Preface

The seminar is open to Master students.

To successfully pass the seminar you need to write a paper and give a presentation. Papers can be written in either German or English and should be of 15-20 pages as a team of two and 20-25 pages as a team of three. For hints how to write a paper see our guidelines. You need to hand in a printed version and also a digital one (PDF). The seminar talks should be given in English. You will have to present around 45 minutes.

For each topic, you should provide a short literature survey (here you should consider more than your intro-paper(s)) and you will also have to work on a practical part in which you should get familiar with empirical analysis (accessing data over Datastream or Bloomberg, performing quantitative analyses). You will need to use a data analysis tool (e.g. Excel, R, Matlab, etc.). 

Please contact your supervisor to discuss the outline of your paper, your empirical part, and any questions that you may have.

Futhermore, you have to hand in a 5-page overview of your problem, your approach and your results. Your supervisor will provide some feedback on base of this overview. Consequently, you can consider this feedback in your presentation and your final paper.

FAQ & Organisational matters

• Do we get a grade? Yes. Your paper and your presentation will be graded and lead to one grade (equally weighted). Both the paper and presentation have to be passed.
• What do we have to hand in? A result-overview one month before your presentation and your final paper one week before the presentation.

Time Table

Topics

1. Predicting the Equity Premium with Combination Forecasts
Forecasts combination is a relatively simple forecasting technique that seems to work well for equity premium prediction. You shall review the evidence and then perform a similar study for Germany and/or other countries of your choice. Information is available from Datastream, Bloomberg and other sources.

Literature to get started:
Rapach, D., Strauss, J. and Zhou, G. (2010). Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy. Review of Financial Studies 3:821-62.

Students: Dan Wu
Supervisor: Gunter Löffler
Template: Excel-File

 
2. Forecasting Stock Market Returns
Ferreira and Santa-Clara (2011) propose the sum-of-the-parts (SOP) method for forecasting stock market returns. In this paper you are expected to carry out your own analysis and investigate how this method performs in the German stock market when compared to the predictive regressions.

Literature to get started:
Ferreira, M. and Santa-Clara, P. (2011). Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole. Journal of Financial Economics 100, 514–537.

Students: Richard Ahadzie, Moses Kangogo
Supervisor: Maximilian Franke
Template: Excel-File
 

3. Three Generations of Prospect Theory
Introduce the original prospect theory. Motivate and discuss the extensions of the second and third generation of prospect theory. Provide empirical evidence for all three generations.

Literature to get started:
Kahneman, D. and Tversky, A. (1979). Prospect Theory: An Analysis of Decision Under Risk, Econometrica, 47 (2), pp. 263-292.
Tversky, A. and Kahneman, D. (1992). Advances in Prospect Theory: Cumulative Representation of Uncertainty, Journal of Risk and Uncertainty, 5 (4), pp 297-323
Schmidt, U., Starmer, C. and Sugden, R. (2008). Third-generation Prospect Theory, Journal of Risk and Uncertainty, 36 (3), pp 203-223.

Students: Paola Acha, Teresa Nacheri
Supervisor: Matthias Böhm
 

4. Reevaluating Myopic Loss Aversion
Motivate the concept of myopic loss aversion. Reevaluate the empirical analysis of Benartzi and Thaler (1995) for the broader time period of July 1926 to December 2012. In a second analysis, evaluate myopic loss aversion for the European and Asian region. Use the data from the library of Kenneth R. French (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html).

Literature to get started:
Benartzi, S. and Thaler, R.H. (1995). Myopic Loss Aversion and the Equity Premium Puzzle, The Quarterly Journal of Economics, 110 (1), pp. 73-92.

Students: Jeyhun Garayev, Benjamin Adomako
Supervisor: Matthias Böhm
Template: R-File
 

5. Momentum, Reversal and the Efficiency of the Market Portfolio
Evaluate the efficiency of the market portfolio against momentum and reversal portfolios similar to Fama and French (1996, p. 67) but compute test statistics as discussed in Chou and Zhou (2006). Consider only the iid case Chou and Zhou (2006). Discuss your results by comparing inferential statistics obtained from an analytical and a bootstrap approach. Use the data from the library of Kenneth R. French (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html).

