High-Frequency Data Econometrics

Date: 26-29 September 2016

Location: Aarhus University

Price: 0 DKK / 1000 DKK (see below)


Course content

The course covers topics from the recent developments in high-frequency econometrics.

We will review the econometrics of non-parametric estimation of the variation of asset prices. This very active literature has been stimulated by the recent advent of complete records of transaction prices, quote data and order books. The interaction of the new data sources with new econometrics methodology is leading to a paradigm shift in one of the most important areas in econometrics: Volatility measurement, modeling and forecasting using high-frequency data.

Careful data cleaning is one of the most important aspects of volatility estimation from high-frequency data. The most challenging problem in this context is dealing with various forms of market frictions, which obscure the latent price from the econometrician. We will characterize types of statistical models of friction and discuss how econometricians have been attempting to overcome them. The main data focus will be on the TAQ data base.


Course materials

The programme and course agenda is preliminary. A reading list and updated course information will be available in mid August.

Sofware and IT requirements

  • Students must bring their own laptop.
  • MATLAB must be installed on computer.


  • 0 DKK including course dinner: for DGPE students and BigDataFinance students
  • 1000 DKK including course dinner: all other external participants

The Danish Graduate Programme in Economics (DGPE) is a research network for graduate students in economics.  DPGE offers a range of specialized PhD courses within: Microeconomics, Macroeconomics, and Econometrics. The lecturers are international experts within the respective course topics.

The courses are free of charge for DGPE members from AU, KU, CBS, SDU, as well as participants from Economics departments at other Nordic universities.

BigDataFinance 2015–2019, a H2020 Marie Sklodowska-Curie Innovative Training Network “Training for Big Data in Financial Research and Risk Management”, provides doctoral training in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 researchers.