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4709853: MasterLAB in Financial Services - Uncertainty everywhere

Semester:SS 19
Scheduled in semester:2
Semester Hours per Week / Contact Hours:21.0 L / 16.0 h
Self-directed study time:74.2 h

Module coordination/Lecturers


Master's degree programme in Finance (01.09.2015)


This is an internal project, guided by Ass.-Prof. Dr. Sebastian Stöckl

Project Goals:
The investment world is full of uncertainties, which is a similar concept as risk but does
neither fully follow econometric laws, nor is it easy to measure/calculate. Prominent
examples for ways to measure uncertainty are:
• Parameter Uncertainty: Garlappi, Uppal, & Wang (2007)
• Macroeconomic/Real/Financial Uncertainty: Jurado, Ludvigson & Ng. (2015),
Ludvigson, Ma & Ng (2017)
• Economic Policy Uncertainty: Baker, Bloom & Davis (2016)
Here at the Chair in Finance, we have been developing various uncertainty measures over
time, e.g. a private investor risk index (Stöckl, Hanke, & Angerer, 2017), parameter
uncertainty indices (Stöckl, 2018a, 2018b) and a macroeconomic uncertainty index (Gächter,
Geiger, & Stöckl, 2019, together with the Financial Market Authority Liechtenstein). All of
them are based on a measure of financial “turbulence”. The task of this project will be to
provide an overview over possible indices for different regions of the world, collect evidence
and set up a self-updating website to provide the data and information to researchers and
investors all over the world! The domain for this will be To keep
everything straightforward and easy, we will set up the website using rmarkdown (which is
therefore a mandatory skill for this project).
The benefit for you will be threefold: (1) you will of course be mentioned as authors of the
website, (2) you will provide new academic evidence to the world and (3) I would be happy
to accept future seminar papers and master theses providing more evidence on these
indices. Such papers will be easily publishable, gather academic recognition for all of you and
the best: You already bring a large amount of knowledge from this Masterlab into such a
future project!

• Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring Economic Policy
Uncertainty. The Quarterly Journal of Economics, 131(4), 1593–1636.
• Gächter, M., Geiger, M., & Stöckl, S. (2019). Financial Distress and the Transmission
of Macroeconomic Uncertainty: International Evidence, 24.
• Garlappi, L., Uppal, R., & Wang, T. (2007). Portfolio Selection with Parameter and
Model Uncertainty: A Multi-Prior Approach. Review of Financial Studies, 20(1), 41–
81. doi:10.1093/rfs/hhl003
• Jurado, K., Ludvigson, S. C., & Ng, S. (2015). Measuring Uncertainty. The American
Economic Review, 105(3), 1177–1216.
• Ludvigson, S. C., Ma, S., & Ng, S. (2017). Uncertainty and Business Cycles:
Exogenous Impulse or Endogenous Response? National Bureau of Economic
Research. Retrieved from
• Stöckl, S. (2018a). Parameter Uncertainty, Financial Turbulence and Aggregate Stock
Returns (SSRN Scholarly Paper No. 2988568). Retrieved from
• Stöckl, S. (2018b). Turbulence in the Cross-Section: Predicting Factor Premia (SSRN
Scholarly Paper No. 3221140). Retrieved from
• Stöckl, S., Hanke, M., & Angerer, M. (2017). PRIX - A Risk Index for Global Private
Investors. The Journal of Risk Finance, 18(2), 214–231. doi:10.1108/JRF-09-2016-

Number of Students Required: Group of 3-5 students

Skills required: Good knowledge of R, basic knowledge of rmarkdown (no real html skills

Supervisor: Sebastian Stöck


Exam Modalities

  • Assignment (depending on the project an additional presentation may apply) (100%)
  • Obligatory class participation


Expected group size: 3-5 students.


22.02.201915:00 - 16:30N.N.
07.03.201909:00 - 12:15S1
22.03.201909:00 - 12:15S3
04.04.201909:00 - 12:15S3
09.05.201913:15 - 16:30S3
23.05.201913:15 - 16:30S3