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Master of Science in Finance and Banking

Thesis titles.

MSc in Finance and Banking Theses Titles, by Academic Year

Anna Cursi, IPO and Covid-19 Pandemic: The Influence on the Underpricing Phenomenon in the Italian Market, Advisor: Prof. Vincenzo Farina

Nicolas De Matteo , The Impact of AI on Firms: An Event Study on Abnormal Returns Following AI Investment Announcements, Advisor: Prof. Vincenzo Farina

Jacopo Failoni , A New Benchmark Interest Rate: From LIBOR to SOFR, Advisor: Prof. Stefano Herzel

Sadaf Khaghani , Analysis of Sharpe Ratio via Residual-Based Nodewise Regression Approach, Advisor: Prof. Tommaso Proietti

Niyamaddin Mammadov , Cognitive Biases in Mbs Risk Perception: Insights From the 2008 Crisis Through the Lens of Behavioral Finance, Advisor: Prof. Stefano Herzel

Valeria Palombi , Realized Volatility Modeling with Time-Varying Dependencies, Advisor: Prof. Alessandro Casini

Leonardo Pavone , Empirical Analysis of M&A Transactions: Evidence from the European Market, Advisor: Prof. Ugo Pomante

Vincenzo Perrone , Endogenous Sampling in Financial Econometrics, Advisor: Prof. Davide Pirino

Carlo Emanuele Autiero, Robust Portfolio Optimisation Under Sparse Contamination, Advisor: Prof. Alessio Farcomeni

Vladyslava Bab'yak, Caviar and Cross-Sectional Quantile Regression Models to Assess Risk in SEP500 Sectors, Advisor: Prof. Tommaso Proietti

Francesco Bianchi, An Analysis of Small Businesses Loan Dynamics Using Inverse Probability Weighting, Advisor: Prof. Alesso Farcomeni

Chiara Cammeo, Arms Trade Network Analysis on R, Advisor: Prof. Alessio Farcomeni

Karin Carlsson, Covered Call on An Index - A Comparative Study of Two Strategies, Advisor: Prof. Shmuel Baruch

Laura Colozzi , The Put-Call Parity Mispricing: An Event Study, Advisor: Prof. Shmuel Baruch

Matteo Cosentino , Retail Investors Against Wall Street: The Role of Reddit in the Gamesstop Short Squeeze, Advisor: Prof. Alessio Farcomeni

Maddalena De Vivo, Factor Mimicking Portfolio and ESG Factor, Advisor: Prof. Alessandro Ramponi

Leonardo Di Filippo, Rough Heston Model: Montecarlo Simulation of the Volatility Surface Dynamics, Advisor: Prof. Alessandro Ramponi

Bruno Di Jeso, Fractional Shares and the Split Minimum, Advisor: Prof. Shmuel Baruch

Sabina Di Maro, Network Analysis and Vulnerability Indexes in Socially Responsible Investments, Advisor: Prof. Rocco Ciciretti

Claudia Esposito, Experimental Analysis of Emotional Engagement in Thematic Fund Advertisements: A Neuroeconomic Perspective, Advisor: Prof. Ugo Pomante

Lucia Formisano , What Role Has the Festival Sector in the Global Economy, What Meaning Has in Our Personal Lives an In-depth Analysis: Elrow and Cinema Festival, Advisor: Prof. Maura Mezzetti

Federica Fubelli , Financial Attitudes of Italian Households and Their Determinants, Advisor: Prof. Maura Mezzetti

Simone Genna , Climate-related Risk and Ngfs Scenarios: A Financial Perspective on CO2 Emissions Correlations, Advisor: Prof. Maura Mezzetti

Leonid Grebinka, The Role and Performance of Accelerators in the Munich Startup Ecosystem, Advisor: Prof. Vincenzo Farina

Simone Grugni, Using Asset Prices to Predict Bank Defaults: A Quantitative Approach, Advisor: Prof. Shmuel Baruch

Ludvig HillenFjärd, Enhancing Forex Trading Strategies: An Investigation into the Integration of Technical Analysis and Portfolio Management, Advisor: Prof. Ugo Pomante

Riccardo Mancini , An In-Depth Analysis of One-Factor Affine Term Structure Models: Cross-Sectional and Time Series Calibration of Vasicek and CIR Models, Advisor: Prof.Stefano Herzel

Angelo Mangieri , Sovereign Bond Yields: Climate Risk Impact, Advisor: Prof. Rocco Ciciretti

Fabio Marchese , The Impact of the Covid-19 Vaccine Announcement on Pfizer's Stock Price: A Single Firm Single Event Study, Advisor: Prof. Shmuel Baruch

Lorenzo Marcolini, Investment Strategies for Young Adults: Building a Dynamic Asset Allocation Model Using Genetic Algorithms, Advisor: Prof. Ugo Pomante

Mattia Marletta, Merton's Portfolio Problem: Does Portfolio Rebalancing Really Affect Investor's Utility?, Advisor: Prof. Shmuel Baruch

Noemi Pandolfi , The Relationship Between Spot and Futures Prices of the EU Ets Market Focusing On Volatility Spillover and Dynamic Correlation, Advisor: Prof. Gianni Nicolini

Andrea Pasquali , Exploring the Relationship Between ESG Disagreement and Stock Returns. An Empirical Analysis, Advisor: Prof. Rocco Ciciretti

Anastasiia Polynskaia , ESG Scores and Acquisition Premia, Advisor: Prof. Shmuel Baruch

Giulia Proietti , Thematic Investments: Challenges and Perspectives for Asset Management, Advisor: Prof. Ugo Pomante

Tommaso Roncacci , From the London Interbank Offered Rate to Risk-Free Rates: An Overview of LIBOR Success, Scandals, and Replacement Inside the Derivatives and Loan Markets, Advisor: Prof. Stefano Herzel

Alessandra Rusu , Financial Drawdown and CO2 Emissions in Sustainable Investments, Advisor: Prof. Rocco Ciciretti

Alina Mihaela Sandu , Econometric Investigation of Volatility Clustering and Asymmetry Effects on the Italian Stock Market, Advisor: Prof. Shmuel Baruch

Lucia Sansone, An Empirical Study of the Weekend Effect in Stock Markets, Advisor: Prof. Lucia Sansone

Sara Scollo, Gender Inequality in the Italian Academia, Advisor: Prof. Maura Mezzetti

Allesandra Tallarico , The Effect of Uncertainty on Firms Investments in Green Technology, Advisor: Prof.Katia Colaneri

Chiara Tenerini , Optimal Portfolio Design for European Regulatory Compliance: Exploring Genetic Algorithms Techniques, Advisor: Prof. Ugo Pomante

Francesco Torlai , Legislative Impacts and Quantitative Insights: Investigating EU ESG Benchmarks for Sustainable Investing, Advisor: Prof. Maura Mezzetti

Cristiano Vasallucci, An Empirical Analyses of the Nordic Banking Sector, Advisor: Prof. Stefano Caiazza

Khaled Youssef , An Empirical Analysis of the Put/Call Ratio Sentiment Indicator, Advisor: Prof. Shmuel Baruch

Valerio Zarrelli , Modelling Rough Volatility: The Rough Heston Model, Advisor: Prof. Alessandro Ramponi

Mehran Akbari, Performance assessment of dimension reduction techniques in market prediction in cross section of present values, Advisor: Prof. Gianluca Cubadda

Massimo Ziad Ammar , A Look into Variance Ratio: Are All Markets Becoming More Efficient with Time?, Advisor: Prof. Tommaso Proietti

Emanuel Andrei, Swap spread arbitrage strategy: a new approach using the Secured Overnight Financing Rate, Advisor: Stefano Herzel

Roberto Bauer , Machine Learning applied to dynamic Hedging strategies: a comparison between ANNs and linear regression models., Advisor: Prof. Alessandro Ramponi

Andrea Caputo, The Socially Responsible Funds, Advisor: Rocco Ciciretti

Stefano Caputo , Bitcoin Trading Strategy on Twitter Sentiment Analysis, Advisor: Prof. Vincenzo Farina

Andrei Carp , Machine Learning applications to predict stock prices based on technical indicators, Advisor: Prof. Alessandro Ramponi

Lorenzo Cianciullo, Investing in corporate socially responsible activities: a robust analysis of deletion event effects, Advisor: Rocco Ciciretti

Maria Ciobanu ,   Behaviour of Healthcare Index: A GARCH forecasting approach to predict volatility, Advisor: Prof. Tommaso Proietti

Domenico Roberto Curciarello, Does Bitcoin hedge inflation risk? A multivariate time series analysis, Advisor: Prof. Tommaso Proietti

Valerio D'Agostini , The Hard Landing of the Chinese Shadow Banking: how China’s printing machine and financial system practices may overwhelm its and other countries’ economy., Advisor: Prof. Ugo Pomante

Michele Dimartino , Legal and Ethical characteristics of Sukuk   to be a Sharia Compliant Financial Instrument, Advisor: Prof. Amalia Diurni

Diana  Andrea Dudas , Are Cat Bonds better than Reinsurance? A numerical study., Advisor: Prof. Katia Colaneri

Thiago Ely Tatsch, Does Alternative Data Improve Financial Forecasting? A series of cases, Advisor: Prof. Vincenzo Farina

Luciana Fauceglia, Portfolio selection with ESG score: a new "optimization" approach to include investors' ESG preferences, Advisor: Prof. Ugo Pomante

Fakhteh Ghalami, Mean-Variance efficient portfolio and skewed assets performance comparison, Advisor: Prof. Shmuel Baruch

Mihael Huzun , Portfolio Performance Analysis: Combining Cryptocurrencies with Traditional Assets, Advisor: Prof. Ugo Pomante

Fatemeh Khazaei ,  The Effect of Knowledge and Experience of Board of Companies on Mergers and Acquisitions , Advisor: Prof. Rocco Ciciretti

Eduard Andrei Kiss, Forecasting Exchange Rates: An Empirical Analysis, Advisor: Prof. Marianna Brunetti

Domenico Leone , Central bank, monetary policy and interest rates, Advisor: Prof. Stefano Herzel

Francesco Milani , The Integration of ESG Factors into the Investment Process: an application in the Portfolio Construction Model, Advisor: Prof. Ugo Pomante

Mirabela Cristina Niscoveanu, Can ESG investing do well while doing good? An analysis of the ESG European funds from 2000 to nowadays, Advisor: Prof. Rocco Ciciretti

Marco Piazza, Can the performance measurement influence mutual funds' valuation?, Advisor: Prof. Ugo Pomante

Davide Radicioni, The Black-Litterman Model: Rigorous Review, Implementation and Application to the Market, Advisor: Prof. Shmuel Baruch

Sebastian Richter , Neural Network assisted Option Pricing under Rough Volatility:   An Empirical Validation., Advisor: Prof. Alessandro Ramponi

Paiman Sobati, GANs and their application in option pricing, Advisor: Prof. Alessandro Ramponi

Gianluca Varrenti, Correlation between assets during market down phases: analysis on the Dow Jones Index, Advisor: Prof. Shmuel Baruch

Assel Altynbek , European Cooperative Banking Group, Advisor: Prof. Stefano Caiazza

Riccardo Angeli , The Covid-19 Effect on Oil Spot and Futures Market and Potential Hedging Strategies, Advisor: Prof. Gianni Nicolini

Nils Anton Ludvig Anner , Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms, Advisor: Prof. Alessandro Ramponi

Masumeh Babaei , Empirical Analysis of the Cryptocurrencies and Bitcoin Price Dynamics, Advisor: Prof. Vincenzo Farina

Riccardo Bruno , Electricity Price Forecasting with Unobserved Components Models, Advisor: Prof. Tommaso Proietti

Giorgia Carena , Stochastic models for simultaneous trading in the lit market and a dark pool: a numerical study, Advisor: Prof. Katia Colaneri

Asia Ciaramella , Hedge Funds and Mutual Funds Performance: A Comparison Analysis, Advisor: Prof. Rocco Ciciretti

Gaetano Cipriani , Volatility Estimation in Presence of Microstructure Noise, Advisor: Prof. Davide Pirino

Lavinia Del Treste , The announcement effect of green bond issuers on their listed share price, Advisor: Prof. Rocco Ciciretti

Paola Di Stasi , Black Litteman Model and Risk Budgeting, Advisor: Prof. Ugo Pomante

Valentina Federici , Different Trends in SRI: The Case of Europe and Usa, Advisor: Prof. Rocco Ciciretti

Michela Fiore , Reinforcement Learning for Automatic Option Hedging, Advisor: Prof. Stefano Herzel

Gianluca Franceschini , The Effectiveness of Weather Derivatives as Risk Mitigating Tool in Wine Industry, Advisor: Prof. Gianni Nicolini

Emanuele Gatta , ESG Portfolios Premia: A Comparison Between Risks and Characteristics, Advisor: Prof. Rocco Ciciretti

Omar Gaye , ESG Factors and Performance in Portfolio Construction: Energy and Power Utility Sector, Advisor: Prof. Ugo Pomante

Saeid Hosseinzadehfarahami, On Rough Fractional Stochastic Volatility andthe Turbocharging Monte Carlo simulation for rBergomi model, Advisor: Prof. Alessandro Ramponi 

Alessandra Iacobone , A Comparison Between Italian Health System and American Health System, Advisor: Prof. Maura Mezzetti

Mina Ibrahim Tawfik Ibrahim , CFD Trading in Financial Markets, Advisor: Prof. Gianni Nicolini

Alessio Incelli , An Advanced Application of Black-Litterman Model: The EBL Approach, Advisor: Prof. Ugo Pomante

Antonio Litterio , Detection of Structural Breaks in HAR Model, Advisor: Prof. Gianluca Cubadda

Daniele Maggio , Corporate Reputation: a Systematic ESG Risk Approach, Advisor: Prof. Rocco Ciciretti

Zaur Mammadov, Implied Volatility Surface: Difference Between Heston Model and SVI Parametrization, Advisor: Prof. Alessandro Ramponi

Daniele Martinelli , Reinforcement Learning for Trading Applications: The Q-Learning Algorithm, Advisor: Prof. Stefano Grassi

Laura Morrocchi , Risk-Return Optimization and ESG Opportunities in the Current Financial Market: an Empirical Study on Model Portfolios, Advisor: Prof. Ugo Pomante

Francesca Romana Multari , Quantile Dependence and Directional Predictability in Economic and Financial Time Series, Advisor: Prof. Tommaso Proietti

