Proposals for Master's theses

Please note our general information on theses. In addition, please note that most theses supervised by the institute have an empirical part. We therefore recommend that students interested in writing a Master thesis attend the modeling and research courses offered by the finance institutes (Financial Modeling, Research in Finance).

ASSET PRICING

 

Predictability of stock market returns

First you shall replicate the core parts of a recent paper on the long-run predictability of stock market returns. Then you shall examine whether additional variables also help to predict stock market returns. The selection of additional variables will be discussed in advance. Contact: Prof. Löffler

Literature to get started: Golez, B., & Koudijs, P. (2018). Four centuries of return predictability. Journal of Financial Economics127(2), 248-263.

 

INVESTING

 

Return-based measures of firm quality

A recent paper shows that stock returns can be predicted with a measure of firm quality that is based on stock returns during stressful times. You shall review results from this paper as well a results of similar approaches and then conduct your own study using international data (Contact: Prof. Löffler).

Literature to get started: Jagannathan, R. and Zhang, Y., 2020. A Return Based Measure of Firm Quality (No. w27859). National Bureau of Economic Research.

 

Using image recognition for return prediction

Machine learning has made tremendous progress in image recognition tasks. In this thesis, you will explore whether standard image recognition approaches can be used to predict returns and to derive trading signals. You will explore different ways of converting financial data into images, and examine different assets and predictive information.  (Contact: Prof. Löffler).

Literature to get started: Jiang, J., Kelly, B.T. and Xiu, D., 2020. (Re-) Imag (in) ing Price Trends. Chicago Booth Research Paper, (21-01).

 

RISK

Performance of value-at-risk models: an update

The corona crisis is a good opportunity to assess the performance of value-at-risk forecasts. In your thesis, you shall test for a representative set of VaR models how they performed during the corona crisis and how this performance compares to their prior performance.

Literature to get started: Nieto, M.R. and Ruiz, E., 2016. Frontiers in VaR forecasting and backtesting. International Journal of Forecasting32(2), 475-501.