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Macroeconometrics

Nowcasting and Forecasting Extreme Events

Real-Time Insights: Nowcasting and Forecasting in Uncertain Times.

20h (10 days)

€795 - €1,375

Online

English

Program date: March 02-13, 2026

Early bird deadline: January 19, 2026

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Macroeconometrics

Nowcasting and Forecasting Extreme Events

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Who is this Course for?

Nowcasting and Forecasting Extreme Events

Course overview

Recent years have underscored how unprecedented crises from financial collapses to pandemics and geopolitical conflicts can transform economies in an instant. Traditional data and models often fail to capture the speed and scale of these disruptions.

This course explores how high-frequency data can be used to detect, monitor, and anticipate major economic disruptions in real time. It responds to the growing need for faster and more effective tools in an era marked by frequent shocks,ranging from financial crises to pandemics and geopolitical events.

It is uniquely designed for professionals seeking to move beyond traditional macroeconomic methods and gain a decisive edge in anticipating and responding to complex, fast-evolving crises.

Whether you’re looking to build a strong foundation or enhance your current skill set, this course provides both the theoretical insights and practical tools to support real-world economic analysis.

Faculty

Discover what makes this Nowcasting and Forecasting course exceptional

1

Real-Time Economic Monitoring:Learn to work with high-frequency data for early detection of shocks and rapid situational analysis.

2

Crisis Anticipation Tools: Gain skills to identify structural risks and early warning signals before major disruptions occur.

3

Bridges Theory and Practice: Combines advanced data analytics with applied macroeconomic insights tailored to real-world crises.

4

Beyond Traditional Macroeconomics:Focused on modern methods that address the limitations of conventional economic models in fast-moving environments.

5

Designed for Decision-makers:Tailored for professionals who need actionable tools to respond to and anticipate complex economic challenges.

6

Interdisciplinary Approach:Integrates data science, macroeconomics, and risk analysis to provide a comprehensive toolkit for crisis management.

Who is this course for?

Practitioners at central banks as well as other private and public institutions which need to provide economic analysis in real time
Masters and PhD students in economics or related fields that want to incorporate in their work real time tools or want to develop new tools to analyze economic activity
Researchers that want to learn about uncertainty and decision making in real time
Students in any quantitative field that want an overview of the techniques used in real economic analysis and incorporate these techniques to their own field

Learning outcomes

By the end of this course, participants will be able to:

Analyze high-frequency economic data to monitor and measure real-time responses to extreme events
Identify and interpret early warning signals of major economic disruptions using advanced analytical tools
Evaluate the role of structural imbalances and disequilibria in triggering extreme economic events
Apply real-time data frameworks to assess the magnitude and dynamics of economic shocks as they unfold
Develop evidence-based strategies to anticipate and respond to unforeseen crises
Integrate traditional macroeconomic insights with high-frequency monitoring to enhance situational awareness and policy or business decision-making

Key topics for Nowcasting and Forecasting Extreme Events course

Take a look at the themes covered during this course.

Challenges and Opportunities of High-Frequency Data

Key challenges in working with high-frequency data
Modeling and forecasting with high-frequency data: principal component methods
Integrating high-frequency data with standard information sets: Kalman filtering with mixed frequencies
Nonlinear models for high-frequency data: Markov switching and regime-change dynamics
Special topics:
- Data selection strategies
- Seasonality adjustments
- Signal-to-noise issues in high-frequency environments

Predicting the Unthinkable

Identifying turning points in real time: dynamic nonlinear factor models
Understanding the role of disequilibrium in predicting crises: duration models
Selecting significant disequilibria using machine learning algorithms
Advanced techniques for forecasting extreme events: Random Forest and XGBoost

Course Materials and Software

MATLAB License

Every participant will receive a time-limited personal free MATLAB license before the course starts. You’ll need to install it on your own computer for practical sessions
Additional materials will be provided, and instructors will be available to discuss your research ideas and projects throughout the course

List of References

Below are some resources that may help you prepare for the course.