Tiara Fatin Binti Nasip , A Comparison of Methods for Sentiment Analysis of Private Companies: The Case of Recent Tweets about Tesla Inc., Advisor: Prof. Alessio Farcomeni

Alberto Noe’ , The Determinants of Italian Households Financial Planning, Advisor: Prof. Rocco Ciciretti

Saeedeh Ostovari , Investigating the Statistical Properties of the Hurst Exponent Estimator of Rough Volatility Model, Advisor: Prof. Tommaso Proietti

Dario Piperni , Green Minus Black: The Risk-adjusted Performance of SRI, Advisor: Prof. Vincenzo Farina

Meruyert Ramazanova, A review of volatility estimators for financial assets, Advisor: Prof. Davide Pirino

Matteo Ronci , Volatility Analysis of Bitcoin and Ethereum Before and After the Introduction of Futures, Advisor: Prof. Gianni Nicolini

Roberto Rosina , The Determinants of Financial Derivatives Use: an Empirical Analysis From European Banking Industry, Advisor: Prof. Gianni Nicolini

Edoardo Sabetta , Doing Well While Doing Good? A Performance Comparison Analysis of European Mutual Funds in Pandemic Times, Advisor: Prof. Vincenzo Farina

Flaminia Sarrantonio , Power market fundamental approach to study the dynamics of the electricity sector in Latin America, Advisor: Prof. Rocco Ciciretti

Roberta Maria Segatore , Estimation of a Structural Model for Stale Prices, Advisor: Prof. Davide Pirino

Noemi Viggiano , Does it matter to be green? The Effect of Green Investment on Corporate Behavior, Advisor: Prof. Stefano Herzel

Mario Viola , Tactical Asset Allocation : A Machine Learning Approach, Advisor: Prof. Ugo Pomante

Aizhan Yermekova , Determinants of M&A premium: evidence from quantile regression analysis, Advisor: Prof. Alessio Farcomeni

Faranak Alikhah , Time Reversibility of Financial Time Series, Advisor: Prof. Tommaso Proietti

Francesco Apa Eduardo , Integration between ethical activity and economic dynamics: the banking sector, Advisor: Prof. Amalia Diurni

Francesco Berretti , The Determinants of Italian Household Financial Planning, Advisor: Prof. Rocco Ciciretti

Andrea Bonelli , Forecasting Realized Volatility: Long vs Short Memory Processes, Advisor: Prof. Gianluca Cubadda

Ana Botorce , Corporate Social Responsibility in Canadian Firms, Advisor: Prof. Rocco Ciciretti

Marco Bruno , The determinants of the Reverse Takeovers: the case of Europe, Advisor: Prof. Vincenzo Farina

Andrea Bulla , Venture capital investments in cyber-security startups: a social network approach, Advisor: Prof. Vincenzo Farina

Veronica Cannas , What happens to options when the underlying returns are predictable?, Advisor: Prof. Stefano Herzel

Giulia Carbotti , A regime-switching cointegration approach to pairs trading, Advisor: Prof. Gianluca Cubadda

Andrea Carcani , Scenario analysis for the energy sector’s transition risk in the context of climate change, Advisor: Matteo Bissiri

Paolo Cianci , ESG rating and financial performance during the SARS-CoV-2, Advisor: Prof. Rocco Ciciretti

Antonio Colasanto , Monte-Carlo assessment of excess staleness estimators, Advisor: Prof. Davide Pirino

Gaia D'Angeli , DCC-NL: model validation for portfolio and risk management in a large dimensional setting, Advisor: Prof. Tommaso Proietti

Samy Zakria Moustafa El Hallag , Forecasting the Electricity Demand in the Italian Market through Supervised Learning Methods, Advisor: Prof. Gianluca Cubadda

Federico Fattinnanzi , Climate Change, Political Economy and Financial Distress, Advisor: Prof. Ugo Pomante

Eric Festuccia , Predictability of Expected Returns, Advisor: Prof. Stefano Herzel

Marco Fioravanti , Anticipating market volatility using google trends data, Advisor: Prof. Vincenzo Farina

Diego Oswaldo Floreano Dominguez , Style-based Value at Risk: an investigation of equity emerging market mutual funds, Advisor: Prof. Ugo Pomante

Emanuel Ignacio Gamboa Quintanilla , Pairs Trading Strategy Efficiency: Cointegration Analysis in Derivative Markets, Advisor: Prof. Gianni Nicolini

Yasaman Ghafarisomeh , Detecting Asymmetric Jumps and Semi-variation in Forecasting Realized Volatility, Advisor: Prof. Gianluca Cubadda

Fidan Huseynli , The Green Finance approach to financial performance, Advisor: Prof. Rocco Ciciretti

Edis Izejrosji , Measuring the connectedness between European stock indices with variance decomposition, Advisor: Prof. Tommaso Proietti

Lorenzo Lo Pinto , Multivariate Logit Models for Household Financial Hardship in Italy, Advisor: Prof. Maura Mezzetti

Marco Lorenzo , High-Dimensional Density Forecasting for Financial Time Series, Advisor: Prof. Tommaso Proietti

Veronica Lupi , Approximated MLE for diffusion models discretely sampled: Focus on Vasicek and CIR, Advisor: Prof. Davide Pirino

Irene Magni , Private Equity and Turnaround Funds: an Italian case study, Advisor: Prof. Vincenzo Farina

Francesco Marconi , A Model for Central Counterparty Risk with Stochastic Default Intensities, Advisor: Prof. Katia Colaneri

Simona Margareta Mare , Empirical Analysis of the Mortgage Market Granted to Italian Families, Advisor: Prof. Rocco Ciciretti

Gianluca Michienzi , ESG vs Blend Investments: Evidence from International Markets, Advisor: Prof. Ugo Pomante

Hamed Molaei Shebilouysofla , The influence of corporate governance and firm performance on CEO compensation: panel analysis from the Canadian corporate sector, Advisor: Prof. Rocco Ciciretti

Simone Mosconi , Artificial Neural Networks for Option Pricing: an application to the Heston model Calibration, Advisor: Prof. Alessandro Ramponi

Merfat Nofal , Modelling Credit Risk with Big Data, Advisor: Prof. Tommaso Proietti

Alessandro Olivieri , Merger and Acquisition operations in the global energy sector: assessing Efficient Market Hypothesis, Advisor: Prof. Rocco Ciciretti

Saverio Piacenti , Value Creation Effect: Spin Off vs. Equity Carve Out, Advisor: Prof. Vincenzo Farina

Leonardo Procoli , The impact of Coronavirus (COVID-19) on market volatility, Advisor: Prof. Vincenzo Farina

Alberto Rainieri , Collateralized Interest Rate Swaps, Advisor: Prof. Stefano Herzel

Mohammad Rashidi Ranjbar , Comparison of volatility models for Bitcoin, Advisor: Prof. Tommaso Proietti

Daniele Ruffa , The Private Equity funds performance, Advisor: Prof. Vincenzo Farina

Cesare Russo , Portfolio construction considering the impact of shocks on higher moments, Advisor: Prof. Stefano Grassi

Mahshid Teimouri Toulabi , Machine Learning Algorithms in Default Loans Prediction, Advisor: Prof. Tommaso Proietti

Oscar Gustav Anders Thelander , Currency Options: Analytical Tractability versus Empirical Misspecification, Advisor: Prof. Stefano Herzel

Riccardo Traglia , A dynamic approach to Black-Litterman: Implementing a M-GARCH derived covariance matrix , Advisor: Prof. Ugo Pomante

Duc Dieu Vinh Vu , Risk assessment with value at risk and expected shortfall during crises, Advisor: Prof. Tommaso Proietti

Chaotong Wang , The financial performance of professional manager succession in the family business-a case study in the Media group, Advisor: Prof. Luca Gnan

Calascibetta Francesco , Crypto Coin and Applycation of Financial Derivatives on the ICOs, Advisor: Prof. Gianni Nicolini

Capoano Lorenzo , Optimal Combination of realised volatility estimators: a forecasting approach, Advisor: Prof. Gianluca Cubadda

Carosi Annalisa , Modeling the evolution of market uncertainty. Hedge Fund returns and Volatility of Aggregate Volatility within a dynamic perspective, Advisor: Prof. Stefano Herzel

Cascioli Aurora , High Dimensional Covariance Matrices Estimation: a comparison between Orthogonal GARCH and Generalized Orthogonal GARCH, Advisor: Prof. Tommaso Proietti

Cesaretta Claudio , Private Equity and Portfolio Performance, Risk and Diversification, Advisor: Prof. Ugo Pomante

Chen Jinghui , The Effect of Horizon on Dynamic Asset Allocation without Parameter Uncertainty, Advisor: Prof. Stefano Herzel

Ciarletta Sara , Fintech: analysis of the relevance in the different activity’s areas of Italian Banks, Advisor: Prof. Vincenzo Farina 

Corio Michele , Forecasting stock index volatility using the daily range of price, Advisor: Prof. Tommaso Proietti

Delghandi Maral , Impact of Political Events on Stock Market Returns: Empirical Evidence from Tehran Stock Exchange, Advisor: Prof. Vincenzo Farina

Di Geronimo Leonardo , Optimal financial resources for Central Counterparties. Introducing default dependence of clearing members: a mixed binomial approach, Advisor: Prof. Stefano Herzel

Di Lelio Andrea , An Investable Cryptocurrency Index: the CRT30 Index, Advisor: Prof. Ugo Pomante

Di Matteo Alessandro , Modeling and forecasting the Italian yield curve with a dynamic Nelson-Siegel approach., Advisor: Prof. Alessandro Ramponi

Isernia Luigi , Weather risk management for utilities & energy: methodologies for estimating exposure and managing risk, Advisor: Prof. Gianni Nicolini

Krajenbrink Menno-Jan , Lockup Expiration Effects, Advisor: Prof. Vincenzo Farina

Li Zuho , Econometric Analysis of Skewness and Risk Premia in Asset Returns, Advisor: Prof. Tommaso Proietti

Molinaro Gianluca , A Financial Stress Index for Turkey, Advisor: Prof. Gianluca Cubadda

Monti Michela , Shrinkage estimation of the covariance matrix for portfolio optimization: an empirical assessment, Advisor: Prof. Gianluca Cubadda

Novikovs Rihards , Governance factors determining FDI inflows in emerging countries: cross-regional comparative study., Advisor: Prof. Vincenzo Farina

Sabbi Federica , The sentiment analysis: an application with the Black Litterman Model, Advisor: Prof. Ugo Pomante

Saponaro Onofrio , Cointegrated market neutral portfolios: identification and performance analysis, Advisor: Prof. Gianluca Cubadda

Sorbo Michele , Risk volatility measures: a comparison., Advisor: Prof. Tommaso Proietti

Sperati Alfredo Paolo , The impacts of ESG Performances on Cost of Equity and Cost of Debt, Advisor: Prof. Vincenzo Farina

Stursa Zbynek , Thresholding for high-dimensional covariance matrix estimation, Advisor: Prof. Tommaso Proietti

Turmunkh Khongor , The use of Derivatives by Mutual funds, Advisor: Prof. Gianni Nicolini

Wang Yuming , Refining the father to son model with the cases of Chinese family firms, Advisor: Prof. Luca Gnan

Yusifli Parvana , Female Employees’ Job Burnout in Foreign Capital Enterprise in China, Advisor: Prof. Alessandro Hinna

Yusifzada Parviz , Professionalization and Managerialization in Small and Medium Family Firms, Advisor: Prof. Luca Gnan

Zeccolella Gianlorenzo , The effect of Mergers and Acquisitions on Bidder Default Risk in the Banking Sector, Advisor: Prof. Stefano Caiazza

Bardeli Aurel , Attribution of ex-ante performance and risk to market sectors, Advisor: Prof. Ugo Pomante

Bilardi Andrea , Dimension Reduction Methods and Har: forecasting analysis, Advisor: Prof. Prof. Gianluca Cubadda

Borin Carlo , A comparison of wrong-way risk Credit Value Adjustment using different techniques: change of measure, 2D Monte Carlo, Gaussian Copula resampling approach and Basel III, Advisor: Prof. Alessandro Ramponi

Caprasecca Mirko , Can market reaction on announcement date affect M&A failure? Evidence from financial deals in the U.S. market, Advisor: Prof. Stefano Caiazza

Ciolli Andrea , Target Cumulative Abnormal Return to M&As in US Banking Sector from 2000-2018, Advisor: Prof. Stefano Caiazza

Diaferia Savino , Merger Arbitrage: Profitability and Risk-Return Characteristic in the Italian Market, Advisor: Prof. Vincenzo Farina

Filippi  Nicolò , The counterparty credit risk and its implication on profit and loss statement and regulatory capital, Advisor: Prof. Stefano Herzel

Forte Federica , Portfolio Optimization using Conditional Value at Risk: Application and Comparison with the Black-Litterman Model, Advisor: Prof. Ugo Pomante

Gurbanli Orkhan , The Impact of Training and Motivation on Organizational Performance, Advisor: Prof. Alessandro Hinna

Iovino Valeria , A zombie bank is in town! Empirical analysis about the health condition of the Eurozone banking system in the 20th century, Advisor: Prof. Stefano Caiazza

Orlova Victoria , Estimating probability of sovereign defaults, Advisor: Prof. Maura Mezzetti

Porcaro Tommaso , Financial Applications of Time-Varying Copulas, Advisor: Prof. Tommaso Proietti

Rezaeighasemkheili Ali , The impact of news on the US dollar index futures, Advisor: Prof. Gianni Nicolini

Serafino Barbara , Renewable Energy Derivatives and the securitization of cash-flows, Advisor: Prof. Gianni Nicolini

Smorra Luca , The Italian market of NPL: Banca IFIS case study, Advisor: Prof. Vincenzo Farina

Zhang Ge , Derivatives Usage and Gender Diversity of Board of Directors, Advisor: Prof. Gianni Nicolini

Cairone Simone , The inductive research of the change in decision-making of family business founder, Advisor: Prof. Tommaso Proietti

Genovese Jacopo , The Growth of Reits Market in East Asia, Advisor: Prof. Ugo Pomante

Gentile Cristina , Measures of Asymmetric Information in Financial Markets, Advisor: Prof. Davide Pirino

Novikov Yurii , What are the country specific factors that influence the foreign direct investment?, Advisor: Prof. Vincenzo Farina

