Chair of Monetary Economics and International Finance

Topics for Master Theses

Master theses (appr. 40 pages):

Formalities for Master theses correspond to those of BA theses.

MA-theses have to be written in English. You may write your MA-thesis in German according to prior agreement with your examiner. You can also suggest your own topic. Please contact our chair as early as possible.

You can make a reservation only for one topic at the same time (deadline for reservation: 4 weeks). You can exchange topic reservations but you cannot change back. Each topic will be assigned only once. Therefore, we recommend contacting our chair early. In case a list is not announced, please contact Prof. Lux directly to arrange a topic.

Assignment of Topics for Master Theses

The list of topics given below is available for Master theses to be supervised at the chair of Monetary Economics & International Finance.

Interest in specific topics should be expressed to:

Ricarda Geilenkirchen ( - accompanied by an up-to-date record of current status and exam results.   


Guidelines for Theses:


Guidelines for writing a thesis or seminar paper

Halten von Vorträgen

Der richtige Umgang mit dem Urheberrecht


Further Information about formalities regarding Bachelor- and Mastertheses are available on the homepage of the Examination Office



1. The Empirical Performance of Consumption Euler Equations

Content: A review of research on the validity of consumption Euler equations as a basic building block of macroeconomic models.


Canzoneri, M. et al., Euler Equations and Money Market Interest Rates: A Challenge for Monetary Policy Models, Journal of Monetary Economics 54, 2007, 1863-1881

Supervisor: Duc Thi Luu


2. Zero-Intelligence Models of the Microstructure of Financial Markets: Model Structure and Estimation


Šmíd, M., Estimation of zero-intelligence models by L1 data, Quantitative Finance 16, 2016

This is probably the only attempt at estimation of the mentioned class of models so far. The thesis should provide an introduction to the models and the estimation approach proposed in this contribution. An attempt at replication with alternative data would be preferable.

Supervisor: Lutz Honvehlmann


3. Money base, reserves and money supply: Tests of the money multiplier hypothesis

Content: Empirical analysis with European data analogous to Carpenter and Demiralp (2012)


Carpenter, S. and S. Demiralp, Money, Reserves and the Transmission of Monetary Policy: does the Money Multiplier Exist?, Journal of Macroeconomics 34, 2012

Supervisor: M. Raddant


4. Patterns of Network Formation in the Credit Network of Spain: An Application of the Exponential Random Graph Model

Content: Application of the framework explained in Lusher et al. (2013) to a comprehensive data base of credit relationships in the Spanish economy. Data is available at the Chair of Monetary Economics and International Finance


Lusher, D., Koskinen, J., & Robins, G. (Eds.). (2013). Exponential random graph models for social networks: Theory, methods, and applications. Cambridge University Press.


Supervisor: Dr. Duc Thi Luu


5. Estimation of Multifractal Model of Asset Returns via the Expectation Maximization Algorithm

Content: Application of the EM algorithm proposed in Schön et al. (2011) to some of the models considered in Lux (2018). Comparison of the efficiency and computational demands of different estimators and emprical application.


Lux, T., Inference for nonlinear state space models: A comparison of different methods applied to Markov-switching multifractal models, Working Paper, Kiel, 2018.

Schön, T. et al., System Identification of Nonlinear State Space Models, Automatica 47, 2011, 39-49

Supervisor: Dr. Duc Thi Luu



6. Bayesian Estimation of Behavioral Models of Financial Markets with Nested Sampling

Content: Application of the methodology of Skilling (2006) to the models of Lux (2010).


Lux, T. Bayesian Estimation of Agent-Based Models via Adaptive Particle Markov Chain Monte Carlo, Working Paper, Working Paper 2020-01, Kiel.

Skilling, John. "Nested sampling for general Bayesian computation." Bayesian analysis 1.4 (2006): 833-859.

Supervisor: Lutz Honvehlmann


7. Estimation of an Agent-Based asset Pricing Model using Synthetic Maximum Likelihood

 Content: Application of the method presented in Wood (2010) to one (or more) of the models covered in Lux (2020)


 Wood, S., Statistical inference for noisy nonlinear ecological dynamical systems, Nature 466, 2010

 Lux, T., Can Heterogeneous Agent Models Explain the Alleged Mispricing of the S&P 500? Working Paper, CAU, 2020

 Supervisor: Dr. M. Raddant