Master Thesis Topics FSS 2020Chair of Finance – Prof. Dr. Erik Theissen

Master Thesis Topics

• Presentation is downloadable on our website:

https://www.bwl.uni-mannheim.de/en/theissen/teaching/master-courses/master-thesis/

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Chair of Finance (I)

• Address:– L 9, 1-2

– Secretary: third floor (“3. OG“)

– Assistants: second, fourth, and fifth floor

• Office hours:– By appointment

– General questions: Please visit our homepage first

– Secretary: Mo-Fr 09.00 – 12.00 am

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Chair of Finance (II)

• Research at the Chair of Finance

a) Market Microstructure

b) Empirical Asset Pricing

c) Blockchain & Cryptocurrency

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Master Thesis Topics

• Prerequisite: – You must have successfully completed one seminar of the area "Banking,

Finance, and Insurance" (Prof. Albrecht, Prof. Bucher-Koenen, Prof. Maug, Prof. Niessen-Ruenzi, Prof. Ruenzi, Prof. Spalt, Prof. Theissen, Prof. Weber/Wimmer).

• The assignment of topics is carried out jointly by the finance area.

• Assignment to the topics will be based on your priority list and the grade in the respective seminar.

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Time Schedule

• Application period:– Monday, 09.03.2020 – Thursday, 19.03.2020

• Topics Allocation Announcement:– Tuesday, 24.03.2020

• Registration Period:– Tuesday, 24.03.2020 – Tuesday 31.03.2020

• Starting Date– Tuesday 31.03.2020

• Colloquium– Friday, 29.05.2020

• Submission Deadline– Friday, 31.07.2020

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Guide to Scientific Writing

• An information sheet on writing a seminar paper or a master thesis is provided on our website:

https://www.bwl.uni-mannheim.de/media/Lehrstuehle/bwl/Theissen/Services/Leitfaden_wissenschaftliche_Arbeiten_SeminarMaster.pdf

• Most important rules:– Your thesis should be 45 pages (+/- 10%)

– 50 pages is the absolute maximum

– Tables and figures have to be included in the text (and count towards the page restriction)

– Only supplementary material that is not needed to read and understand the thesis may be collected in an appendix

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Important Remarks

• Plagiarism policy:

– Your master thesis will be analyzed by plagiarism detection software (Turnitin).

– Our chair has a zero-tolerance policy regarding plagiarism.

– Students who submit plagiarized work will be graded with 5.0.

• Language quality:

– Grading of your master thesis takes also into account the language quality.

– Linguistic shortcomings negatively impacts your final grade.

– The master thesis can be either written in English or German.

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Master Topics

Questions ???

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T1. Resiliency Prof. Erik Theissen

Topic Description• Resiliency, one of the dimensions of the elusive concept of market liquidity, measures how

long the market takes in order to recover from a shock. Resiliency is difficult to measurebecause it is an inherently dynamic concept. In a recent paper, Hua et al. (2020) haveproposed and implemented a new empirical measure of resiliency. The objective of the masterthesis is

- to discuss the concept of resiliency and the empirical measures proposed to measure it

- to implement some of these measures (e.g. the one used in Bessembinder et al. 2016) aswell as the Hua et al. (2020) measure using data from the German equity market

- to compare and interpret the results.

• The empirical analysis requires Stata literacy and the ability to handle large data sets.

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Starting References• Bessembinder, H., A. Carrion, L. Tuttle and K. Venkataraman (2016): Liquidity, resiliency and

market quality around predictable trades: Theory and evidence. Journal of Financial Economics 121, 142-166.

• Hua, J., L. Peng, R. Schwartz and N. Sila Alan (2020): Resiliency and Stock Returns. Review ofFinancial Studies 33, 747-782.

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T1. Resiliency Prof. Erik Theissen

T2. Mutual Fund Manager Attractiveness and Fund Performance

Thomas Johann

Topic Description• There exists a large body of literature analyzing the mutual fund industry. One strain of that

literature regards whether personal characteristics of the manager (like age, name, education,experience, gender, …) drive performance, risk taking and fund flows of the fund undermanagement.

• A manager’s characteristics could affect fund flows due to behavioral or social biases ofinvestors: Niessen-Ruenzi/Ruenzi (2014) find that female managers receive significantly lessfund flows even though their performance is not different from that of their malecounterparts. Kumar et al. (2015) find something similar for foreign sounding manager names.

• Halford/Hsu (2014) show that CEOs with a higher Attractiveness Index are associated withhigher firm values. Graham et. al. (2015) suggest that more competent looking CEOs get jobsat larger firms and earn higher compensation.