Renzetti Francesco ,   Empirical analysis on the phenomenon of delisting, Advisor: Prof. Vincenzo Farina

Schiavo Edoardo , Financial crisis, Buyout investments, and Corporate performance: the Italian case, Advisor: Prof. Vincenzo Farina

Fu Yite , The inductive research of the change in decision-making of family business founder, Advisor: Prof. Luca Gnan

Vittiglio Emanuele , Cointegration and trading opportunities: an empirical analysis Advisor: Prof. Vincenzo Farina

Rognone Lavinia , Pricing interest rate derivatives in a negative yield environment, Advisor: Prof. Stefano Herzel

Melone Alessandro , Understanding and Forecasting Financial Market Volatility Over Long Horizons, Advisor: Prof. Tommaso Proietti

D'Aria Marianna , The Credit Valuation Adjustment: Regulation and Implementation, Advisor: Prof. Stefano Herzel

Cesaroni Giulia , Contingent Convertible Bonds - A Market-Conform Equity Derivative Model, Advisor: Prof. Stefano Herzel

Carrozi Stefano , Negative Rates in the SABR Model, Advisor: Prof. Stefano Herzel

Bernardi Cristiano , Four Moments Portfolio Optimization: an Empirical Test, Advisor: Prof. Ugo Pomante

Almonte Stefania , Assessing the predictive ability of financial variables through a mixed frequency approach: some evidence from the Italian case, Advisor: Prof. Gianluca Cubadda

Baggia Douglas , Succession Process In Family Owned Businesses in Honduras: Incorporating new young members, Advisor: Prof. Luca Gnan

Barrano Salvatore , The Implied volatility as a risk predictor: the case of Brexit, Advisor: Prof. Gianni Nicolini

Giacomazzi Consuelo , Optimization of CFDs portfolio implementing SMA technique, Advisor: Prof. Gianni Nicolini

Moradi Hadi , The Determinants and Investigating of CANSLIM Method Profitability for Evaluation of Tehran Stock Exchange Stocks, Advisor: Prof. Sandro Brunelli

Maino Andrea , Time Varying Dependence and Panic Copula model for Risk Measurements, Advisor: Prof. Stefano Herzel

Petrova Denitza ,On Psychological Barriers and Price Behaviors: Evidence from Eastern European Markets, Advisor: Prof. Gianni Nicolini

Riccardo Antonio , Vector Heterogeneous Autoregressive Index Model: an application on NYSE mahjor Banks'assets, Advisor: Prof. Gianluca Cubadda

Svetlomirova Biliana , Cryptocurrency:Nature and Features, Advisor: Prof. Williams De Ascaniis

Verneau Guglielmo , Loss Estimation in Structured Credit Products, Advisor: Prof. Stefano Herzel

Taraborrelli Jessica , The Management of A Real Estate Fund, Advisor: Prof. Ugo Pomante

Scalia Roberto , Forecasting Real Estate Prices, Advisor: Prof. Tommaso Proietti

Sardo Simone , Sovereign CDS: how the default probability influence the market, Advisor: Prof. Gianni Nicolini

Santurelli Simone , The impact of reputation on banks liquidity risk: a study of italian listed banks, Advisor: Prof.  Vincenzo Farina

Rinaldi Francesco , Portfolio construction and valuation: machine learning techniques applied to quantitative trading system, Advisor: Prof. Ugo Pomante

Procacci Pierfrancesco , Flexible Bayesian Framework in Portfolio Construction: Entropy Pooling, Advisor: Prof. Ugo Pomante

Petrilli Luka , Undirected Graphs for Large Scale Portfolios of European Stocks, Advisor: Prof. Tommaso Proietti

Maino Andrea , Behavioral risk modeling and Agency MBS valuation, Advisor: Prof. Stefano Herzel

Luzzi Francesco , News related to macroeconomic variable as risk factors on equity returns: evidence from Asian markets, Advisor: Prof. Rocco Ciciretti

Jiao Xuyang , Are There Tournaments in Mutual Funds?, Advisor: Prof. Stefano Herzel

Iasenzio Stefano , A Vector Heterogeneous Autoregressive Index Model for Realized Volatility: some empirical results for European Equity Indexes, Advisor: Prof. Gianluca Cubadda

Cortesini Alessandro , Test on Fama French factor on Hong Kong Singapore and India stock market, Advisor: Prof. Rocco Ciciretti

Cordiner Lorenzo , Statistical Arbitrage with Index Options: An Empirical Study of the European Option Market, Advisor: Prof.  Marianna Brunetti

Carnevali Laura , An Empirical Analysis of the Italian attitude toward Mortagage Refinancing, Advisor: Prof.  Rocco Ciciretti

Avoli Alessandro , The CDS spread and spread charge determinants in the US Market, Advisor: Prof.  Marianna Brunetti

Arnone Raffaella , Econometric analysis of Value-at-Risk and Expected Shortfall, Advisor: Prof. Tommaso Proietti

Di Cosmo Marco , Calendar anomalies: Evidence from Real Estate Investment vehicles, Advisor: Prof.  Gianluca Mattarocci

Fortuna Alice , Multiple bankin: the Italian case, Advisor: Prof. Marianna Brunetti

Korsaye Sofonias Alemu , Artificial Neural Networks for Implied Volatility Surface: Construction and Dynamics, Advisor: Prof. Cesare Robotti

Romaniello Christian , Central Couterparties: A numerical implementation of the default waterfall, Advisor: Prof. Stefano Herzel

De Michelis Francesco , Technical Anlysis, Advisor: Prof. Stefano Herzel

Torelli Edoardo , Convexity Correction for Interest Rate Derivatives, Advisor: Prof. Stefano Herzel

Aguilar Jauregui Catherine Stefany , Sustainability and outreach trade-off of Microfinance Institutions in Peru, Advisor: Prof. Leonardo Becchetti

Bologni Enrico , The effects of Microfinance on poverty reduction. The Case study of Buen Vivir, Ecuador, Advisor: Prof. Leonardo Becchetti

Borzi Chiara , Real Estate Factor Premium, Advisor: Prof. Gianluca Mattarocci

Brescia Mauro , The optimal capital structure of the firm with taxes, bankruptcy costs and stochastic volatility, Advisor: Prof. Stefano Herzel

Cavarretta Maria Chiara , Power Options in the Italian electricity market: an assessment of their potential in managing risk for the Italian operators, Advisor: Prof. Gianni Nicolini

Cea Lorenzo , A LIBOR Market Model with Multiple Curves, Advisor: Prof. Stefano Herzel

D'Orazio Gianpaolo , Portfolio construction and empirical testing of Black Litterman model, Advisor: Prof. Ugo Pomante

Goudarzi Mostafa , Dynamic Spillover Effect in Future Markets, Advisor: Prof. Gianni Nicolini

Leone Stefano , ALM logics for Pension Funds, Advisor: Prof.Ugo Pomante

Principe Claudia , Impact of International Cross-Listing on Stock Liquidity: Evidence from European Stock Exchanges, Advisor: Prof. Gianluca Mattarocci

Sajadi Zahra , A review on the impact of venture capital on family businesses, Advisor: Prof. Luca Gnan

Serafini Alberto , Comparative analysis of socially responsible and traditional investments, Advisor: Prof. Stefano Herzel

Turchetti Cristiano , An affine term structure for European interbank risk, Advisor: Prof. Stefano Herzel

Verico Marco , Eccomi!. The App for one-to-one volunteerism. From idea generation to fundraising, Advisor: Prof. Williams De Ascaniis

Amiraslanov Farid , A comparative analysis of the family business governance in UK, Canada and China, Advisor: Prof. Luca Gnan

Azzarelli Filippo , The impact of corporate governance on capital structure, Advisor: Prof. Vincenzo Farina

Bernardo Giuseppe , Lines of credit in corporate finance, Advisor: Prof. Gianluca Mattarocci Colarossi Daniele, Active management and returns dispersion, Advisor: Prof. Rocco Ciciretti

Di Mario Alessio , Prospectus content, investor attention and IPO first-day returns, Advisor: Prof. Vincenzo Farina

Ducci Lorenzo , Estimating the probability of default with balance sheet information: an empirical analysis on US SMES during the last financial crisis, Advisor: Prof. Marianna Brunetti

Febo Angelo W. , Liquidity, market impact and optimal trading strategies, Advisor: Prof. Stefano Herzel Formichella Valentina, The credit value adjustment, Advisor: Prof. Stefano Herzel

Giosi Pierluigi , Pricing variance swap contracts, Advisor: Prof. Stefano Herzel

Gomez Walter Alexandar , Return based style analysis of globally invested flexible mutual funds, Advisor: Prof. Ugo Pomante

Klimovich Sergey , An analysis of co-integration of financial derivative markets in a worldwide perspective, Advisor: Prof. Gianni Nicolini

Li Yanjun , Credit cycle and macroprudential policy, Advisor: Prof. Luisa Corrado

Maccari Laura , The creditworthiness evaluation through the rating system: an empirical application to the construction industry, Advisor: Prof. Gianluca Mattarocci

Malek Mohammadi M. , Portfolio optimization with parametric quadratic programming, Advisor: Prof. Stefano Herzel

Mao Wenli , The influence of venture capital on family governance system, Advisor: Prof. Luca Gnan

Mtengwa Nyashadzashe , Impact investing: an advanced market capital allocation framework, Advisor: Prof. Ugo Pomante

Piccirelli Alessia , How diversification affects idiosyncratic and overall risk of open-end equity funds, Advisor: Prof. Rocco Ciciretti

Quaranta Nicoletta , CSR and idiosyncratic volatility, Advisor: Prof. Rocco Ciciretti

Ranalli Giulia , Minibond. What kind of issuers are SMES? Evidence from the financial statement analysis, Advisor: Prof. Ugo Pomante

Setaro Arianna , Short term inflation density forecasting with a Bayesian Var, Advisor: Prof. Tommaso Proietti

Stragapede Michele , Portfolio value at risk with jumps, Advisor: Prof. Stefano Herzel

Strauss Magdalena , A discussion of a matrix exponential model for spatially  correlated data, Advisor: Prof. Maura Mezzetti

Tamburri Matteo , A comparison of forecasting performances between random walk, Garch-m and Egarch-m, Advisor: Prof. Marianna Brunetti

Totev Aleksandar , Corporate ownership of American and German companies: a comparative analysis of dual-class shares. Market performance and tendencies, Advisor: Prof. Luca Gnan

Troiano Federica , Labor market differences between natives and immigrants, Advisor: Prof. Franco Peracchi

Tucci Simone , The usefulness of the omega ratio in evaluating investment opportunities in the Greek Market, during the  crisis, Advisor: Prof. Gianluca Mattarocci

Viselli Gabriele , The share of income from non-intermediation activities in the European cooperative Banks, Advisor: Prof. Rocco Ciciretti

Wang Cizhi , Case study in Wanda and Huawei, so that we can find some suggestion on shareholder structure and employees motivation, Advisor: Prof. Luca Gnan

Abbasov Farid , Liqudity risk at Basel III, Advisor: Prof. Gianluca Mattarocci

Canori Alfredo , Basel III: A new regulatory framework, Advisor: Prof. Sandro Brunelli

Cesari Lorenzo , ESG performance and financial performance of equity mutual funds, Advisor: Prof. Stefano Herzel Di Rocco Andrea, Corporate social responsibility around the world, Advisor: Prof. Vincenzo Farina

Ficcadenti Valerio , Inflation and growth: some empirical results from the European Union countries, Advisor: Prof. Giovanni Trovato

Kelemen Iringo Anna , Tactical asset allocation embedding with the Black-Litterman model's views, Advisor: Prof. Ugo Pomante

Kraujutaityte Faustina , Competition among stock exchanges : comparison of listing regulations of singapore stock exchange and London stock exchange, Advisor: Prof. Nicoletta Ciocca

Marcone Michela , Stochastic methods for capital budgeting analysis, Advisor: Prof. Roberto Monte

Norante Valentini Giulio , Multinational companies and currency risk in the speculative attacks, Advisor: Prof. Gianluca Mattarocci

Petrini Francesco Maria , From Bail-out to Bail-in: a new framework of rules", Advisor: Prof. Leonardo Becchetti

Petrongari Michael , Future on Commodities: Agrex  – Agricultural Derivatives Exchange, Advisor: Prof. Gianni Nicolini

Rahimli Sarkhan , Constant proportion portfolio insurance strategies and Related gap risk measures for processes with jumps and Applications, Advisor: Prof. Sergio Scarlatti

Razi Bibi Alia , The difference between the modern marketing management practices of family business, Advisor: Prof. Luca Gnan

Recupero Silvia , The Gold Pricing: Evidence from the Spot and the Future Gold Pricing, Advisor: Prof. Gianni Nicolini

Scalone Chiara , Italian target maturity funds: investment style and performance analysis, Advisor: Prof. Rocco Ciciretti

Tallarida Tiziano , Asset market microstructure: order book analysis, Advisor: Prof. Stefano Herzel

Bendziute Dovile , Commercial and Investment Banking in Economies with Asymmetric Information, Advisor: Prof. Eloisa Campioni

Cilla Edoardo , Measuring and modelling the risk of liquidity, Advisor: Prof. Stefano Herzel

Del Signore Piera , Evaluating Density Forecasts for Financial Time Series, Advisor: Prof. Tommaso Proietti

Donato Ludovico , Investor Sentiment and Asset Prices Can a protable trading strategy be devised from a Pessimism index?, Advisor: Prof. Ugo Pomante

Girardi Alessio , Investing in vice: An empirical study based on the U.S. market, Advisor: Prof. Ugo Pomante

Grasso Adriana , Dynamic portfolio strategies with liquidity costs, * Advisor: Prof. Stefano Herzel

Haddad Khalil , Financial Analysis: Different Parts and Their Usages, Advisor: Prof. Ugo Pomante

Lamaj Erisa , An overview of VaR. An application of Block Maxima method in risk management for heavy tailed stock returns, Advisor: Prof. Ugo Pomante

Malatesta Fabrizio , Ethical funds and liquidity risk, * Advisor: Prof. Stefano Herzel

Mariotti Sara , Pricing and hedging CDOs using copulas, Advisor: Prof. Stefano Herzel

Oshafi Vesna , Trading in secondary loan markets, Advisor: Prof. Andrea Kamal Attar

Sarcinelli Nicola , Value creation through strategic diversification: the Fincantieri case, Advisor: Prof. Sandro Brunelli

* judged "particularly relevant" in the contest of the prestigious Bank of Italy Prize "Giorgio Mortara", for the best thesis of the year

Capo Mariangela , Managing risk exposures using the risk budgeting approach: the equal risk contribution portfolio construction and analysis, Advisor: Prof. Ugo Pomante

D'Onofrio Rossella , Pricing the Energy: the case of the European natural gas, Advisor: Prof. Stefano Herzel

Flores Deborah , A tactical asset allocation perspective applied to the black-litterman model, Advisor: Prof. Ugo Pomante Inglese Gabriele, Home bias and new measures of bias in asset allocation, Advisor: Prof. Ugo Pomante

Lautizi Francesco , Empirical estimates of pricing kernel and risk aversion, Advisor: Prof. Stefano Herzel Manenti Dario, Flexible funds: strategies and performances, Advisor: Prof. Ugo Pomante

Pavana Marco , Mutual fund performance: active versus passive management, Advisor: Prof. Ugo Pomante

Sangrigoli Dario , The evolution of the finance-growth nexus: past studies and new perspectives, Advisor: Prof. Leonardo Becchetti

Santorelli Giulio , Demographic structure and asset returns: A new prospective from international data, Advisor: Prof. Marianna Brunetti

Cassetti Sante , Sequential conditional Correlation, Advisor: Prof. Tommaso Proietti

Santangelo Daniela , The Goldman Sachs event and SRI funds, Advisor: Prof. Rocco Ciciretti

Formica Francesco , Basel III and its potential impact on global banks, Advisor: Prof. Stefano Caiazza

Periotto Marco , Provate equity and venture  capital market in Italy: performances and potential development, Advisor: Prof. Vincenzo Farina

Research Topics & Ideas: Finance

120+ Finance Research Topic Ideas To Fast-Track Your Project

If you’re just starting out exploring potential research topics for your finance-related dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research topic ideation process by providing a hearty list of finance-centric research topics and ideas.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . To develop a suitable education-related research topic, you’ll need to identify a clear and convincing research gap , and a viable plan of action to fill that gap.

