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‘Economic Forecasting for Banking’ training course

On 5-7 November 2018, the Florence School of Banking and Finance organised an executive training course on ‘Economic Forecasting for Banking’, which provided a primer on econometric methods for forecasting economic and financial variables relevant in a banking context, discussing also some more advanced topics related to forecast construction and evaluation.

The rationale behind this course lays in the fact that forecasting is a key ingredient of decision making, both in the public and in the private sector, and is particularly important in the context of banking for their management as well as for their supervision. In fact, banks’ assets and liabilities are influenced by a number of factors, such as general economic and financial conditions, interest rates, and the prices of financial assets. These variables are however the result of a vast, complex, dynamic and stochastic system.
This course taught to the participants the theoretical and practical elements to forecast these variables appropriately, reducing the errors and enhancing the forecast prediction by using the proper econometric models and methods.

The course was taught by Massimiliano Marcellino, professor of Econometrics in the Economics Department of Bocconi University and Scientific Advisor at the Florence School of Banking and Finance. Theoretical sessions covered the linear regression models for evaluating financial variables, including considerations on selecting the variables and measuring the goodness of fit, as well as handling instability and dynamics. In parallel, the instructor conducted practical sessions, during which participants were led through concrete applications of the theory on economic and financial variables, both simulated and actual.

Participants appreciated the course design, the instructor, as well as the overall organisation of the course. Asked for a personal feedback, a participant commented as follows: This course was quite interesting and well structured, with dense information and many practical exercises. The presenter showed remarkable training skills and was notably able to describe theoretical aspects with examples and clear explanations, allowing non-specialists to better understand the concepts taught.

Another participant reported that taking this course ‘has been an excellent choice and a great experience. I’ve improved my knowledge about forecasting models, met colleagues working at relevant institutions and enjoyed the wonderful installations of the Institute‘.