• In this master thesis the author should construct an execute an online experiment testing thehypothesis that fund manager appearance affects fund flows.

• Recommended skills: Time Management, Survey Design, Programming (Stata, R or Python).

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Starting References• Baks, Klaas P., 2003, On the performance of mutual fund managers. Working Paper.

• Kumar, Alok and Niessen-Ruenzi, Alexandra and Spalt, 2015, Oliver G., What is in a Name? Mutual Fund Flows When Managers Have Foreign-Sounding Names. Review of Financial Studies 28, 8, pp. 2281-2321 .

• Niessen-Ruenzi, Alexandra and Ruenzi, Stefan, 2014, Sex Matters: Gender Bias in the Mutual Fund Industry. Management Science (2018).

• Halford, Joseph Taylor and Hsu, Scott HC, 2014, Beauty is wealth: CEO appearance and shareholder value. Working Paper

• Graham, John R., Campbell R. Harvey, and Manju Puri, 2015, A corporate beauty contest. Working Paper.

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T2. Mutual Fund Manager Attractiveness and Fund Performance

Thomas Johann

T3. Commonality across Time Zones Stefan Scharnowski

Topic Description• While it is well known that returns of different assets often move in the same direction, the

same is also true for how easily one can trade different assets.

• Commonality in liquidity is the co-movement of liquidity and trading activity of multipleassets. While earlier studies have documented such commonalities within single countries,later studies extended these analyses by looking at commonality across different countries.

• Typically, these later studies often ignore differences in time zones and thus differences in theoverlap of trading hours. However, intuitively one would expect that longer overlaps of tradinghours and stronger liquidity commonality are related.

• The aim of this thesis is to empirically analyze how differences in trading hour overlaps,particularly those due to time zone differences, affect commonality in international stockmarkets.

• Since this is a relatively novel research question, this thesis is especially suited for thosewanting to conduct original research. Some prior experience in working empirically (Stata, R,or Python) would be advisable.

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Starting References• Chordia, T., Roll, R., & Subrahmanyam, A. (2000). Commonality in liquidity. Journal of Financial Economics,

56(1), 3-28.

• Ito, T., & Hashimoto, Y. (2006). Intraday seasonality in activities of the foreign exchange markets: Evidence from the electronic broking system. Journal of the Japanese and International Economies, 20(4), 637-664.

• Zhang, Z., Cai, J., & Cheung, Y. L. (2009). Explaining country and cross‐border liquidity commonality in international equity markets. Journal of Futures Markets, 29(7), 630-652.

• Moulton, P. C., & Wei, L. (2009). A tale of two time zones: The impact of substitutes on cross-listed stock liquidity. Journal of Financial Markets, 12(4), 570-591.

• Karolyi, G. A., Lee, K. H., & Van Dijk, M. A. (2012). Understanding commonality in liquidity around the world. Journal of Financial Economics, 105(1), 82-112.

• Wang, J. (2013). Liquidity commonality among Asian equity markets. Pacific-Basin Finance Journal, 21(1), 1209-1231.

• Frino, A., Mollica, V., & Zhou, Z. (2014). Commonality in liquidity across international borders: Evidence from futures markets. Journal of Futures Markets, 34(8), 807-818.

• Dang, T. L., Moshirian, F., Wee, C. K. G., & Zhang, B. (2015). Cross-listings and liquidity commonality around the world. Journal of Financial Markets, 22, 1-26.

• Moulton, P. C., & Wei, L. (2009). A tale of two time zones: The impact of substitutes on cross-listed stock liquidity. Journal of Financial Markets, 12(4), 570-591.

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T3. Commonality across Time Zones Stefan Scharnowski

T4. Volatility Patterns in CryptocurrenciesStefan Scharnowski

Topic Description• The relatively new asset class of cryptocurrencies, of which Bitcoin is by far the most popular,

has received a lot of attention in recent years, both in the media and in academic research.One focus of research has been understanding their volatility dynamics.

• However, since cryptocurrencies have shown to be extremely volatile, understanding,modeling, and forecasting such volatility dynamics is no easy endeavor. There is still much tounderstand.

• This thesis contributes to the debate by empirically analyzing patterns in volatility for differentcryptocurrencies over a long period, potentially using intraday data. A focus should be placedon time-varying volatility asymmetry and its determinants.

• Since this is a relatively novel research question, this thesis is especially suited for thosewanting to conduct original research. Some prior experience in working empirically (Stata, R,or Python) would be advisable.