If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, if you’d like hands-on help, consider our 1-on-1 coaching service .

Overview: Finance Research Topics

• Corporate finance topics
• Investment banking topics
• Private equity & VC
• Asset management
• Hedge funds
• Financial planning & advisory
• Quantitative finance
• Treasury management
• Financial technology (FinTech)
• Commercial banking
• International finance

Corporate Finance

These research topic ideas explore a breadth of issues ranging from the examination of capital structure to the exploration of financial strategies in mergers and acquisitions.

• Evaluating the impact of capital structure on firm performance across different industries
• Assessing the effectiveness of financial management practices in emerging markets
• A comparative analysis of the cost of capital and financial structure in multinational corporations across different regulatory environments
• Examining how integrating sustainability and CSR initiatives affect a corporation’s financial performance and brand reputation
• Analysing how rigorous financial analysis informs strategic decisions and contributes to corporate growth
• Examining the relationship between corporate governance structures and financial performance
• A comparative analysis of financing strategies among mergers and acquisitions
• Evaluating the importance of financial transparency and its impact on investor relations and trust
• Investigating the role of financial flexibility in strategic investment decisions during economic downturns
• Investigating how different dividend policies affect shareholder value and the firm’s financial performance

Investment Banking

The list below presents a series of research topics exploring the multifaceted dimensions of investment banking, with a particular focus on its evolution following the 2008 financial crisis.

• Analysing the evolution and impact of regulatory frameworks in investment banking post-2008 financial crisis
• Investigating the challenges and opportunities associated with cross-border M&As facilitated by investment banks.
• Evaluating the role of investment banks in facilitating mergers and acquisitions in emerging markets
• Analysing the transformation brought about by digital technologies in the delivery of investment banking services and its effects on efficiency and client satisfaction.
• Evaluating the role of investment banks in promoting sustainable finance and the integration of Environmental, Social, and Governance (ESG) criteria in investment decisions.
• Assessing the impact of technology on the efficiency and effectiveness of investment banking services
• Examining the effectiveness of investment banks in pricing and marketing IPOs, and the subsequent performance of these IPOs in the stock market.
• A comparative analysis of different risk management strategies employed by investment banks
• Examining the relationship between investment banking fees and corporate performance
• A comparative analysis of competitive strategies employed by leading investment banks and their impact on market share and profitability

Private Equity & Venture Capital (VC)

These research topic ideas are centred on venture capital and private equity investments, with a focus on their impact on technological startups, emerging technologies, and broader economic ecosystems.

• Investigating the determinants of successful venture capital investments in tech startups
• Analysing the trends and outcomes of venture capital funding in emerging technologies such as artificial intelligence, blockchain, or clean energy
• Assessing the performance and return on investment of different exit strategies employed by venture capital firms
• Assessing the impact of private equity investments on the financial performance of SMEs
• Analysing the role of venture capital in fostering innovation and entrepreneurship
• Evaluating the exit strategies of private equity firms: A comparative analysis
• Exploring the ethical considerations in private equity and venture capital financing
• Investigating how private equity ownership influences operational efficiency and overall business performance
• Evaluating the effectiveness of corporate governance structures in companies backed by private equity investments
• Examining how the regulatory environment in different regions affects the operations, investments and performance of private equity and venture capital firms

Asset Management

This list includes a range of research topic ideas focused on asset management, probing into the effectiveness of various strategies, the integration of technology, and the alignment with ethical principles among other key dimensions.

• Analysing the effectiveness of different asset allocation strategies in diverse economic environments
• Analysing the methodologies and effectiveness of performance attribution in asset management firms
• Assessing the impact of environmental, social, and governance (ESG) criteria on fund performance
• Examining the role of robo-advisors in modern asset management
• Evaluating how advancements in technology are reshaping portfolio management strategies within asset management firms
• Evaluating the performance persistence of mutual funds and hedge funds
• Investigating the long-term performance of portfolios managed with ethical or socially responsible investing principles
• Investigating the behavioural biases in individual and institutional investment decisions
• Examining the asset allocation strategies employed by pension funds and their impact on long-term fund performance
• Assessing the operational efficiency of asset management firms and its correlation with fund performance

Hedge Funds

Here we explore research topics related to hedge fund operations and strategies, including their implications on corporate governance, financial market stability, and regulatory compliance among other critical facets.

• Assessing the impact of hedge fund activism on corporate governance and financial performance
• Analysing the effectiveness and implications of market-neutral strategies employed by hedge funds
• Investigating how different fee structures impact the performance and investor attraction to hedge funds
• Evaluating the contribution of hedge funds to financial market liquidity and the implications for market stability
• Analysing the risk-return profile of hedge fund strategies during financial crises
• Evaluating the influence of regulatory changes on hedge fund operations and performance
• Examining the level of transparency and disclosure practices in the hedge fund industry and its impact on investor trust and regulatory compliance
• Assessing the contribution of hedge funds to systemic risk in financial markets, and the effectiveness of regulatory measures in mitigating such risks
• Examining the role of hedge funds in financial market stability
• Investigating the determinants of hedge fund success: A comparative analysis

Financial Planning and Advisory

This list explores various research topic ideas related to financial planning, focusing on the effects of financial literacy, the adoption of digital tools, taxation policies, and the role of financial advisors.

• Evaluating the impact of financial literacy on individual financial planning effectiveness
• Analysing how different taxation policies influence financial planning strategies among individuals and businesses
• Evaluating the effectiveness and user adoption of digital tools in modern financial planning practices
• Investigating the adequacy of long-term financial planning strategies in ensuring retirement security
• Assessing the role of financial education in shaping financial planning behaviour among different demographic groups
• Examining the impact of psychological biases on financial planning and decision-making, and strategies to mitigate these biases
• Assessing the behavioural factors influencing financial planning decisions
• Examining the role of financial advisors in managing retirement savings
• A comparative analysis of traditional versus robo-advisory in financial planning
• Investigating the ethics of financial advisory practices

The following list delves into research topics within the insurance sector, touching on the technological transformations, regulatory shifts, and evolving consumer behaviours among other pivotal aspects.

• Analysing the impact of technology adoption on insurance pricing and risk management
• Analysing the influence of Insurtech innovations on the competitive dynamics and consumer choices in insurance markets
• Investigating the factors affecting consumer behaviour in insurance product selection and the role of digital channels in influencing decisions
• Assessing the effect of regulatory changes on insurance product offerings
• Examining the determinants of insurance penetration in emerging markets
• Evaluating the operational efficiency of claims management processes in insurance companies and its impact on customer satisfaction
• Examining the evolution and effectiveness of risk assessment models used in insurance underwriting and their impact on pricing and coverage
• Evaluating the role of insurance in financial stability and economic development
• Investigating the impact of climate change on insurance models and products
• Exploring the challenges and opportunities in underwriting cyber insurance in the face of evolving cyber threats and regulations

Quantitative Finance

These topic ideas span the development of asset pricing models, evaluation of machine learning algorithms, and the exploration of ethical implications among other pivotal areas.

• Developing and testing new quantitative models for asset pricing
• Analysing the effectiveness and limitations of machine learning algorithms in predicting financial market movements
• Assessing the effectiveness of various risk management techniques in quantitative finance
• Evaluating the advancements in portfolio optimisation techniques and their impact on risk-adjusted returns
• Evaluating the impact of high-frequency trading on market efficiency and stability
• Investigating the influence of algorithmic trading strategies on market efficiency and liquidity
• Examining the risk parity approach in asset allocation and its effectiveness in different market conditions
• Examining the application of machine learning and artificial intelligence in quantitative financial analysis
• Investigating the ethical implications of quantitative financial innovations
• Assessing the profitability and market impact of statistical arbitrage strategies considering different market microstructures

Treasury Management

The following topic ideas explore treasury management, focusing on modernisation through technological advancements, the impact on firm liquidity, and the intertwined relationship with corporate governance among other crucial areas.

• Analysing the impact of treasury management practices on firm liquidity and profitability
• Analysing the role of automation in enhancing operational efficiency and strategic decision-making in treasury management
• Evaluating the effectiveness of various cash management strategies in multinational corporations
• Investigating the potential of blockchain technology in streamlining treasury operations and enhancing transparency
• Examining the role of treasury management in mitigating financial risks
• Evaluating the accuracy and effectiveness of various cash flow forecasting techniques employed in treasury management
• Assessing the impact of technological advancements on treasury management operations
• Examining the effectiveness of different foreign exchange risk management strategies employed by treasury managers in multinational corporations
• Assessing the impact of regulatory compliance requirements on the operational and strategic aspects of treasury management
• Investigating the relationship between treasury management and corporate governance

Financial Technology (FinTech)

The following research topic ideas explore the transformative potential of blockchain, the rise of open banking, and the burgeoning landscape of peer-to-peer lending among other focal areas.

• Evaluating the impact of blockchain technology on financial services
• Investigating the implications of open banking on consumer data privacy and financial services competition
• Assessing the role of FinTech in financial inclusion in emerging markets
• Analysing the role of peer-to-peer lending platforms in promoting financial inclusion and their impact on traditional banking systems
• Examining the cybersecurity challenges faced by FinTech firms and the regulatory measures to ensure data protection and financial stability
• Examining the regulatory challenges and opportunities in the FinTech ecosystem
• Assessing the impact of artificial intelligence on the delivery of financial services, customer experience, and operational efficiency within FinTech firms
• Analysing the adoption and impact of cryptocurrencies on traditional financial systems
• Investigating the determinants of success for FinTech startups

Commercial Banking

These topic ideas span commercial banking, encompassing digital transformation, support for small and medium-sized enterprises (SMEs), and the evolving regulatory and competitive landscape among other key themes.

• Assessing the impact of digital transformation on commercial banking services and competitiveness
• Analysing the impact of digital transformation on customer experience and operational efficiency in commercial banking
• Evaluating the role of commercial banks in supporting small and medium-sized enterprises (SMEs)
• Investigating the effectiveness of credit risk management practices and their impact on bank profitability and financial stability
• Examining the relationship between commercial banking practices and financial stability
• Evaluating the implications of open banking frameworks on the competitive landscape and service innovation in commercial banking
• Assessing how regulatory changes affect lending practices and risk appetite of commercial banks
• Examining how commercial banks are adapting their strategies in response to competition from FinTech firms and changing consumer preferences
• Analysing the impact of regulatory compliance on commercial banking operations
• Investigating the determinants of customer satisfaction and loyalty in commercial banking

International Finance

The folowing research topic ideas are centred around international finance and global economic dynamics, delving into aspects like exchange rate fluctuations, international financial regulations, and the role of international financial institutions among other pivotal areas.

• Analysing the determinants of exchange rate fluctuations and their impact on international trade
• Analysing the influence of global trade agreements on international financial flows and foreign direct investments
• Evaluating the effectiveness of international portfolio diversification strategies in mitigating risks and enhancing returns
• Evaluating the role of international financial institutions in global financial stability
• Investigating the role and implications of offshore financial centres on international financial stability and regulatory harmonisation
• Examining the impact of global financial crises on emerging market economies
• Examining the challenges and regulatory frameworks associated with cross-border banking operations
• Assessing the effectiveness of international financial regulations
• Investigating the challenges and opportunities of cross-border mergers and acquisitions

Choosing A Research Topic

These finance-related research topic ideas are starting points to guide your thinking. They are intentionally very broad and open-ended. By engaging with the currently literature in your field of interest, you’ll be able to narrow down your focus to a specific research gap .

When choosing a topic , you’ll need to take into account its originality, relevance, feasibility, and the resources you have at your disposal. Make sure to align your interest and expertise in the subject with your university program’s specific requirements. Always consult your academic advisor to ensure that your chosen topic not only meets the academic criteria but also provides a valuable contribution to the field. 

If you need a helping hand, feel free to check out our private coaching service here.

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thank you for suggest those topic, I want to ask you about the subjects related to the fintech, can i measure it and how?

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Banking and Finance

The Master’s thesis is an important part of your Master's Programme. The thesis is written individually and in English.

Below you can find information about the time schedule and deadlines, the regulations, the U.S.E. thesis award, and some tips.

