Last 2019 course: ‘Forecasting for Banking Using Time Series Methods’
The last residential training course of 2019 at the Florence School of Banking and Finance was held on 27-29 November 2019 and was centered on the topic of ‘Forecasting for Banking Using Time Series Methods’.
This course aimed at introducing the use of time series methods for modelling and forecasting economic and financial variables relevant in a banking context. Since forecasting is a key ingredient of decision making both in the public and in the private sector, in the context of banking it is particularly important for their management and for their supervision.
The course was taught by Massimiliano Marcellino, professor of Econometrics in the Economics Department of Bocconi University and fellow of CEPR and IGIER, who has published over ninety academic articles in leading international journals on forecasting, econometrics, and empirical macroeconomics.
Professor Marcellino started the course by introducing the main macroeconomic and financial drivers of banking performance and the use of the ARIMA model for assessing the related economic and financial variables. After having discussed the tests and formulae for performing forecasting in this model, the instructor led two practical sessions using the software EViews, on simulated and actual economic and financial data.
The following sessions were concentrated on the theory and practice on modelling and forcasting economic and financial variables using VAR models, with a specific focus on impulse-response functions and forecast error variance decompositions. Finally, the course was closed by sessions on cointegration ananlysis and on Error Correction Models. As done in the previous sessions, the theoretical elements were followed by practical exercises led using the software EViews.
An anonymous course participants, asked to comment on the course, provided the following testimonial:This course was very well structured, intriguing and helpful. The lecturer was a master in the field but great in simplifying complex problems so that the lecture was easy to follow. Thanks for this great experience.