21 August 2021
Econometric Methods for Forecasting and Data Science with Applications in Finance, Economics and Business
The importance of developing appropriate quantitative models and methods for risk-assessment, climate-impact scenarios, energy policy, house market prices, and big data analyses generally are well understood in the academic and professional worlds. The developments in new technologies for econometric modelling, analysis and forecasting of (big) data in finance, economics and business are moving forwards rapidly. In this summer school we will treat a number of these developments in much detail. In each case we start with the basics of the methodology and theory, we illustrate their use and their importance, we implement the basic methods in a computer lab, and we review the latest developments in the academic and professional literature. Given the interdisciplinary nature of the summer school, we start with a review of the basic methods and theory in each case. More specifically, we aim to treat the latest developments in univariate time series models, dynamic econometric models, volatility models, dynamic factor models, state space models, time-varying location and scale models, etc. The practical use of econometric methods in the context of specific applications are assessed in individual cases targeted towards the backgrounds of the participants.
Despite the Covid-19 outbreak we still expect that the BDS summer school courses can take place. In the unfortunate event that we are not able to offer courses due to tightened national regulations, you will receive a full refund of your payment to the BDS courses. If this is the case, we will inform all applicants accordingly via email asap.
The 2020 lecturers are Professor Siem Jan Koopman (Vrije Universiteit Amsterdam, Tinbergen Institute) and Francisco Blasques (Vrije Universiteit Amsterdam, Tinbergen Institute).
Siem Jan Koopman is Professor of Econometrics
The summer course welcomes (research) master students, PhD students and post-docs with a quantitative background and who are interested in learning state-of-the art econometrics and data science forecasting methods.
A formal background in quantitative studies (mathematics, statistics, econometrics, engineering, etc.) is required from students (at the level of a first year course in a Master study), but no formal background in Econometrics or Statistics will be assumed.
We aim to treat the latest developments in univariate time series models, dynamic econometric models, volatility models, dynamic factor models, state space models, time-varying location and scale models, etc. The practical use of econometric methods in the context of specific applications are assessed in individual cases targeted towards the backgrounds of the participants.
Participants who joined at least 80% of all sessions will receive a certificate of participation stating that the summer school is equivalent to a work load of 3 ECTS. Note that it is the student’s own responsibility to get these credits registered at their university.
EUR 1000: PhD and Master Students
EUR 1500: Postdocs