Time schedule

Kick-off event for each master programme is organized, usually between 16 and 30 November, but deviations are possible. You will be informed about

• Potential thesis topics
• Potential supervisors and second readers
• Guidelines in case you want to propose your own topic
• Opportunities for a research internship in combination with your thesis

Matchmaking with your supervisor and the second reader takes place in December-January. The second reader will be involved in the process to (i) to grade and provide feedback on the research proposal and set up of the thesis, and (ii) read and independently grade the final manuscript. Grades for both will be based on the independent assessments of the supervisor and second reader; the supervisor consults with the second reader to establish a final grade that will be made available to the student.

Period 3 (5 EC)

Research proposal. At the end of period 3 you are supposed to have written a full research proposal. This implies you have done extensive literature research, addressed a research gap, drafted research questions, and develop a plan for empirical data analysis. You are usually also supposed to have collected the empirical  material for your thesis, or at minimum, developed a plan for data collection.

You present and/or discuss your draft research proposal with your supervisor and second reader.

Deadline to upload your research proposal via Osiris Case. The proposal will be graded (weight 10%). If you upload the research proposal too late, or not at all, the research proposal will be graded with a 1. When your progress is insufficient at this point, you will have to put in substantial extra effort in period 4 to be able to finish your thesis in time.

Deadline for supervisor (including consultation with second reader, resulting in the final grade) to finish the assessment in Osiris Case.

Period 4 (10 EC)

Develop and finalise thesis. You collect remaining data and literature, analyse data, and write your thesis.

June  17-21

You present and/or discuss your draft thesis in a meeting or final seminar organized by your supervisor and second reader, and receive final comments.

Deadline to upload the final version of your thesis in Osiris Case. The thesis will be graded (weight 90%).

Deadline for supervisor to finish the assessment (including consultation with second reader, resulting in the final grade) in Osiris Case.

Number of meetings

The thesis process has at least four compulsory meetings/deadlines:

• April 8-11: discuss your draft research proposal and full literature review
• April 12: hand in your final resarch proposal and full literature review online via Osiris Case. Specific instructions will be supplied on Blackboard. Concerning the literature review, consider coverage of at least 20 relevant academic papers as a reference point. However, your supervisor may set other expectations during the process.
• June 17-21: present/discuss your draft thesis
• June 28: hand in your final thesis online via Osiris Case (specific instructions will be supplied)

Theses need to be handed in via OSIRIS Student  (tab Cases > Thesis Assessment (U.S.E.)) to the thesis supervisor and second reader. The supervisor checks the thesis on plagiarism, grades it, and digitally fills in the two evaluation forms ( evaluation form 10% and evaluation form 90% ). You can check the evaluation forms in OSIRIS Student  (after your supervisor finalises the assessment and determined the grade in Osiris).

• For your research proposal no retake is possible.

For your master thesis , a retake is possible. Conditions:

• Your unrounded final score (10%*proposal + 90%*thesis) is less than 5.5, but at least 4.0.
• Your supervisor will provide you with feedback/guidance of what to improve, but only once. Afterwards no additional feedback or guidance can be claimed from the supervisor (holiday season).
• You can resubmit your master thesis only once.
• The deadline to upload your revised thesis is August 4, after which the grade will be handed in by the supervisor at the latest by August 18.
• The rounded final grade for the thesis cannot be higher than a 6; this is only to be fair to students finishing in shorter time.

In case you do not succeed in finishing your thesis with a passing grade in semester 2, including the retake opportunity, you can consult the study advisor and submit a request to redo the thesis with a new topic and supervisor in period 1+2 of the next academic year if you think the following requirements apply:

• You have worked on the thesis in the regular period, but did not receive a passing grade.
• You have put in enough effort. The thesis evaluation form, including the written feedback by your supervisor, serves as the basis for this and your thesis grade is at least 4.
• You have finished all other courses of your master programme.

The request needs to be made ultimately on September 15 (or when this is a Saturday or Sunday, the Friday before September 15). The study advisor will contact the Board of Examiners (BoE). The BoE takes the final decision.

If your unrounded final grade is less than 4.0, no retake is possible. You will have to enroll again, and start with a new topic and supervisor in November 2024. Thus, you will then develop a new thesis in period 3 and 4 of the academic year 2024/25. 

In some circumstances the July deadline may be extended. See ‘Regulations’ (hereafter).

U.S.E. thesis regulations Academic Masters 2022-2023

• All theses must be written and finished within semester 2.
• All theses will be checked on plagiarism.
• In agreement with the second supervisor, the thesis supervisor will determine the final grade and fill in the Thesis Evaluation Form, which is then presented to you.
• The supervisor grades the thesis within 10 working days from receiving the material, and makes sure the results are processed administratively. Deadline to hand in final versions of the thesis to the supervisor and co-reader is June 30th . Deadline for supervisor to hand in the thesis grade is July 14th .
• In case of special personal circumstances, the Board of Examiners may grant a postponement of the deadline, following consultation with the MSc coordinator.
• When you have stopped working on your thesis during semester 2 for other reasons than special personal circumstances, or do not hand in your thesis on time, or when you receive an insufficient grade, you will have to start again in the next academic year (at the kick-off event in November), with a new thesis subject and new supervisor, unless the requirements mentioned under 10 apply.
• You can resubmit your master thesis only once .
• The deadline to hand in your revised thesis is August 9th, after which the grade will be handed in by the supervisor at the latest by August 18th .
• If your unrounded final grade is less than 4.0, no retake is possible. You will have to subscribe again, and start with a new topic and supervisor in November 2023 . Thus, you will then develop a new thesis in period 3 and 4 of the academic year 2023/24 .
• You have put in enough effort . The thesis evaluation form, including the written feedback by your supervisor, serves as the basis for this and your thesis grade is at least 4.
• The request needs to be made ultimately on September 15 (or when this is a Saturday or Sunday, the Friday before September 15 ). The study advisor will contact the Board of Examiners (BoE). The BoE takes the final decision.
• In addition to the cum laude classification in art. 6.2 of the Education and Examination Regulations: if you do an external research in combination with your thesis and this prevents you to graduate in one year, and as a consequence you do not qualify for a cum laude graduation, the Board of Examiners may apply a special (leniency) regulation.

Publish your thesis

It is not mandatory, but we recommend you submit your thesis to the Students Theses Archive .

Thesis award

U.S.E. Master’s Thesis Award

Each year, Utrecht University School of Economics (U.S.E.) chooses the top Master's theses from each of the 1-year MSc programmes. These theses are recognised with the  U.S.E. Master's Thesis Award . The winning theses need to be written and completed in semester 2 and are chosen for their relevance, academic merit, and particularly for their integration of a ‘real world perspective’ into an economics issue. Furthermore, the submitted thesis must have received a mark of at least an 8.5. Out of these ‘best-in-programme’ theses, the one thesis that stands out most receives additional accolades. The authors of the winning theses are awarded with a certificate during the Master’s Graduation ceremony.

UU Best Master’s Thesis

Utrecht University awards a prize for the best Master's thesis written at the University. It is awarded every year during the opening of the new academic year. The winner will receive an award which consists of a certificate and €1,500. Nominees need to meet certain criteria. The submitted graduate thesis or research must have received a mark of at least an 8.5 for instance. U.S.E. strives to select and submit one candidate each year. More information can be found on the university website .

Tips and tricks

Tips and tricks about academic research, writing skills, etcetera you can find in the Thesis Manual and Toolbox (this is not available yet)

For workshops, courses and individual writing tutoring see the Skills lab  and Libguide for an overview on much consulted information sources Economics

Research Data Management

When you write a thesis, you are dealing with Research Data Management: processing data and possibly also personal data, for example when you conduct interviews. In the latter case, you are then dealing with the General Data Protection Regulation (GDPR). You also need to secure your data properly at all times. It is therefore important that you know what you have to comply with in terms of legislation and university frameworks. Please figure this out before you start writing your thesis. Your thesis supervisor can help you with this, ask for the guidelines. More information can be found on the following websites:

• https://www.uu.nl/en/research/research-data-management
• https://www.uu.nl/en/research/research-data-management/guides/handling-personal-data

Subscriptions to databases

U.S.E. has acquired subscriptions to

• Wharton Research Data Services (WRDS), 
• Mergent FISD,
• Refitiviv Eikon and Datastream

Compustat covers financial information and executive compensation data for publicly listed companies in the United States. WRDS provides access to Compustat and other free databases using a Web interface, SAS, Matlab, Python and R. Furthermore, WRDS offers a cloud environment with a SAS 9.4 installation. WRDS and Compustat can be accessed through the Wharton website and are available to all U.S.E. staff and students. Bank Focus is accessible through Bureau van Dijk .

See also the UU Library Search Engine ; and select 'Economie'.

Follow Utrecht University

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Department of Finance

Quicklinks und sprachwechsel, main navigation.

The preparation for the application as well as the writing of the Bachelor or Master's thesis at the Department of Finance entails different steps, whereby the application process is described in detail here.

• You find your own topic, write a Research Proposal and submit it via DF Thesis Market.
• Choose one of the provided Topic Proposals and apply for the corresponding topic on the DF Thesis Market including a letter of motivation.
• Supervisor: If your Research Proposal has been accepted or your application for an existing topic has been successful, you will be contacted by the person who will supervise you in your thesis. Based on your Research Proposal inputs, your supervisor will formulate the thesis assignment.
• Thesis assignment on OLAT: The task assignment includes your official thesis assignment for the written thesis. It can be collected on OLAT from the moment you have been informed by your supervisor. Once you collect the thesis assignment on OLAT, the time limit of six months starts.
• Time limit: Start working on your thesis early and discuss problems with your supervisor. Nevertheless, remember that a Bachelor or Master’s thesis is to be written independently.
• Submission: You must submit your thesis via OLAT i.e. you upload your thesis and any additional documents/attachments as a ZIP-file to OLAT.
• Grading of task: You receive your grade within a month after submission.

The following Video in German shows the recording of a presentation (PDF, 276 KB) in which the students were informed. It goes more into detail about the individual steps.

The prerequisite for writing a Bachelor and Master's thesis at the Department of Finance is relevant prior knowledge in the corresponding subject area. In particular, the relevant lectures must have been attended and passed. Provided Topic Proposals may contain further requirements, which you will find in the respective proposal.

It is also important that the rules and instructions of the Dean's Office ( study and graduation ) are generally to be noted. The responsibility regarding compliance with these regulations lies with you.

Application

In order to write a thesis at the Department of Finance, a digital application via the DF Thesis Market is required. You will need the following documents for the application:

• Curriculum Vitae (as PDF)
• Transcript of records (as PDF, current export from the Module Booking)
• Research Proposal (if you propose a topic of your own)

For the application via the Department of Finance Thesis Market, you also need your UZH login credentials (shortname and password).

There are two ways to apply for a thesis at the Department of Finance:

Option A: Own topic

Elaborate your own suggested topic and write a Research Proposal. On two to three pages, the Research Proposal summarises your motivation, the objectives, the planned procedure and the expected results. The following documents serve as a guide:

• Instructions for writing a Research Proposal (PDF, 114 KB)
• Example of a Research Proposal (PDF, 205 KB)

If you would like to write an empirical paper, check before submitting your application whether the data you need can be found in the available databases . It is advisable to check with a concrete example whether the data quality is sufficient (e.g., availability of time series).

It is important that you assign your Research Proposal to the correct research area so that it can be made available to appropriate supervisors. The research areas and fields of interest listed in the table below can serve as a decision-making aid. The links of the Professors lead to the Bachelor and Master's theses that they supervised so far. They can give an intuition on typical topics for writing a thesis.

Based on your Research Proposal, the final thesis assignment will be issued. However, the Department of Finance reserves the right to ask for improvements to the proposal, to make changes, to provide a different topic or to reject the application.

Option B: Provided topic

Apply for a topic provided by a supervisor via DF Thesis Market . Look at the topics on the marketplace, choose one and apply. Note that in addition to a CV and transcript of records, a short letter of motivation is also required for the application. Describe how the provided topic matches your skills and interests, and how the topic fits into your course of study.

Useful documents

As guidance to help you estimate the length of a thesis, we provide you with two sample theses:

• Bachelor’s thesis: The different theories of the 2010 Flash Crash with main focus on high-frequency trading (PDF, 1 MB)
• Master’s thesis: Strategic Allocation to Return Factors (PDF, 1 MB)

Additionally you can find a template for LaTeX (ZIP, 414 KB) .

Further notes

The Department of Finance strongly recommends that you start finding a topic for your Bachelor or Master's thesis at an early stage. The application must be submitted at least one month before the desired starting month. For example if you want to start writing your thesis at the beginning of May, you must apply by the end of March. 

The matching process usually takes about a month, sometimes longer (especially for your own proposals), since all supervisors supervise several theses, and your own proposal must match the interests of your supervisor in terms of content. We will inform you as soon as the matching process is completed, or if we need further information or adjustments from you. If you want/need to start as soon as possible, you also have the option to apply to one of the posted proposals.

The DF endeavours to offer all applicants the opportunity to write a thesis at the Department of Finance, but we cannot guarantee a specific topic or a specific supervisor. Temporary bottlenecks may occur in the supervision. If you have any questions or problems in connection with your application, please contact the study coordinator and Managing Director of the DF, Dr. Benjamin Wilding, at [email protected] .

Research interest

Bereichs-navigation, unterseiten von theses.

• DF Thesis Market
• FAQ for Students

We appreciate that you are interested in writing a thesis at the Institute of Banking and Finance. The following sections provide information on potential areas for both Bachelor and Master theses. When conducting your thesis, you will have to critically review the relevant literature and to carry out your own quantitative analysis. This requires applying software for statistical analysis (R, Matlab, or Stata). To prepare you, we offer online courses in scientific writing and an introduction to R. We are looking forward to supervising your thesis!

Bachelor theses

Master theses, general information on final theses, contact for general questions about theses, registration.

After you have been assigned to the Institute of Banking and Finance through the central allocation procedure of the Faculty of Economics and Management, you can apply for one of the topics listed below. If you have any questions, please contact Brian von Knoblauch .

Please note: Bachelor theses at our institute are always related to empirical research questions. We there strongly (!) recommend to conduct a seminar thesis at our institute and to take finance related classes.

An information session that covers organizational aspects and introduces available topics will be held on Tuesday, February 13, (Warning: Changed Date!) 2024, from 2:30pm - 4:00pm via Cisco WebEx . To join the session (via browser or app), please click here . Further information is available via this link (in German).

To choose preferences and your preferred starting date, please click here: Application form

Please also note that - to register your thesis - it is mandatory to complete our introductions to Scientific Writing and R .

