting themselves to the information given in class. The course grade will be based on homework and a final examination. The final grade will be determined using the following weights: 30\% Homework, 70\% final written exam.
Series of lectures on the various topics
Inglese
scritto
Programma definitivo.
Data ultima modifica programma: 13/09/2021