Financial Econometrics

Are you looking to gain additional skills in financial econometrics? Would you like to improve or brushup your knowledge of financial econometrics? The certificate of Financial Econometrics provides participants with an understanding of how to implement and use advanced financial econometric techniques for high-quality risk modeling and data-driven portfolio optimization. We follow a hands-on approach and cover all practical aspects of data-driven financial volatility modeling and risk measurement. We focus on the practical design and estimation of volatility models, data-driven portfolio optimization and advanced methods in financial risk measurement. This certificate can be completed using either MATLAB, python or R.

Program Modules

Module 1 (one full day of training):Econometrics for Financial Risk Modeling. This module covers the design and estimation of conditional volatility models of the ARCH and GARCH type. Participants learn how to filter conditional volatilities from stock prices and other financial time-series. Additionally, participants will learn to use these models to calculate time-varying loss probabilties and extract risk measures such as the Value-at-Risk.

Module 2 (one full day of training):Data-Driven Portfolio Optimization. This module expands on the methods covered in Module 1, and covers the design and estimation of multivariate conditional volatility models of the CCC and DCC type. Participants learn how to filter time-varying conditional volatilities and correlations between stocks. Additionally, participants will learn to use these models to optimize financial portfolios that maximize expected return and minimize risk.

Module 3 (one full day of training): Advanced Models of Financial Risk. This module expands on the methods covered in the previous two modules, and covers the design and estimation of advanced conditional volatility models. Participants learn how to filter time-varying conditional volatilities that are robust to outliers and incorporate leverage effects. Additionally, participants will learn to use these most recently developed models to calculate robust time-varying loss probabilities and extract risk accurate measures of financial risk.

Module 4 (one full day of training): State Space Models of Financial Risk. This module introduces participants to parameter-driven models of conditional volatility. In particular, it covers the design and estimation of the dynamic stochastic volatility model. Additionally, participants will learn to use these models to calculate time-varying risk measures.

Certificate

The certificate is composed of four one-day modules:
  • Econometrics for Financial Risk Modeling
  • Data-Driven Portfolio Optimization
  • Advanced Models of Financial Risk
  • State Space Models of Financial Risk

Each module is a one-day course (9am to 5 pm) and can be taken separately. Successfully completing all modules will grant you the certificate diploma in "Financial Econometrics".



Professionals working on data science in business, finance and economics. Professionals that work with time series data, whose work involves forecasting and prediction. Researchers on think tanks and research institutes, phd researchers using time-series data.
Module 1: 8 May 2020
Module 2: 15 May 2020
Module 3: 22 May 2020
Module 4: 29 May 2020

Francisco Blasques is an associate professor at the department of the Department of EconometricsVrije Universiteit Amsterdam and a research fellow at Tinbergen Institute. He obtained his PhD at the University of Maastricht. He has been a visiting researcher at the Central Bank of Portugal, a director of the bachelor and master programs of Econometrics and Operations Research, and is currently director of doctoral research at the School of Business and Economics of the Vrije Universiteit Amsterdam. His research interests include econometric theory, time-series econometrics, and dynamic modeling. Francisco Blasques has experience in delivering data science training and consultancy services for private companies and governmental institutes alike. He has teaching experience at both graduate and undergraduate levels. Currently he teaches courses in advanced econometrics and time-series analysis at both the Vrije Universiteit Amsterdam and the Tinbergen Institute.

Siem Jan Koopman is a Professor of Econometrics at the Department of EconometricsVrije Universiteit Amsterdam. He is also a research fellow at Tinbergen Institute and a long-term Visiting Professor at CREATES, University of Aarhus. Furthermore, he is a Journal of Applied Econometrics Distinguished Author, and Fellow of the Society of Financial Econometrics (SoFiE). He held positions at London School of Economics and CentER (Tilburg University), and had long-term visits at US Bureau of the CensusEuropean University Institute, and European Central Bank, Financial Research. Siem Jan Koopman is listed among the top 40 economists in The Netherlands in 2019 according to ESB. The research interests of Siem Jan Koopman cover topics in time series econometrics, financial econometrics, forecasting and simulation-based estimation. His current research focusses on score-driven time-varying parameter models (GAS models), state space models and dynamic factor models. He fulfills editorial duties at Journal of Business and Economic StatisticsJournal of Applied Econometrics, and Journal of Forecasting. He currently teaches courses in time-series econometrics, state-space modeling and financial econometrics.

Andre Lucas is a Professor in Financial Econometrics and head of the Department of EconometricsVrije Universiteit Amsterdam. He has been a director of graduate studies for finance at Tinbergen Institute, program director of Risk Management at Duisenberg school of finance, program director of the MSc Finance program at Vrije Universiteit Amsterdam, and vice dean of research and member of the faculty board at the School of Business and Economics. Andre Lucas is listed among the top 40 economists in The Netherlands in 2019 according to ESB. His research interests include financial econometrics, risk and asset management, focusing particularly  on model instability and time-variation of model parameters. For this, he and his co-authors have developed the class of generalized autoregressive score models (http://gasmodel.com) for which he obtained the prestigious VICI grant of NWO (2010-2015). He also participated as one of the principal investigators in the EU funded network on systemic risk tomography (2013-2016). His PhD students were placed at multiple world-leading institutions including: FED Boston, ECB, Riksbank, Gothenberg University, University of Sydney, Smurfit Business School Dublin, Dutch Central Bank. He currently teaches courses in econometrics, statistics and empirical finance.

 

For more information, you can always contact us through e-mail. Send your queries to F. Blasques at executive.econometrics.sbe@vu.nl.