Master theses (appr. 40 pages):

Formalities for Master theses correspond to those of BA theses.

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 (geilenkirchen@economics.uni-kiel.de) - 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

Reference:

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

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

Reference:

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

Supervisor: Clemens Koppe

3. Meso-scale structures in the correlation-based networks

Content: Replications of the analysis of MacMahon and  Garlaschelli (2015) with updated data or other stock markets (e.g. emerging markets)

Reference:

MacMahon and  Garlaschelli (2015). Community Detection for Correlation Matrices. Phys. Rev. X 5.
Source: https://journals.aps.org/prx/abstract/10.1103/PhysRevX.5.021006

Supervisor: Dr. Duc Thi Luu

4. 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.

References:

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

5. 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).

References:

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

6. Estimation of a Bivariate Multifractal Model of Asset Returns and Sentiment
 

Content: Replication of the analysis of Liu and Gupta (2021) and application to German data.

References:

Liu, T. and R. Gupta, Investors’ Uncertainty and Forecasting Stock Market Volatility, Journal of Behavioral Finance, 2021, in press.

Supervisor: Lutz Honvehlmann

7. Sentiment and Stock Returns: Trading Strategies based on VAR Models
RESERVED

Content: Replications of Lux (2011) with updated data

Reference: Lux, T., Sentiment and Stock Returns: The Case of the German Stock Market, Empirical Economics 41, 2011

Supervisor: Dr. Duc Thi Luu

8. Estimation of a Behavioral Model of Speculative Activity via Bayesian Indirect Inference

Content: Application of the methodology developed in Creel and Kristensen (2013, 2015a,b) to the model of Alfarano et al. (2018)

References:

Alfarano, S., T. Lux and F. Wagner, Time Variation of Higher Moments in a Financial Market with Heterogeneous Agents: An Analytical Approach, Journal of Economic Dynamics & Control 32, 2008

Creel, M. and D. Kristensen, Indirect Likelihood Inference, Working Paper, University College London, 2013

Creel, M. and D. Kristensen, On Selection of Statistics for Approximate Bayesian Computing (or the Method of Simulated Moments), Working Paper, University College London, 2015

Creel, M. and D. Kristensen, ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models, Journal of Empirical Finance 31, 2015

Supervisor: Clemens Koppe

Supervisor: Dr. Duc Thi Luu

10. Estimation of a Discrete Choice Model for the Distribution of Deposit Volumes across Banks 

Content: Implement a discrete choice model of the banks’ deposit volumes as theoretical sketched in: 

Maire, B. and A. Bloechlinger, Optimal Deposit Pricing in Competitive, Oligopolistic Markets . Working Paper, University of Zurich, 2012 

Supervisor: Lutz Honvehlmann

11. Business Sentiment and Opinion Dynamics: Identification of Social Interaction Effects 

Content: Replication of Lux (2009) with updated data 

Reference: Rational Forecasts or Social Opinion Dynamics: Identification of  Interaction Effects in a Business Climate Index, in: Journal of Economic Behavior and Organization 72, 2009, 638 - 655 

Supervisor: Clemens Knoppe