Time Series Methods for Risk Analysis

Course overview

The Barcelona School of Economics Intensive Course on ​​Time Series Methods for Risk Analysis provides an introduction to state-of-the-art techniques for the analysis of risk in finance and macroeconomics. 

The first part of the course introduces univariate time series models used for the analysis of time-varying volatility (GARCH models); multivariate time series models for the analysis of time-varying correlations (DCC models) as well as quantile regression for the analysis of downside risk. 

The second part of the course presents empirical applications. In the first application, GARCH-DCC models are used to construct a number of systemic risk measures recently proposed in the literature (CoVaR, MES, SRISK). In the second application GARCH models and quantile regression are used for Growth-at-Risk forecasting. 

The course includes theory sessions (10 hours) and practical sessions (10 hours). During the practice sessions, students will use MATLAB to replicate the methodology as well as the empirical findings documented in the lectures.

Course director

facultyLuca Gambetti


Course instructor

facultyChristian Brownlees


Key benefits

  • Understand state of the art models for volatility and risk, and for time varying large dimensional covariance matrices
  • Apply the methodology studied in the lectures to study risk in financial and macro applications
  • Evaluate the accuracy of risk forecasts in financial and macro applications

Course dates: February 28 - March 11, 2022

Apply to Time Series Methods for Risk Analysis

Early-bird payment deadline: January 14, 2022

Applications close: February 7, 2022

See below for reduced fee eligibility or email us to request more information

This course is part of the BSE Macroeconometrics study itinerary. You may also be interested in this related course:

See all available Macroeconometrics courses below