Bachelor theses not related to the central allocation prodecure (industrial engineers or second attempts) can be registered throughout the whole year.  Please note that we can only offer a limited number of Wi-Ing places at our institute in the upcoming summer semester 2023. Currently (as of 01.02.2024) four places are still open.

As soon as you have received your topic, you will have 2 weeks to prepare a proposal (please take into account time to revise the proposal!). On 2-3 pages, the proposal should cover the following elements:

• Problem setting and objective of the thesis
• Methodology and theoretical and/or conceptual approaches
• Necessary data and sources for data acquisition
• Expected knowledge gains for research and/or practice
• Basic literature (from international, peer-reviewed journals)

After the proposal has been accepted by your supervisor, your bachelor thesis will be registered immediately.

Bachelor theses in Behavioral Finance

Theoretical part of the task:

• Explain the "noise trader theory" according to De Long et al (1990).
• Define the term "investor sentiment" and outline approaches to measure sentiment.

Empirical part of the task:

• Investigate the impact of investor sentiment on stock market returns or anomalies.
• Test the robustness of your results with respect to combinations of selected control variables. Are you results robust to subperiods?

Basic literature:

• Baker, M. and Wurgler, J. (2006): Investor Sentiment and the Cross-Section of Stock Returns.  The Journal of Finance,  61(4), 1645–1680.
• Baker, M. and Wurgler, J. (2007): Investor Sentiment in the Stock Market. Journal of Economic Perspectives,  21(2), 129–152.
• De Long, J.B., Shleifer, A., Summers, L.H., and Waldmann, R.J. (1990): Noise Trader Risk in Financial Markets.  Journal of Political Economy,  98(4), 703–738.
• Fisher, K.L. and Statman, M. (2000): Investor Sentiment and Stock Returns.  Financial Analysts Journal,  56(2), 16–23.
• Frazzini, A. and Pedersen, L.H. (2014): Betting against beta.  Journal of Financial Economics,  111(1), 1-25.
• Jegadeesh, N. and Titman, S. (1993): Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.  The Journal of Finance,  48(1), 65-91.
• Lee, W.Y., Jiang, C.X., and Indro, D.C. (2002): Stock market volatility, excess returns, and the role of investor sentiment. Journal of Banking & Finance,  26(12), 2277–2299.
• Lee, C.M.C., Shleifer, A., and Thaler, R.H. (1991): Investor Sentiment and the Closed-End Fund Puzzle. The Journal of Finance, 46(1), 75–109.
• Lemmon, M. and Portniaguina, E. (2006): Consumer Confidence and Asset Prices: Some Empirical Evidence.  The Review of Financial Studies , 19(4), 1499–1529.  
• Stambaugh, R.F., Yu, J., and Yuan, Y. (2012): The short of it: Investor sentiment and anomalies.  Journal of Financial Economics , 104(2), 288-302.
• Kenneth French Data Library
• Refinitiv Datastream
• Describe the term "investor sentiment" and explain ways to measure it. In particular, address methods for text-based measurement of investor sentiment.
• Provide a review of relevant literature examining the relationship between text-based sentiment measures and stock returns.
• Calculate a text-based sentiment measure and explain its step-by-step derivation from raw text to final measure.
• Perform a descriptive analysis of the sentiment measure.
• Analysieren den Zusammenhang zwischen Ihrem hergeleiteten Stimmungsmaß und Aktienrenditen anhand von Regressionsmodellen.
• Analyze the relationship between your inferred sentiment measure and stock returns using regression models.
• McDonald, B. and Loughran, T. (2011): When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks. The Journal of Finance, 66(1), 35-65.
• Smales, L. A. (2017): The importance of fear: investor sentiment and stock market returns.  Applied Economics , 49(34), 3395-3421.
• Stambaugh, R.F., Yu, J., and Yuan, Y. (2012): The short of it: Investor sentiment and anomalies. Journal of Financial Economics, Special Issue on Investor Sentiment,  104(2), 288-302.
• Tetlock, P.C. (2007): Giving Content to Investor Sentiment: The Role of Media in the Stock Market. The Journal of Finance, 62(3), 1139-1168.
• Refinitiv Workspace
• Loughran-McDonald Master Dictionary
• New York Times News Article
• Separate the empirical evidence of investor participation from the assumptions of classical portfolio theory. Motivate and explain determinants of participation.
• Formulate a probit model in accordance with relevant models from the literature. Introduce the probit regression.
• Among other things, you will deal with estimation using the maximum likelihood method.

 Empirical part of the task:

• Check the developed model by means of a panel data set.
• Explicitly refer to the definitions you used to create variables and describe the data set.
• Perform the estimation of the probit model and interpret your results.
• Grinblatt, M., Keloharju, M., and Linnainmaa, J. (2011): IQ and stock market participation. The Journal of Finance, 66 (6), 2121-2164.
• Kaustia, M. and Torstila, S. (2011): Stock market aversion? Political preferences and stock market participation. Journal of Financial Economics, 100(1), 98-112.
• Van Rooij, M., Lusardi, A., and Alessie, R. (2011): Financial literacy and stock market participation. Journal of Financial Economics, 101(2), 449-472.
• Brooks, C. (2019):  Introductory Econometrics for Finance. Fourth edition. Cambridge, United Kingdom; New York, NY: Cambridge University Press.
• Polkovnichenko, V. (2005): Household Portfolio Diversification: A Case for Rank-Dependent Preferences.  The Review of Financial Studies, 18(4), 1467–1502.
• Malmendier,  U. and Nagel, S. (2019): Depression Babies: Do Macroeconomic Experiences Affect Risk Taking?.  The Quarterly Journal of Economics,  126(1), 373–416.

 Data:

• Explain the difference between normative and descriptive decision theories.
• Introduce and explain selected static and dynamic portfolio insurance strategies.
• Explain Cumulative Prospect Theory (CPT) and its role for the evaluation of portfolio insurance strategies.
• Conduct a simulation study comparing different selected portfolio insurance strategies in regard to their CPT value and the corresponding expected utility (EUT). Do the decisions of CPT investors differ from an EUT investor?
• Interpret your results in regards to the sensitivity of your results to the different CPT parameters. Is any parameter more important than others?
• Tversky, A. and Kahneman, D. (1992): Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty , 5(4), 297-323.
• Dichtl, H. and Drobetz, W. (2011): Portfolio insurance and prospect theory investors: Popularity and optimal design of capital protected financial products. Journal of Banking and Finance , 35(7), 1683-1697.
• Dierkes, M., Erner, C., and Zeisberger, S. (2010): Investment horizon and the attractiveness of investment strategies: a behavioral approach. Journal of Banking and Finance, 34, 1032-1046.
• Explain the Cumulative Prospect Theory (CPT) as a descriptive decision theory and outline differences from normative decision theories.
• Explain how individual stocks can be evaluated as "prospects" under the CPT.
• Present the model-theoretical prediction for stock returns of companies depending on their CPT value.

Quantitative part of the task:

• Calculate the CPT values of all companies in a relevant sample of a stock market (e.g., US market).
• Analyze the performance of companies depending on their CPT values using portfolio construction and Fama-MacBeth regressions.
• Evaluate with your performance analysis whether factor models (e.g., CAPM, Fama-French Three-Factor Model) can explain these returns.
• Tversky, A. and Kahneman, D., (1992 ), Advances in prospect theory: Cumulative representation of uncertainty, Journal of Risk and Uncertainty , 5(4), 297-323. Cambridge, United Kingdom.
• Barberis, N., Abhiroop, M. and Baolian, W., (2016 ), Prospect theory and stock returns: An empirical test, The review of financial studies , 29(11), 3068-3107. Cambridge, United Kingdom.
• Bali, T.G., Engle, R. F. and Murray, S., (2016 ), Empirical asset pricing: The cross section of stock returns, John Wiley & Sons, Cambridge, United Kingdom.

Bachelor theses in Asset Management

• Define sustainability criteria (e.g. ESG) and explain the Morningstar-Sustainability-Ranking .
• Give an overview of the relevant literature of performance measurements and explain common descriptive and risk-adjusted performance measurements.
• Calculate and compare performance measurements for different categories of sustainability funds and a market benchmark.
• Identify and interpret differences between the categories.
• Bauer, R., Koedijk, K., and Rotten, R. (2005): International evidence on ethical mutual fund performance and investment style. Journal of Banking & Finance, 29(7), 1751-1767.
• Brooks, C. (2019): Introductory Econometrics for Finance. Fourth edition. Cambridge, United Kingdom ; New York, NY: Cambridge University Press.
• Schroeder, M. (2006): Is there a Difference? The Performance Characteristics of SRI Equity Indices. Journal of Business Finance & Accounting, 34(1-2), 331-348.
• Database of Richard Stehle
• Morningstar

Bachelor theses in Risk Management

• Introduce in general terms the role of volatility in financial markets.
• Explain the concept of Realized Volatility and provide an overview of traditional econometric forecasting models, such as Corsi's (2008) heterogenous autoregressive (HAR) model.
• Explain selected machine learning methods and their estimation procedures in the context of Realized Volatility predictions.
• Evaluate the predictive performance of selected machine learning methods based on a chosen data set, such as daily Realized Volatility of the S&P 500.
• Compare your results with those of selected traditional econometric models and discuss your findings.

Basic literature (selection):

• Corsi, F. (2008): A Simple Approximate Long-Memory Model of Realized Volatility.  Journal of Financial Econometrics,  7(2), 174–196.
• Bucci, A. (2020): Realized Volatility Forecasting with Neural Networks.  Journal of Financial Econometrics,  18(3), 502–531.
• Christensen, K., Siggaard, M., and Veliyev, B. (2022): A Machine Learning Approach to Volatility Forecasting. Journal of Financial Econometrics.
• James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013): An introduction to statistical learning: with applications in R. 2nd Edition, Springer.

Data Resources:

• Oxford Realized Library
• Provide an overview of the relevant literature on the forecasting of credit defaults of companies and individuals.Pay special attention to so-called P2P loans.
• Identify relevant characteristics of private debtors that potentially affect the risk of credit default.
• Explain the logit regression and address the marginal effects and the ROC procedure.
• Set up a logit model to estimate the probability of default of personal loans.
• Analyse the Lending Club data set and present the characteristics of the loans granted there.
• Do you estimate the logit model set up on the basis of the data, can defaults be forecast?
• Emekter, R., Tu, Y., Jirasakuldech, B., and Lu, M. (2015): Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending.  Applied Economics, 47(1), 54-70.
• Hull, J. (2018): Risk management and financial institutions. Hoboken, New Jersey: Wiley & Sons.
• Brooks, C. (2014): Introductory econometrics for finance. Cambridge: Cambridge University Press. 
• Lending Club Privatkredite, via kaggle.com

Bachelor theses in Asset Pricing

• Describe the momentum anomaly and explain how to construct the momentum strategy.
• Note both advantages and disadvantages of the momentum strategy. In particular, focus on momentum crashes.
• Outline the risk management strategies of Barroso and Santa-Clara (2015) and Dierkes and Krupski (2022).
• Estimate the momentum strategy for the U.S. market over the period from 1926 to 2022.
• Implement the risk management strategies of Barosso and Santa-Clara (2015) and Dierkes and Krupski (2022).
• Outline both advantages and disadvantages of each strategy.
• Barroso, P. and Santa-Clara, P. (2015): Momentum has its moments. Journal of Financial Economics, 116(1), 111–120.
• Cooper, M.J., Gutierrez, R.C., and Hameed, A. (2004): Market States and Momentum. The Journal of Finance, 59(3), 1345–1365.
• Dierkes, M. and Krupski, J. (2022): Isolating momentum crashes. Journal of Empirical Finance, 66, 1-22.
• Daniel, K. and Moskowitz, T.J. (2016): Momentum crashes. Journal of Financial Economics, 122(1), 221–247.
• Jegadeesh, N. and Titman, S. (1993): Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Kenneth French's database
• Derive the Capital Asset Pricing Model (CAPM) and explain why the use of additional factors can be a useful extension.
• Outline the three-factor model of Fama and French (1993).
• Explain the value and the size effect on which the three-factor model is built.
• Calulate the risk factors yourself using monthly price data.
• Analyze to which extend multi-factor models can increase the explanability of return data.
• Explicitly conduct a performance test against the CAPM.
• What influence do the factors of value and size have on returns? Do they match your expectations? 
• Fama, E. F. and French, K. R. (1993): Common risk factors in the returns on stocks and bonds.  Journal of Financial Economics, 33(1), 3–56.
• Fama, E. F. and French, K. R. (1992): The cross-section of expected stock returns.  Journal of Finance, 47(2), 427–465.
• Fama, E. F. and French, K. R. (2015): A five-factor asset pricing model.  Journal of Financial Economics, 116(1), 1–22.
• Empirical research shows a strong negative relationship between returns and idiosyncratic volatility.
• Derive why in neoclassical finance theory idiosyncratic volatility should not affect returns.
• Introduce the so-called idiosyncratic volatility puzzle and provide an overview of relevant related literature. Explain possible solutions to the puzzle.
• Calculate idiosyncratic volatilities for a cross-section of stocks.
• Evaluate pricing effects of idiosyncratic volatility using portfolio formation and investigate whether they are significant.
• Ang, A., Hodrick, R. J., Xing, Y., and Zhang, X. (2006): The cross‐section of volatility and expected returns.  Journal of Finance, 61(1), 259-299.
• Ang, A., Hodrick, R. J., Xing, Y., and Zhang, X. (2009): High idiosyncratic volatility and low returns: International and further US evidence.  Journal of Financial Economics, 91(1), 1-23.
• Bali, T. G. and Cakici, N. (2008): Idiosyncratic volatility and the cross section of expected returns.  Journal of Financial and Quantitative Analysis, 43(01), 29-58.
• Short-Term Reversal is one of the most distinctive anomalies in asset pricing. Explain the (short-term) reversal effect and show why this effect counteracts the weak form of the efficient market hypothesis.
• Introduce to the relevant literatur.
• Provide an overview of the different explanatory approaches.
• Conduct an empirical analysis of the short term reversal effect using linear regression and portfolio formation.
• Investigate whether the short term reversal effect can be explained by capital market models (e.g. CAPM, Fama-French three factor model).
• Jegadeesh, N. (1990): Evidence of predictable behavior of security returns.  Journal of Finance, 45(3), 881-898.
• Jegadeesh, N. and Titman, S. (1995): Short-horizon return reversals and the bid-ask spread. Journal of Financial Intermediation, 4(2), 116-132.
• Campbell, J. Y., Grossman, S. J., and Wang, J. (1993): Trading volume and serial correlation in stock returns.  Quarterly Journal of Economics, 108, 905–939.
• Kelly, B., Moskowitz, T., and Pruitt, S. (2021): Understanding Momentum and Reversal.  Journal of Financial Economics, 140(3), 726-743.
• CRSP US Stock Databases
• Introduce the topic of economic uncertainty and distinguish this concept from other concepts relevant to finance such as risk and investor sentiment.
• Introduce the literature on uncertainty measurement and explain the different methodological approaches. In this context, explain in detail the derivation of two selected measures.
• Explain why economic uncertainty can have a theoretical impact on real and financial economics.  In this context, present empirical literature that examines the relationship between uncertainty and financial markets.
• Perform a descriptive analysis of the selected uncertainty measures.
• Analyze the relationship between the selected uncertainty measures and stock returns using regression models.
• Bloom, N. (2014): Fluctuations in Uncertainty. Journal of Economic Perspectives, 28(2), 153-176.
• Brogaard, J., and Detzel, A. (2015): The Asset-Pricing Implications of Government Economic Policy Uncertainty. Management Science, 61(1), 3-18.
• Jurado, K., Ludvigson, S. C., and Serena, N. (2015): Measuring Uncertainty. American Economic Review,  105(3), 1177-1216.
• Knight, F.H. (1921): Risk, Uncertainty and Profit. Houghton Mifflin Company, Boston , 682-690.
• Datenbank von Sydney Ludvigson
• EPU Datenbank

