Empirical quantitative methods

Forecasting for Banking Using Time Series Methods

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EARLY BIRD DISCOUNT (-10%) until 23 June

29/09/2025 - 31/10/2025

Location

Online

Download the programme

Click here to download

Registration Deadline

22/09/2025

Level

Advanced, Intermediate

Approach

Quantitative

Delivery mode

Online

This course provides an introduction to time series methods for modeling and forecasting economic and financial variables within a banking context. Forecasting plays a crucial role in decision-making for both the public and private sectors and is especially significant for banking institutions, whether in management or supervision. Banks’ assets and liabilities are shaped by various factors, including economic and financial conditions, interest rates, and the prices of financial assets. These variables emerge from a vast, complex, dynamic, and stochastic system, making accurate forecasting a challenging task where errors are inevitable. However, by applying appropriate econometric models and methods, forecast errors can be minimised, and forecasting precision can be significantly improved.

Topics

Module 1: Modelling economic and financial variables (ARMA) + Empirical application in Eviews using simulated and actual economic and financial data
Module 2: Forecasting economic and financial variables using the ARMA model + Empirical application in Eviews using simulated and actual economic and financial data (focusing on forecasting and forecasting performance)
Module 3: Modelling and forecasting economic and financial variables using VAR models + Empirical application in Eviews using simulated and actual economic and financial data (focusing on forecasting and shock transmission)
Module 4: Cointegration and error correction models + Empirical application in Eviews using simulated and actual economic and financial data (focusing on cointegration analysis and forecasting)

Develop skills in specifying, estimating, and evaluating univariate ARIMA models and multivariate VAR models for macroeconomic and financial variables relevant to the banking sector
Learn to construct point, interval, and density forecasts
Understand shock identification and transmission mechanisms
Explore the interaction between short-run and long-run dynamics through ECM modeling

This course combines self-paced materials with live online activities to provide a flexible and engaging learning experience.

You will access course materials and interact with instructors, teaching assistants, and fellow participants directly from your own devices. The course includes video lectures for exploring theoretical concepts, complemented by small work assignments and lab sessions. During these live online sessions, you will engage in practical exercises using EViews, guided by the course instructor and teaching associates.

The format ensures ample opportunities for Q&A and collaboration. You will benefit from close guidance throughout the course, with multiple chances to receive individual feedback and interact with both the instructor and teaching assistants.

Time required from participants: 20 hours

Massimiliano Marcellino

Professor of Econometrics in the Economics Department

Bocconi University

View Massimiliano Marcellino profile

29 September

Start of the course
Access to all course modules

2 October

15:00 – 16:30 Live ‘Brush up’ Session

3 October

15:00 – 17:00 Teaching Assistant-led office hours

9 October

15:30 – 17:30 First live class: recap of modules 1-2 + Q&A

14 October

15:00 – 17:00 Announcement of the competition and Teaching Assistant-led office hours

15 October

15:00 – 17:00 Second live class: Lab 1
17:00 – 18:30 Teaching Assistant-led office hours

23 October

15:00 – 17:00 Third live class: recap modules 3-4 + Q&A

27 October

15:00 – 17:00 Fourth live class: Lab 2
17:00 – 18:30 Teaching Assistant-led office hours

30 October

Deadline for competition submission

31 October

16:00 Announcement of competition results during final live class.
End of the course

FULL FEES applicable from 24 June onwards*:

€ 850 – Academics
€ 1150 – Public sector
€ 1250 – Private sector

*Please note that the payment must be settled one week before the start of the course.

The fee includes tuition, access to all course materials and pedagogic activities, coffee and lunch breaks and social activities, as well as a certificate of attendance after the course has been completed. The fee does not include travel and accommodation expenses or other local transportation costs (taxis, private cars).

Please submit a certificate attesting your status of Professor, PhD Student or Research Associate to fbf@eui.eu before registering. FBF secretariat will provide you with a code to register. Seats for academics are limited.

EARLY BIRD DISCOUNT (-10%), applicable until 23 June COB:

Participants are eligible for the below early bird discount if they register and pay by 23 June 2025. Please note that those who wish to pay a reduced fee for academics must send proof of academic status to fbf@eui.eu in order to verify their eligibility.

€ 765 – Early bird academic*/ € 850 full fee (from 24 June)
€ 1035 – Early bird public sector / € 1150 full fee (from 24 June)
€ 1125 – Early bird private sector / € 1250 full fee (from 24 June)

GROUP DISCOUNT (-15%) for minimum 3 participants from the same institution registering at the same time (always applicable):

A group discount is available for institutions registering three or more participants. To qualify, the names of all participants must be submitted together in a single email to FBF. Please note that this offer cannot be applied retroactively to individual registrations completed at different times. Those wishing to take advantage of the group discount must write an email to fbf@eui.eu, stating the full names of the proposed participants.

€ 722,50 – Group discount academic
€ 977,50 – Group discount public sector
€ 1062,50 – Group discount private sector

CANCELLATION POLICY

Paid registration fee is non-refundable. However, registrant substitution may be made up to 15 days before the start date of the course by contacting fbf@eui.eu.

For any questions, please contact us at fbf@eui.eu and/or noemi.epote@eui.eu.

Forecasting for Banking Using Time Series Methods

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