Books

James Hamilton. “Time Series Analysis” Princeton. (1994).
Chang-Jin Kim, Charles R. Nelson. “State-Space Models With Regime Switching: Classical and Gibbs-Sampling Approaches With Applications”. MIT Press (1999).
Andrew Blake and Haroon Mumtaz. “Applied Bayesian Econometrics for Central Bankers” (2007). Bank of England.
Helmut Lütkepohl “New Introduction to Multivariate Time Series Analysis”. (2005).
Fabio Canova.” Methods for Applied Macroeconomic Research” (2007)
Specific references for our course will be:
Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. “The MIDAS Touch: Mixed Data Sampling Regression Models,” CIRANO Working Papers 2004s-20, CIRANO.
Hale, T, A Petherick, T Phillips, S Webster, B Kira, N Angrist and L Dixon (2020), “Oxford COVID-19 Government Response Tracker”, Blavatnik School of Government, Oxford University
Lewis, D., K. Mertens, and J. Stock. 2020. “Monitoring Real Activity in Real Time: The Weekly Economic Index,” Federal Reserve Bank of New York Liberty Street Economics, March 30.
Chetty, Raj, John N. Friedman, Nathaniel Hendren, Michael Stepner, and the Opportunity Insights Team (2020). “How Did COVID-19 and Stabilization Policies A§ect Spending and Employment? A New Real-Time Economic Tracker Based on Private Sector Data,” mimeo, Harvard University.
Perez Quiros, G. and Saiz, L. “Introducing the Eurotracker” ECB Mimeo 17) Gonzales, F, A Jaax and A Mourougane (2020), “Nowcasting aggregate services trade. A pilot approach to providing insights into monthly balance of payments data”, Paris: OECD Publishing.
Manuel Medina Magro (2022) Nowcasting The USA Real Quarterly GDP Growth With a Seasonally Adjusted Weekly Economic Index. U. of Alicante (mimeo)
Sercan Eraslan & Thomas G ö tz. (2021). “An unconventional weekly economic activityindex for Germany”. Economics Letters, Volume 204, 109881, ISSN 0165-1765.
Woloszko, N (2020), “A Weekly Tracker of activity based on machine learning and Google Trends”, OECD Economics Department Working Papers 1634, Paris: OECD Publishing.
Maccarrone G, Morelli G, Spadaccini S. GDP Forecasting: Machine Learning, Linear or Autoregression? Front Artif Intell. 2021 Oct 15;4:757864.

Articles and Working Papers

Lewis, D., K. Mertens, and J. Stock (2020): “U.S. Economic Activity During the Early Weeks of the SARS-Cov-2 Outbreak,” FRB Dallas Working Paper, 20-11.
Christiane Baumeister, Danilo Leiva-León & Eric R. Sims. “Tracking Weekly State-Level Economic Conditions” NBER Working Paper 29003. July 2021 19) Cuevas, Á., Ledo, R. & Quilis, E.M. Seasonal adjustment of the Spanish sales daily data. SERIEs 12, 687–708 (2021).
Camacho, M. and Perez Quiros G. (2010) “Introducing the euro-sting: Short-term indicator of euro area growth” Journal of Applied Econometrics, Volume25, Issue 4
Schorfheide, F and Song, D. (2021) Real-Time Forecasting with a (Standard) MixedFrequency VAR During a Pandemic “Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic”. NBER Working paper 29535
Leiva Leon, D, Perez Quiros, G and Rots, E. Real-time weakness of the global economy a first assessment of the coronavirus crisis. ECB Working Paper 2381. March 2020
Eo, Y. and C.-J. Kim (2016). Markov-switching models with evolving regime-specific parameters: Are postwar booms or recessions all alike? Review of Economics and Statistics 98 (5), 940–949.
Bai, Jennie, Eric Ghysels and Jonathan Wright (2010), “State Space Models and MIDAS Regressions.” Econometric Reviews Volume 32, 2013 – Issue 7

Why should you attend BSE Executive Education courses?

All BSE Executive Education courses are taught to the same high standard as our Master’s programs.

1

Network with like-minded peers from around the world

2

Short courses allow you to learn without a big time commitment

3

Try something new and expand your knowledge and career prospects, or advance your thesis

Testimonials

IK

Ioannis Krompas

The course provided valuable insights into leveraging high-frequency data for real-time economic forecasting. I gained a deeper understanding of nowcasting techniques and their practical applications, which I look forward to applying.

Read less

Admissions

If you want to apply for this Nowcasting and Forecasting course, ensure you meet the criteria below.

Program date: March 02-13, 2026

Early Bird deadline: January 19, 2026

Requirements

Candidates are assessed on an individual basis according to their professional or academic background
Students must have their own laptop or desktop computer and good Internet connection to be able to follow and fully benefit from the course

Nowcasting and Forecasting Extreme Events Requirements

Knowledge of mathematics and/or statistics at graduate level could help to take further advantage of the course although it is not mandatory

Course Schedule

The times listed are Central European Time (CET). Compare with your time zone on time.is

Instructors, topics, and schedules are subject to change.

Week 1

Time

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Mon

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Tue

3
Wed

4
Thu

5
Fri

16:45-18:45

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Practical

Lecture

Practical

Lecture

Week 2

Time

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Mon

2
Tue

3
Wed

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Thu

5
Fri

16:45-18:45

Practical

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Practical

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Certificate and Fees

Certificate

Participants who attend at least 80% of the course will receive a Certificate of Attendance free of charge. Participants will not be graded or assessed during the course.

Fees

A 10% discount applies when the confirmation payment is completed on or before the announced Early Bird deadline.

Multiple course discounts are available. Find out more information in our Fees and Discounts pdf.

Fees for courses in other Executive Education programs may vary.

Course

Nowcasting and Forecasting Extreme Events

Modality

Online

Total Hours

20

ECTS

0

Regular Fee

1,375€

Reduced Fee*

795€

*Reduced Fee applies for PhD or Master’s students, Alumni of BSE Master’s programs, and participants who are unemployed.

FAQ

Need more information? Check out our most frequently asked questions.

Are the sessions recorded?

Sessions will be recorded and videos will be available for a month once the course has finished.

How much does each Executive Education course cost?

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Yes, BSE offers a variety of discounts on its Executive Education courses. See more information about available discounts or request a personalized discount quote by email.