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Module (6 Credits)

Financial Econometrics


Name in diploma supplement
Financial Econometrics
Responsible
Prof. Dr. Yannick Hoga
Admission criteria
See exam regulations.
Workload
180 hours of student workload, in detail:
  • Attendance: 60 hours
  • Preparation, follow up: 60 hours
  • Exam preparation: 60 hours
Duration
The module takes 1 semester(s).
Qualification Targets

Students

  • acquire comprehensive knowledge of financial econometric methods for both cross-sectional data as well as time series data and are proficient in their application
  • are able to transfer questions concerning financial market data into suitable models, to estimate the models with the help of current methods, to draw valid conclusions from the data and to question the empirical results
  • can competently evaluate and critically examine studies in financial econometrics
  • are able to solve practical problems independently with the help of statistical software
Relevance

The practical relevance is high due to the combination of theory and empirical work.

Module Exam

Written exam (generally 60-90 minutes) or oral exam (generally 20-40 minutes). The chosen examination method (written or oral exam) is defined by the lecturer during the first weeks of the lecture period.

Usage in different degree programs
  • BWL EaF MasterWahlpflichtbereich 1.-3. Sem, Elective
  • ECMX MasterWahlpflichtbereichME7 Econometric Methods 1.-3. Sem, Elective
  • MuU MasterWahlpflichtbereich IWahlpflichtbereich I A.: Methodologie und allgemeine Theorien zur Untersuchung von Märkten und Unternehmen 1.-3. Sem, Elective
  • VWL MasterWahlpflichtbereich I 1.-3. Sem, Elective
  • WiMathe MasterVWL-M I 1.-4. Sem, Elective
  • WiMathe MasterVWL-M II 1.-4. Sem, Elective
Elements

Name in diploma supplement
Financial Econometrics
Organisational Unit
Lehrstuhl für Finanzmarktökonometrie
Lecturers
Prof. Dr. Yannick Hoga
SPW
2
Language
English
Cycle
irregular
Explanation for irregular cycle
The courses in this module take place irregularly and (usually) in summer semesters. Information on whether the course is offered can be obtained from the chair homepage or the LSF.
Participants at most
no limit
Participants

Preliminary knowledge

Knowledge of basic econometric and statistical methods as well as knowledge of univariate time series analysis. Knowledge of a statistical programming language such as R is also helpful.

Abstract

Teaching current financial econometric methods for cross-sectional and time series data.

Contents

  • Stochastic discount factor
  • Nonlinear generalized method of moments (GMM)
  • Factor pricing models
  • Equity premium puzzle
  • Predictability of returns
  • Multivariate volatility modeling

Literature

  • Cochrane, J.H. (2005). Asset Pricing. Princeton University Press.
  • Linton, L. (2019). Financial Econometrics: Models and Methods. Cambridge University Press.
  • Newey, W. K. and McFadden, D. (1994). Large sample estimation and hypothesis testing. In Engle, R. F. and McFadden, D., editors, Handbook of Econometrics, volume 4, chapter 36, pages 2111–2245. Elsevier.
  • Francq, C. and Zakoian, J.-M. (2019). GARCH Models: Structure, Statistical Inference and Financial Applications. Wiley.

Teaching concept

Presentation of the material in theory and practice, the latter in R.

Lecture: Financial Econometrics (WIWI‑C1254)

Name in diploma supplement
Financial Econometrics
Organisational Unit
Lehrstuhl für Finanzmarktökonometrie
Lecturers
Prof. Dr. Yannick Hoga, wissenschaftliche Mitarbeiter(innen)
SPW
2
Language
English
Cycle
irregular
Participants at most
no limit
Participants

Preliminary knowledge

See lecture

Contents

See lecture

Literature

See lecture

Teaching concept

Working on theoretical as well as practical exercises; the latter in R

Exercise: Financial Econometrics (WIWI‑C1255)
Module: Financial Econometrics (WIWI‑M0961)