Bachelor theses in Corporate Finance

• Standard methods for calculating the cost of capital use realized returns as an approximation for expected future returns. Implicit cost of capital offer an alternative in which the estimator for the cost of capital is derived implicitly and ex ante from a valuation model.
• Give an introduction into the valuation of companies.
• Derive the cost of capital model according to Ohlson and Juettner-Nauroth (2005).
• The cost of capital model above requires forecasts of earnings. Explain how earnings can be estimated via regression using the model of Hou et al. (2012). Additionally, address advantages and disadvantages for using estimates from analysts as alternative.
• Conduct an empirical analysis of implicit capital costs at firm and market level for the German (European) stock market.
• Compare the implied cost of capital estimates when using analyst forecasts and when using earnings forecasts by the model of Hou et al. (2012), respectively. 
• Hou, K., Van Dijk, M. A., and Zhang, Y. (2012): The implied cost of capital: A new approach.  Journal of Accounting and Economics, 53(3), 504–526.
• Ohlson, J. A. and Juettner-Nauroth, B. E. (2005): Expected eps and eps growth as determinants of value.  Review of accounting studies, 10(2), 349–365.
• CDAX/STOXX Europe 600 (from Refinitiv Workspace)
• I/B/E/S Estimates

Application for master theses is possible throughout the year, i.e. there are no fixed deadlines. However, you should contact us at least 4 weeks before the desired registration date to find a topic and prepare a proposal.

Please contact Brian von Knoblauch by e-mail and include the following information:

• Choose two preferences from the topics listed below.
• Outline your motivation.
• When is your master thesis supposed to start?
• An up-to-date overview of your grades.

Subsequently, you will receive an e-mail from your supervisor (depending on the topic) to arrange an appointment. In this meeting, we will define the research question of your thesis and outline what should be included in your proposal.

As soon as you have received your topic, you will have roughly 3 weeks to prepare a proposal (please take into account time to revise the proposal!). On 2-3 pages, the proposal should cover the following elements:

After the proposal has been accepted by your supervisor, your master thesis will be registered immediately.

Brief description of the area

Investor sentiment is an important element of Behavioral Finance. Hence, there are numerous studies to analyze the impact of investor sentiment on stock markets. In addition to sentiment measures, recent studies particularly focus on the effects of sentiment on individual and aggregated stock returns. However, both are not conclusively clarified areas of research.

Possible topics (among others) are

• Measuring investor sentiment: alternatives to the Baket and Wurgler (2006) sentiment Index
• Investor sentiment and stock returns
• Investor sentiment and the risk-return trade-off
• Effects of investor sentiment on capital market anomalies

Basic literature

• De Long, B.J., Shleifer, A., Summers, L.H., and Waldman, R.J. (1990): Noise Trader Risk in Financial Markets. Journal of Political Economy,  98(4), 703–738.
• Baker, M. and Wurgler, J. (2006): Investor sentiment and the cross-section of stock returns. The Journal of Finance, 61(1), 1645–1680.
• Kozak, S., Nagel, S., and Shrihari, S. (2018): Interpreting Factor Models. The Journal of Finance, 73(3), 1183–1223.
• Yu, J. and Yuan, Y. (2011): Investor sentiment and the mean–variance relation. Journal of Financial Economics, 100(2), 367–381.
• Stambaugh, R.F., Yu, J., and Yuan, Y. (2012): The short of it: Investor sentiment and anomalies. Journal of Financial Economics, Special Issue on Investor Sentiment, 104(2), 288–302.

Preferences are a behavioral approach to explain the observed deviations of individual investors' behavior from the predictions of neoclassical theory. As of now, the most important theories for decision making under risk are the (Cumulative) Prospect Theory and the Salience theory.

• Portfolio insurance strategies under Cumulative Prospect Theory and Salience Theory
• The salience effect on the stock market
• Expected returns under Cumulative Prospect Theory
• Skewness preferences and security prices
• Bordalo, P., Gennaioli, N., and Shleifer, A. (2012): Salience theory of choice under risk. The Quarterly Journal of Economics, 127(3), 1243-1285.
• Tversky, A. and Kahneman, D. (1992): Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty, 5(4), 297-323.
• Dichtl, H. and Dobritz, W. (2011): Portfolio insurance and prospect theory investors: Popularity and optimal design of capital protected financial products. Journal of Banking & Finance, 35(7), 1683-1697.
• Cosemans, M. and Frehen, R. (2017): Salience Theory and Stock Prices: Empirical Evidence. Working Paper.
• Barberis, N. and Huang, M. (2008): Stocks as Lotteries: The Implications of Probability Weighting for Security Prices. American Economic Review, 95(5), 2066-2100.
• Barberis, N., Mukherjee, A., and Wang, B. (2016): Prospect Theory and Stock Returns: An Empirical Test. Review of Financial Studies, 29(11), 3068-3107.

Kurzbeschreibung des Themenbereichs

Sustainability is progressively gaining prominence in investment considerations. Beyond purely financial factors, the inquiry emerges as to the impact of the environmental, social, and governance (ESG) dimensions on both corporations and investors, and how a company's ESG performance influences its returns.

Themenbeispiele

• Construction and analysis of an ESG pricing factor
• Estimation of the ex-ante Greenium by Implied Cost of Capital
• Measurement of "Climate Change" and Analysis of the Risk Premium of Climate Change Betas or Climate Change Risks
• Analysis of the Impact of Weather and Pollution on Stock Returns

Basisliteratur

• Pástor, Ľ., Stambaugh, R., and Taylor, L.A. (2021): Sustainable investing in equilibrium.  Journal of Financial Economics,  142(2), 550-571.
• Pástor, Ľ., Stambaugh, R. F., and Taylor, L. A. (2022): Dissecting green returns.  Journal of Financial Economics, 146(2), 403-424.
• Ardia, D., Bluteau, K., Boudt, K., and Inghelbrecht, K. (2023): Climate change concerns and the performance of green vs. brown stocks. Management Science . 
• Sautner, Z., Van Lent, L., Vilkov, G. and Zhang, R. (2023): Firm-Level Climate Change Exposure. The Journal of Finance, 78(3), 1449-1498.
• Sautner, Z., Van Lent, L., Vilkov, G. and Zhang, R. (2023): Pricing Climate Change Exposure. Management Science.
• Loughran, T. and Schultz, P. (2004): Weather, Stock Returns, and the Impact of Localized Trading Behavior. Journal of Financial and Quantitative Analysis,   39(2), 343-364.
• Ding, X., Guo, M., and Yang, T. (2021): Air pollution, local bias, and stock returns. Finance Research Letters, 39, 1-6.
• Hirshleifer, D. and Shumway, T. (2003): Good Day Sunshine: Stock Returns and the Weather. The Journal of Finance, 58(3), 1009-1032.

The literature provides numerous empirical studies that contradict the predictions of neoclassical theory. In addition to proving the existence and robustness of anomalies across markets and market regimes, examining different approaches to explain the anomalies are of particular interest and can be investigated in the context of your master thesis.

• Out-of-sample tests of selected anomalies (e.g. momentum, idiosyncratic volatility, betting-against-beta, max effect)
• Anomalies and multi-factor models
• Interaction of anomalies (e.g. skewness and momentum)
• Risk management strategies and anomalies
• Ang, A., Hodrick, R.J., Xing, Y., and Zhang, X. (2006): The cross‐section of volatility and expected returns. Journal of Finance, 61(1), 259-299.
• Jegadeesh, N. and Titman, S. (1993): Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance,  48(1), 65–91.
• Frazzini, A. and Pedersen, L.H. (2014): Betting against beta. Journal of Financial Economics, 111(1), 1–25.
• Bali, T.G., Cakici, N., and Whitelaw, R.F. (2011): Maxing out: Stocks as lotteries and the cross-section of expected returns. Journal of Financial Economics, 99(2), 427-446.
• Hou, K., Mo, H., Xue C., and Zhang, L. (2019): Which Factors?. Review of Finance, 23(1), 1-35.
• Barroso, P., Detzel, A.L., and Maio, P.F (2020): Managing the Risk of the Low-Risk anomaly. Working Paper.
• Kelly, B. T., Pruitt, S., and Su, Y. (2019). Characteristics are covariances: A unified model of risk and return.  Journal of Financial Economics , 134(3): 501–524.

Although machine learning algorithms are becoming increasingly important, they have rarely been used in empirical capital market research. Thus, the comparison of new and established methods provides numerous research questions.

• Empirical asset pricing and machine learning
• Multi factor models and artificial neural networks
• Hastie, T., Tibshirani, R., and Friedman, J. (2017): The Elements of Statistical Learning 2nd Edition. Springer Verlag.
• Gu, S., Kelly, B., and Xiu, D. (2020): Empirical asset pricing via machine learning. The Review of Financial Studies, 33(5), 2223-2273.
• Gu, S., Kelly, B., and Xiu, D. (2021): Autoencoder asset pricing models.  Journal of Econometrics, 222(1): 429–450.
• Gareth, J., Witten, D., Hastie, T., and Tibshirani, R. (2017): An Introductoin to Statistical Learning: With Applicatoins in R. Springer Verlag, New York.
• Hou, K. and Lee, J. (2018): Nonlinear CAPM Beta. Working Paper.
• Dimson, E. (1979): Risk measurement when shares are subject to infrequent trading. Journal of Financial Economics, 7(2), 167-226.

Market prices of derivatives and, in particular, options provide rich information about market participants' expectations about the future. The elicitation of these expectations is possible via well-known option pricing models, such as Black & Scholes (1973), or numerous model-free approaches.

• Estimation of risk-neutral moments from option prices
• Option-implied risk preferences
• Market indicators of volatility and skewness: VIX and SKEW
• Risk premia for variance and skewness
• Option pricing and estimation of the volatility surface using neural networks
• Bakshi, G., Kapadia, N., and Madan, D. (2003): Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options. Review of Financial Studies, 16(1), 101–143.
• Breeden, D.T. and Litzenberger, R.H. (1978): Prices of State-contingent Claims Implicit in Option Prices. Journal of Business, 51(4), 621-651.
• Jackwert, J. (2000): Recovering Risk Aversion from Option Prices and Realized Returns. The Review of Financial Studies, 13(2), 433-451.
• Liu, Z. and Faff, R. (2017): Hitting SKEW for SIX. Economic Modelling, (64), 449-464.
• Bollerslev, T., Tauchen, G., and Zhou, H. (2009): Expected Stock Returns and Variance Risk Premia. The Review of Financial Studies, 22(11), 4463-4492.
• Carr, P. and Wu, L. (2009): Variance risk premiums. Review of Financial Studies, 22(3), 1311-1341.

Portfolio selection is one of the classic areas of research in finance. Results not only depend on investor preferences, but also on the data generating process and the investment horizon. While neoclassical models explore the optimal portfolio choice, it is equally important to apply behavioral analyses in order to understand why many people do not engange in the stock market and how investors make portfolio choices.

• The optimal portfolio choice under ambiguity
• The optimal portfolio choice with a long investment horizon and predictability
• The influence of estimation risk on the optimal portfolio selection
• Portfolio selection under behavioral decision theories
• Participation in the stock market

Basisc literature

• Garlappi, L., Uppal, R., and Wang, T. (2007): Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach.  The Review of Financial Studies, 20(1), 41-81.

DeMiguel, V., Garlappi, L., and Uppal, R. (2009): Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy?.  The Review of Financial Studies, 22(5), 1915–1953.

• Barberis, N. (2000): Investing for the Long Run when Returns Are Predictable.  The Journal of Finance, 55, 225-264.

Chapman, D.A. and Polkovnichenko, V. (2009): First‐Order Risk Aversion, Heterogeneity, and Asset Market Outcomes.  The Journal of Finance, 64, 1863-1887.

• Grinblatt, M., Keloharju, M., and Linnainmaa, J. (2011): IQ and stock market participation.  The Journal of Finance, 66 (6), 2121-2164.
• Kaustia, M. and Torstila, S. (2011): Stock market aversion? Political preferences and stock market participation.  Journal of Financial Economics, 100(1), 98-112.
• Van Rooij, M., Lusardi, A., and Alessie, R. (2011): Financial literacy and stock market participation.  Journal of Financial Economics, 101(2), 449-472.
• Brooks, C. (2019): Introductory Econometrics for Finance. Fourth edition. Cambridge, United Kingdom ; New York, NY, Cambridge University Press.
• Malmendier, U. and Nagel, S. (2011): Depression Babies: Do Macroeconomic Experiences Affect Risk Taking?.  The Quarterly Journal of Economics, 126(1), 373–416.

Although Modigliani and Miller (1958) document that - when assuming a perfect market - capital structure is irrelevant, there are numerous studies to show that this result does not hold empirically. More recent studies, such as Baker and Wurgler (2002), show that financing decisions (and thus capital structure), in particular, depend on market timing.