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Starting References• Cryptocurrencies

– Dyhrberg, A. H. (2016). Bitcoin, gold and the dollar–A GARCH volatility analysis. Finance Research Letters, 16, 85-92.

– Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economics Letters, 158, 3-6.

– Klein, T., Thu, H. P., & Walther, T. (2018). Bitcoin is not the New Gold–A comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis, 59, 105-116.

– Chaim, P., & Laurini, M. P. (2018). Volatility and return jumps in bitcoin. Economics Letters, 173, 158-163.

– Baur, D. G., & Dimpfl, T. (2018). Asymmetric volatility in cryptocurrencies. Economics Letters, 173, 148-151.

– Baur, D. G., Dimpfl, T., & Kuck, K. (2018). Bitcoin, gold and the US dollar–A replication and extension. Finance Research Letters, 25, 103-110.

– Ardia, D., Bluteau, K., & Rüede, M. (2019). Regime changes in Bitcoin GARCH volatility dynamics. Finance Research Letters, 29, 266-271.

– Charles, A., & Darné, O. (2019). Volatility estimation for Bitcoin: Replication and robustness. International Economics, 157, 23-32.

• Other assets

– Wang, J., & Yang, M. (2009). Asymmetric volatility in the foreign exchange markets. Journal of International Financial Markets, Institutions and Money, 19(4), 597-615.

– Talpsepp, T., & Rieger, M. O. (2010). Explaining asymmetric volatility around the world. Journal of Empirical Finance, 17(5), 938-956.

– Wu, G. (2001). The determinants of asymmetric volatility. The Review of Financial Studies, 14(3), 837-859.

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T4. Volatility Patterns in CryptocurrenciesStefan Scharnowski

T5. Option-Implied Volatility, Idiosyncratic Volatility, and Stock Returns

Lukas Zimmermann

Topic Description• Volatility represents uncertainty and thus summarizes an important source of risk in stock

returns. As it is important for investors to manage and understand their risk exposure, therelation of expected volatility to returns is of interest for investors. The most straightforwardapproach to determine volatility is the historical or realized volatility of stock returns. Thereare further approaches and concepts that are used to determine expected volatility:Idiosyncratic volatility measures the volatility of the stock specific components of stockreturns. However, the return premium associated with this type of volatility is relatively weakin recent time. One explanation is that idiosyncratic volatility is a proxy for limits to arbitrageand these are lower than in the past. Option-implied volatility is derived from option prices. Incontrast to the previously introduced measure, option-implied volatility is a market basedmeasure that is derived from current prices.

• The thesis should examine the concept of option-implied volatility more closely and compareit to the other approaches for measuring volatility. The first task will consist of comparing thedifferent volatility measures and determine how similar or dissimilar they are, similar toChristensen and Prabhala (1998). The second task will be to examine the ability of thedifferent measures to predict stock returns, similar to An et al. (2014), Ang et al. (2006), orBali and Cakici (2009).

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Starting References• An, Byeong-Je, Andrew Ang, Turan G. Bali, and Nusret Cakici, 2014, The Joint Cross Section of

Stocks and Options, The Journal of Finance 69, 2279–2337.

• Ang, Andrew, Robert J. Hodrick, Yuhang Xing, and Xiaoyan Zhang, 2006, The Cross-Section ofVolatility and Expected Returns, The Journal of Finance 61, 259–299.

• Bali, Turan G, and Nusret Cakici, 2009, Idiosyncratic Volatility and the Cross Section ofExpected Returns, Journal of Financial and Quantitative Analysis 43, 29.

• Bartram, Söhnke M., Gregory W. Brown, and René M. Stulz, 2019, Why is there a SecularDecline in Idiosyncratic Risk in the 2000s?, Working Paper.

• Canina, Linda, and Stephen Figlewski, 1993, The Informational Content of Implied Volatiliy, Review of Financial Studies 6, 659–681.

• Christensen, B.J., and N.R. Prabhala, 1998, The Relation Between Implied and RealizedVolatility, Journal of Financial Economics 50, 125–150.

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T5. Option-Implied Volatility, Idiosyncratic Volatility, and Stock Returns

Lukas Zimmermann

T6. Price Pressure and Liquidity Mengnan Wu

Topic Description• The price pressure hypothesis(PPH) states that there is a temporary price effect induced by

large transactions. An increase in trading activity leads to an increase in compensation forliquidity providers. To test for PPH, previous studies often analyze the effect of information-freetrading by transaction returns, which may contain the noise associated with bid-ask bounce. Inaddition, often times they focus on events that are contaminated by economically relevantinformation, such as block sales or index revision.

