NMAK24011U Financial Econometric Time Series Analysis (FinMetrics)

Volume 2024/2025

MSc Programme in Mathematics-Economics

MSc Programme in Statistics

MSc Programme in Actuarial Mathematics


The course gives an introduction to the mathematical statistical and econometric analysis of time series data with emphasis on financial time series data. Various applications are considered, e.g. risk management, forecasting and derivatives pricing.

Specifically we consider univariate linear time series models for the conditional mean (autoregressive processes, or AR) and nonlinear time series models for higher order moments including autoregressive conditional heteroskedastic (ARCH) models. In addition, multivariate extensions are considered, including vector autoregressive (VAR) models, and multivariate ARCH (MGARCH) models.

The stochastic properties of the processes are analyzed in detail in terms of stationarity and dependence. Statistical analysis is likelihood-based, and we consider asymptotic theory for estimators and test-statistics.

The modeling is illustrated empirically using standard statistical software.

Learning Outcome


  • Account for properties of stochastic processes used for financial time series modelling. This includes strict stationarity, mixing, and geometric ergodicity.
  • Account for properties of maximum likelihood estimators and test-statistics.



  • Analyze stochastic properties of time series proceses.
  • Establish likelihood-based estimators asymptotic distributions, and clarify under what conditions properties hold.
  • Implement estimation of financial time series models in statistical software.
  • Discuss the suitability of a given time series models for typical finanical empirical applications.


  • Apply the acquired knowledge and skills in new contexts. For example the student should be able to analyze richer classes of models and carry out estimation of these.
  • Ability to read leading and novel journal articles within financial econometrics.

Literature will be announced in Absalon.

MStat, Sand2 and Finansering 1.

Academic qualifications equivalent to a BSc degree is recommended.
4 hours of lectures and 2 hours of exercises per week for 7 weeks.
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 136
  • Theory exercises
  • 14
  • Project work
  • 25
  • Exam
  • 3
  • Total
  • 206
Continuous feedback during the course of the semester
7,5 ECTS
Type of assessment
On-site written exam, 3 hours under invigilation
Exam registration requirements

Two mandatory written assignments (mid and final term tests) must be handed in and approved.

Without aids

The exam is closed book.

Marking scale
7-point grading scale
Censorship form
External censorship

30 minutes oral exam, no preparation time and no aids.

Mandatory assignment(s) that have not been approved or are invalid must be handed in no later than three weeks before the start of the re-exam period and approved.

Criteria for exam assesment

The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.