Literature to get started:
Fama, E.F. and French, K.R. (1996). Multifactor Explanations of Asset Pricing Anomalies, Journal of Finance, 51 (1), pp. 55-84.
Chou, P.-H. and Zhou, G. (2008). Using Bootstrap to Test Portfolio Efficiency, Annals of Economics and Finance, 7 (2), pp. 217-249.

Student: Ahmed Mahmoud
Supervisor: Matthias Böhm
Template: R-File


6. Lottery Stocks
What are lottery stocks? Perform an empirical analysis for lottery stocks similar to Bali et. al. (2011). In your empirical analysis, focus on the German stock market from 1990 and the relation between the maximum daily return over the past one month and expected stock returns. You can obtain data from Datastream.

Literature to get started:
Bali, T., Cakici, N. and Whitelaw, R. (2011). Maxing Out: Stocks as Lotteries and the Cross-section of Expected Returns, Journal of Financial Economics, 99 (2), pp. 427-446
Kumar, A. (2009). Who Gambles in the Stock Market?, Journal of Finance, 64 (4), pp. 1889-1933.

Student: Elvina Khusainova, Liza Lashin
Supervisor: Maximilian Franke
Template: R-File
Data: Stocks-CSV


7. Idiosyncratic Return Volatility
Similar to Kang et al. (2011), you are expected to investigate the role of hedge funds and other institutional investors in explaining the dynamics of extreme realizations in the cross.-section of German stock returns.

Literature to get started:
Kang, N., Kondor, P. and Sadka, R. (2011). Idiosyncratic Return Volatility in the Cross-section of Stocks. Working Paper.

 
8. Systematic and Idiosyncratic Skewness
Introduce the concepts of systematic and idiosyncratic skewness and how they relate to expected returns. Provide empirical evidence using 49 industry portfolios from the library of Kenneth R. French (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html).

Literature to get started:
Boyer, B., Mitton, T. and Vorkink, K. (2010). Expected Idiosyncratic Skewness, Review of Financial Studies, 23 (1), pp. 169-202
Harvey, C. and Siddique, A. (2000). Conditional Skewness in Asset Pricing Tests, Journal of Finance, 55 (3), pp. 1263-1295.

Student: Elvan Karatas
Supervisor: Maximilian Franke
Template: R-File
Data: Portfolios-CSV, French-Factors-CSV


9. Illiquidity Premia in Stock Returns
Follow the procedure in Amihud (2001) and evaluate empirically if there is evidence for liquidity premia in stock returns. You can obtain data from Bloomberg and Datastream.

Literature to get started:
Amihud, Y. (2002). Illiquidity and Stock Returns: Cross-section and Time-series Effects, Journal of Financial Markets, 5, pp. 31-56.


10. Riding Bubbles
Guenster et al. (2012) propose a bubble detection method. In this seminar topic, you are required to apply this method to German industries. Is there statistical and/or economic evidence in support of the riding bubbles hypothesis in the German Market?

Literature to get started:
Guenster, N., Kole, E. and Jacobsen, B. (2012). Riding Bubbles. Working Paper.


11. Value, Size and Distress
Review recent evidence on the financial distress explanation for the value and size premium. Using data for Germany, replicate findings from Kapadia (2011) for the German stock market. You can obtain data from German stock market data from Datastream, and German insolvency data from www.destatis.de.

Literature to get started:
Kapadia, N. (2011). Tracking Down Distress Risk. Journal of Financial Economics 102, 167-182.

Students: Papa Orgen, Mohammadali Montazeri
Supervisor: Prof. Dr. Gunter Löffler
Template: Excel-File
 

12. Investment-based Asset Pricing and a New Factor Model
The intuition behind investment-based asset pricing is as follows: if a firm’s discount rate is relatively low, investing is relatively attractive. Investment behavior can thus be indicative of discount rates, i.e. expected returns. You shall review the reasoning and the empirical evidence and then perform a similar study for Germany and/or other countries of your choice. Information is available from Datastream or Bloomberg.

Literature to get started:
Hou, K., Xue, C. and Zhang, L. (2012): Digesting Anomalies: An Investment Approach. Working Paper.

Students: Kofi Agyekum, Jane Durrell
Supervisor: Prof. Dr. Gunter Löffler
Template: Text-File