• Kosiki and Michaely(2000) find trades without fundemental information have no impacts onprice and liquidity with transaction data. D'Mello et al.(2003) show that tax-induced sellingpressure causes the price to be at the bid, temporarily depresses the equilibrium price, andnegatively affects market liquidity.

Student‘s Task• The thesis should survey and compare the measures for illiquidity proposed in the literature.

• The primary goal of the thesis is to find evidence on how events without fundamentalinformation (i.e. tax-induced selling in Germany from 2002 to 2009) impact the price andstocks liquidity by analyzing trades, quotes, bid-ask spreads and depths.

• The thesis can further examine the price and liquidity patterns of trades with asymmetricinformation(i.e. pre-ipo shareholder selling) as comparison.

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Starting References• D'Mello, R., Ferris, S. P., & Hwang, C. Y. (2003). The tax-loss selling hypothesis, market liquidity, and price

pressure around the turn-of-the-year. Journal of Financial Markets, 6(1), 73-98.

• Koski, J. L., & Michaely, R. (2000). Prices, liquidity, and the information content of trades. The Review of Financial Studies, 13(3), 659-696.

• Hendershott, T., & Menkveld, A. J. (2014). Price pressures. Journal of Financial Economics, 114(3), 405-423.

• Talijan, V. (2017). Marketwide Price Pressure. Available at SSRN 3049682.

• Coval, J., & Stafford, E. (2007). Asset fire sales (and purchases) in equity markets. Journal of Financial Economics, 86(2), 479-512.

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T6. Price Pressure and Liquidity Mengnan Wu

T7. Climate Change-Related Natural Disasters and Green Innovation

Clemens Mueller

Description• Climate Change affects the likelihood of extreme temperatures and intense climate-

related disasters (IPCC)• Record-breaking temperatures and extreme events help raise awareness• Key to finding a global solution to climate change are technological breakthroughs• Are firms exposed to natural disasters more likely to patent green technologies?

Student‘s Task

• The goal of this thesis is to find drivers of green innovation• Does exposure to natural disasters increase future innovation output as measured

by patents?• Due to exogenous nature of weather events, the goal is to make causal statements• Data on US patents and extreme weather events will be provided

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T7. Climate Change-Related Natural Disasters and Green Innovation

Clemens Mueller

Description• Gianluca Orsatti, Francesco Quatraro, Michele Pezzoni. The antecedents of green technologies: The role of

team-level recombinant capabilities, Research Policy, Volume 49, Issue 3, 2020.• Emdad Islam, Mandeep Singh. The Impact of Temperature Shocks on the Credit Market, Working Paper

2019.• Matthew M. Wynter. Frugality and Firms’ Financial Flexibility: Evidence from Natural Disasters, Working

Paper 2019.

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T8. Patents and InnovationClemens Mueller

Description• Patents are temporary monopoly rights that serve to incentivize innovators• However what is the causal impact of a patent grant to a start-up?• Using recent methodological advances and data in Sampat & Williams (2019) and

Farre-Mensa (forthcoming) we get closer to answering this question• Using the quasi-random assignment of examiners to a firm‘s patent application, we

can make a patent quasi-random to a firm and observe subsequent effects such asfurther financing rounds and M&A or IPO likelihood

Student‘s Task

• Replicate the findings of Farre-Mensa (forthcoming)• Data on patents, examiners and start-ups is provided• Extend the analysis by either focusing on:

– Biases in the examiner process (gender discrimination, homophilia)– Firm- or region-level effects

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T8. Patents and InnovationClemens Mueller

Description• Joan Farre-Mensa, Deepak Hegde, Alexander Ljungqvist. What is a Patent Worth? Evidence from the U.S.

Patent "Lottery“. Journal of Finance, forthcoming• Bhaven Sampat & Heidi L. Williams, 2019. How Do Patents Affect Follow-On Innovation? Evidence from the

Human Genome, American Economic Review, vol 109(1), pages 203-236.• Cesare Righi, Timothy Simcoe. Patent examiner specialization, Research Policy, Volume 48, Issue 1, 2019,

Pages 137-148.• Yael V. Hochberg, Carlos J. Serrano, Rosemarie H. Ziedonis. Patent collateral, investor commitment, and the

market for venture lending, Journal of Financial Economics, Volume 130, Issue 1, 2018, Pages 74-94.

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T9. Corona and the Stock Market: Miles Away From Ordinary? Stefan Greppmair

Topic Description

• “Global stocks have worst day in two years as coronavirus fears spread“ (FT, 26.02.2020)

• “Stocks have worst day since October over coronavirus worries“ (NY Times, 27.01.2020)

• “Apple says coronavirus effects will cause revenues to fall (MarketWatch, 17.02.2020)

• “Coronavirus could cost airlines $30 Billion“ (Forbes, 21.02.2020)

• Anecdotal evidence suggests that the outbreak of the corona virus is associated with plungingstock markets around the world

• Moreover, globally operating companies or companies with significant business connections tothe affected regions expect falling revenues or increasing uncertainty in demand

• In asset pricing, one can think of the corona virus as a fundamental shock which can affectstock prices, expected returns, and higher-order moments of „connected“ companies

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Topic Description

• The purpose of this thesis is to investigate the effect of the corona virus on aggregate stockmarkets and especially individual stocks

• More specifically, the student needs to first identify companies that are most likely to beaffected by the outbreak of the virus.

• Then, it should be investigated how stock prices, expected returns and higher-order momentsof affected companies react to significant news about the virus

• From a theoretical perspective, the analysis should be embedded into the context of long-runrisk models (Bansal and Yaron, 2005) and the rare distaster risk framework proposed by Barro(2006) and Gabaix (2012)

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T9. Corona and the Stock Market: Miles Away From Ordinary? Stefan Greppmair

Starting References• Bansal, R. and Yaron, A. (2005). Risks for the Long Run: A Potential Resolution of Asset Pricing

Puzzles. Journal of Finance, 59, p.1481-1509

• Barro, R.J. (2006). Rare Disasters and Asset Markets in the Twentieth Century. The Quarterly Journal of Economics, 121, p.823-866

• Barro, R.J. and Jin, T. (2020). Rare Events and Long-Run Risks. NBER Working Paper

• Berkman, H., Jacobsen, B. and Lee, J.B. (2011). Time-varying rare disaster risk and stock returns. Journal of Financial Economics, 101, p.313-332

• Gabaix, X. (2012). Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance. The Quarterly Journal of Economics, 127, p.645-700

• Seo, S.B. and Wachter, J.A. (2019). Option Prices in a Model with Stochastic Disaster Risk. Management Science, 65, p.3449-3469

• Tsai, J. and Wachter, J.A. (2015). Disaster Risk and Its Implications for Asset Pricing. Annual Review of Financial Economics, 7, p.219-252

• Wachter, J.A. (2013). Can time-varying risk of rare disasters explain aggregate stock marketvolatility? Journal of Finance, 68, p.987-1035

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T9. Corona and the Stock Market: Miles Away From Ordinary? Stefan Greppmair

T10. Do Stocks Outperform Treasury Bills? Evidence for Germany

Can Yilanci

Topic Description• Bessembinder (2018) shows that only 4% of stocks account for the net gain of the entire US

stock market since 1926. These stocks include, for example, Apple, Microsoft, Coca Cola,McDonald’s, Walt Disney and many other well-known companies.

• The evidence that stock market returns exceed treasury bill returns is based on broadlydiversified stock market portfolios. However, Bessembinder (2018) focuses on returns toindividual common stocks. He shows that “most individual US common stocks provide buy-and-hold returns that fall short of those earned on one-month US treasury bills over the samehorizons”. Bessembinder (2018) highlights that for the period from 1926 to 2016, only 47.8%of CRSP stock returns are larger than the US Treasury Bill rates in the same month. Hence, it isimportant for investors to not omit key stocks from investment portfolios (portfoliodiversification).

• The aim of the thesis is to replicate the main findings of Bessembinder (2018) for Germany. Inparticular, the following questions should be analyzed in more detailed. Can the growth of theGerman stock market be attributed to a small number of firms as well? And if so, which firmsare the main drivers behind the German stock market growth? The student should gain an in-depth understanding on the importance of diversification and skewness in stock returns.

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T10. Do Stocks Outperform Treasury Bills? Evidence for Germany

Can Yilanci

Starting References• Main Paper

– Bessembinder, H. (2018). Do stocks outperform Treasury bills?. Journal of Financial Economics. 129(3). 440-457

• Time Diversification– Savor, P. and M. Wilson (2013). How Much Do Investors Care About Macroeconomic Risk? Evidence from Scheduled

Economic Announcements. Journal of Financial and Quantitative Analysis. 48(2). 343-375

– Lucca, D. and E. Moench (2015). The Pre-FOMC Announcement Drift. The Journal of Finance. 70(1). 329-371

• Equity Risk Premium– Mehra, R. and E. C. Prescott (1985). The equity premium: A puzzle. Journal of Monetary Economics. 15(2). 145-161

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