• Empirical validation of theories on IPO underpricing
• Long-term performance of IPOs
• Market timing of financing decisions
• Forecast of earnings and implied cost of capital

Ritter, J. R. (1991): The long‐run performance of initial public offerings.  The Journal of Finance,   46 (1), 3-27.

• Loughran, T. and Ritter, J. R. (2002): Why don’t issuers get upset about leaving money on the table in IPOs?. The Review of Financial Studies,  15(2), 413-444.
• Ritter, J. R. and Welch, I. (2002): A review of IPO activity, pricing, and allocations.  The Journal of Finance,  57(4), 1795-1828.
• Green, T. C. and Hwang, B. H. (2012): Initial public offerings as lotteries: Skewness preference and first-day returns.  Management Science , 58(2), 432-444.
• Laeven, L. and Levine, R. (2007): Is there a diversification discount in financial conglomerates?. Journal of Financial Economics,  85(2), 331-367.
• Baker, M. and Wurgler, J. (2002): Market timing and capital structure.  The Journal of Finance,  57(1), 1-32.
• Hou, K., Van Dijk, M. A., and Zhang, Y. (2012): The implied cost of capital: A new approach.  Journal of Accounting and Economics,  53(3), 504–526.

On the following pages you will find more information about the scientific work at the Institute for Banking and Finance. Please note the formal information and the dates for the introduction to scientific work.

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Master Theses

Master theses winter semester 2023/2024.

Dates for writing a master thesis at our professorship in winter semester 2023/2024:

• Announcement of the list of topics: Mon., 9 October 2023
• Deadline for naming your  topic preferences  or  submitting the exposé: Sun. , 15 October 2023
• Kick-off event:    Wed., 18 October 2023, 09:00 (s.t.) (via BBB)
• 1st colloquium:  Wed., 22 November 2023 , 09:00 (s.t.) (via BBB)
• 2nd colloquium:  Wed., 20 December 2023 , 09:00 (s.t.) (via BBB)
• 3rd colloquium:   Wed., 7 February 2024 , 09:00 (s.t.) (via BBB)
• Submission: Mon., 9 April 2024 (4-semester Master), Thu., 15 February 2024 (2-semester Master)

Participation in the kick-off event is mandatory, whereas participation in the colloquia is optional, but strongly recommended.

Since the summer semester 2017, Master theses can also be written in German at the Professor BWL VI. However, in view of the English language literature, we recommend writing the Master thesis in English.

We would be pleased to receive your own topic suggestions from your side. You are welcome to be inspired by the titles listed below or to choose them as your topic (you are welcome to make changes to the titles).

Master Theses summer semester 2024

Dates for writing a master thesis at our professorship in summer semester 2024:

• Announcement of the list of topics: Tue., 9 April 2024
• Deadline for naming your  topic preferences  or  submitting the exposé: Sun. , 14 April 2024
• Kick-off event:    Wed., 17 April 2024 , 09:00 (s.t.) (via BBB)
• 1st colloquium:  Wed., 15 May 2024 , 09:00 (s.t.) (via BBB)
• 2nd colloquium:  Wed., 19 June 2024 , 09:00 (s.t.) (via BBB)
• 3rd colloquium:   Wed., 7 August 2024 , 09:00 (s.t.) (via BBB)
• Submission: Mon., 14 October 2024 (4-semester Master), Thu., 15 August 2024 (2-semester Master)

Possible theses topics:

• CSR and corporate value creation 
• Sustainability factors in remuneration policies of DAX and MDAX companies
• Say on Climate: shareholder activism in the area of sustainability 
• ESG Ratings: chances and limitations 
• The financial performance of green bonds 
• The effects of non-financial disclosures on financial performance
• Compliance of the Declarations of Conformity of DAX companies with the German Corporate Governance Kodex (Übereinstimmung mit dem Deutschen Corporate Governance Kodex anhand der Entsprechenserklärung) 
• Cultural differences in the CEOs' letters to shareholders and their stock price effects
• Cultural effects on corporate financial decisions
• Gender differences in financial risk-taking

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MASTER'S THESIS Factors Influencing the Adoption of Internet Banking

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With the advancement of technology, Internet Banking has paved a way for a new era which is far more ahead of the traditional practices of banking. Earlier the customers had to spend their time and energy to visit the banks. But with the introduction of this new innovated system, the difficulties faced by the customers have been reduced to a greater extent. But still in Sri Lanka, thecustomers are lagging behind the traditional customs rather than shifting to new technologies. Thereby the number of customers who use internet banking is still at the primary stage with a lesser number. Therefore, the purpose of this study is to investigate the factors that affect customers’ intention to adopt internet banking in Sri Lanka. the research. Five point likert scale was used to test the constructs of the variables. In determining customers’ intention towards internet banking, the study analyzed 200 customer opinions using questionnaires. Binary Logistic Regression was applied to test the effect of Attitude, Perceived Behavioral Control (PBC), Perceived usefulness (PU), Perceived Ease Of Use (PEOU) and Perceived Risk (PR) on intention to adopt internet banking. The data was employed into SPSS version 21 and carried out the data analysis. The results showed that intention is significantly influenced by Attitude, PBC and PR relative to other factors considered.Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) were used in as the framework of

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Internet banking is the latest technology that has revolutionized the changes of banking and business systems around the world. However, arrival of technology has an impact on Internet banking and transforms from a traditional banking system to a very useful innovation technology. The purpose of this study is to analyze factors that have influenced users to use Internet banking in doing financial transaction. This study uses content analysis on the previous literatures. The findings showed that there were 10 main different factors which influence the adoption of internet banking by the users. This study also proved that the highest factors which consist of 2 main factors are generated from technology acceptance model (TAM). Contribution of this research are significantly helps bank to have a better understanding on factors that influence the adoption of internet banking as well as help to develop a strategy to improved internet banking services.

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There continues to be a gap in understanding ofwhat makes an individual reject using Internet banking service. This is the primary research question of this study. So far, very few academic studies have been done on internet banking adoption in Arab countries. Hence, this research aims to investigate factors that influence the behavioral intention to use Internet banking in Yemen. Cross-sectional data were collected from1286 respondents through a survey. Data were then analyzedby structural equation modeling. The findingsverified the research hypotheses and confirmed that perceived ease of use and perceivedusefulness, compatibility and trialabilityall impact attitude toward intentionof adopting Internet banking.

Recently information technology is one of the vital elements in human daily activity supports. One example of information technology measurement is based on the Technology Acceptance Model (TAM), which is an information system that shows how users come to accept and use the technology. Usefulness and Ease of Use are the main reasons that would predispose a person to use such technology. The TAM is also applied to the use of Internet Banking, but there are some more factors that will affect the Behavior Intention in using the Internet Banking including Risk and Trust. The aim of this study is to prove the hypothesis of the variables that affect the Behavior Intention. Research variables were measured using a questionnaire that is processed with SPSS software. The results showed that the four variables studied positive influence on Behavior Intention in the use of Internet Banking. Keywords: Internet banking; Usefulness; Ease of use; Risk; Trust; Behavior intention.

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The number of Bachelor's and Master's Theses supervised at the Institute for Finance & Banking (IFB) is due to capacity.

Skip to content

Information for mathematics students, application deadlines, formal requirements, theses archive.

Mathematics and Business Mathematics students can apply any time to be supervised in writing their Bachelor or Master Thesis by IFB via mail to IFB-Theses . Please enclose your CV and latest transcript of records.

Prerequisites

• Successful participation in an advanced seminar qualifies for the acceptance of a Bachelor thesis (6 ECTS).
• Students who have taken an advanced seminar in the field of finance (chairs of Elsas/Glaser/Richter/Riordan) will be accepted preferentially.
• The requirements of the respective examination regulations apply.

Application

• a letter of motivation in which you briefly, but as precisely as possible, outline your areas of interest. Please refrain from general statements as "I don't know any special field of interest". You can orientate yourself on the contents of your studies (lectures or advanced seminar) or be inspired by the theses already completed .
• an exposé with a short outline (a few sentences) of your own proposed topic. Therein, address the question(s) to be investigated, the methods (data) and the relevant literature. This also applies to theses written in cooperation with a company.
• Please send your complete application by email to the IFB: Theses .
• We will inform you regarding acceptance or rejection of your application no later than 2 weeks after receipt of your application. In case of acceptance we will assign you a topic and a supervisor.
• The thesis at the IFB can generally be started any time though the registration of theses usually starts at the beginning of the month. Please note the application deadlines .
• The deadline is determined by the corresponding completion time (8 weeks for Bachelor's theses and 22 weeks for Master's theses).
• Before the thesis is registered at the ISC, each student prepares an exposé (max. 2 pages). This is generally done after agreement on a topic. The exposé must be handed in to the respective supervisor at the latest one week after agreement on the topic. In consultation with the supervisor the draft is then revised and extended if necessary.
• Upon agreement on the final topic, the thesis is registered at the examination office.
• Theses can be written in English or German (English is preferred).
• Please follow our formal requirements - if you have any questions, please consult your supervisor.
• A thesis colloquium is held on the first Wednesday of each month. The colloquium takes place after about half of the processing time. Students present the status of their work for a maximum of 30 minutes, the presentation is held in English or German. During the colloquium, structure of the work and methodological approach are explained in particular. The subsequent discussion helps to identify problems in dealing with the topic and possible alternative solutions. The colloquium is rounded off by a short insight into the current state of work and possible open questions. Aim of the colloquium is to give constructive feedback - it is attended by the scientific staff and head of the institute.
• Thesis submission is effected according to the ISC guidelines. Please inform your supervisor about the planned submission date.
• For theses with a programming component, the student is required to submit data and codes to generate the results. The student is also responsible for ensuring that results can be replicated and reproduced by the supervisor.
• Your supervisor will inform you as soon as the thesis has been evaluated.

Compliance with these guidelines (PDF, 136 KB) is generally mandatory and is intended to provide you with the necessary guidance to write a formally correct paper.

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• Can Twitter help predict firm-level earnings and stock returns, Master Thesis
• On the pricing of European Dual Class Stocks, Master Thesis
• The effect of corporate hybrid bonds issuance announcements on stock prices, Master Thesis
• Performance of S&P 500 Index Additions, Bachelor Thesis
• Hedge funds and their performance during the COVID-19 pandemic, Bachelor Thesis
• Cryptocurrency price prediction using an LSTM and an ARMA model, Master Thesis
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• The Effect of European Short Position Disclosure Requirement on Market Efficiency, Master Thesis
• Earnings Forecasts by Analysts - Accuracy and Timing, Master Thesis
• Text mining of corporate disclosures for stock index forecasting, Master Thesis
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• Examining Deterministic Volatility Functions on Short-Term Options, Master Thesis
• Deep Learning and Option Pricing, Bachelor Thesis
• An empirical analysis of financial advisors and M&A returns, Master Thesis
• International Diversification and Market Capitalization, Bachelor Thesis
• Identifying Financial Distress in Company Filings, Master Thesis
• Investigating Capital Market Reactions to Corporate Events Using Machine Learning, Master Thesis
• An Analysis of the Relationship between Short Interest and Stock Performance, Bachelor Thesis
• Predicting Hourly Price Movements Of Bitcoin Based On Reddit Sentiment And Price Information Using Machine Learning Algorithms, Bachelor Thesis
• An Empirical Analysis of Corporate Social Responsibility and Access to Finance, Bachelor Thesis
• The Impact of Activist Short Sellers on the Returns of Target Companies, Bachelor Thesis
• Analysis of the influence of Covid-19 on the Ad Hoc Publicity, Master Thesis
• Was the retail investement portion significant in the initialization of the short squeeze of GameStop?, Bachelor Thesis
• Estimating market betas for Germany, Master Thesis
• Text analysis of Reddit WallStreetBets posts, Bachelor Thesis
• An empirical analysis of options and implied volatility, Bachelor Thesis
• The Impact of M&A Announcements on Short Interest in the German Market - An Event Analysis Approach, Bachelor Thesis
• Anomaly Detection in Finance, Master Thesis
• A Machine Learning Approach to Risk Factors Applying the Fama-French-Carhart Model: A Case Study on the German Stock Market, Master Thesis
• The Heston-Nandi GARCH option valuation model for the DAX30 index options market, Master Thesis
• The Effect of Rumors on the Stock Price of potential Target Companies, Bachelor Thesis
• Analyse von Investorenreaktionen auf themenübergreifende Finanzpublikationen mittels Anwendung der latenten Dirichlet-Allokation, Master Thesis
• News-based Volatility Forecasting using Machine Learning, Master Thesis
• Static- and Delta Hedging of Options, Master Thesis
• Topics in Ad-Hoc-News, Bachelor Thesis
• An Empirical Analysis of OTC Stocks, Master Thesis
• Employee satisfaction and equity returnsunder alternative statistical tests, Master Thesis
• Idiosyncratic Risk Innovations and the Idiosyncratic Risk-Return Relation in the German Equity Market, Master Thesis
• Financial and Legal Advisors and the Performance of M&A Transactions, Bachelor Thesis
• Media Coverage of German Listed Companies, Bachelor Thesis
• The effects of regulatory uncertainty on merger and acqusition activity, Bachelor Thesis
• The Effect of Finntech M&A on Acquirer Stock Performance in the Financial Sector, Bachelor Thesis
• Bank Risk Dynamics and Distance to Default, a Simulation based Analysis, Bachelor Thesis
• Pricing VSTOXX Futures, Master Thesis
• An empirical analysis of temperature shocks and the cost of equity capital, Bachelor Thesis
• The Usage of Factor Models to Explain Cross-Sectional Stock Returns, Bachelor Thesis
• An empirical analysis of the effects of corporate takeovers on the abnormal return to acquirer competitors, Bachelor Thesis
• The release of the subsidiaries into independence: The choice between Sin-offs and Carve-outs, Bachelor Thesis
• Value Drivers and Deal Characteristics in Private Equity Transaction Versus Strategic Acquisitions, Master Thesis
• The Influence of Ad-hoc Disclosures on Stock Returns, Master Thesis
• Isolating the disaster risk premium with equity options in the German market, Bachelor Thesis
• Insider-forecasted operating synergies' impact on M&A performance, Bachelor Thesis
• An Empirical Analysis of Callable Contingent Convertibles, Master Thesis
• Static Replication of Window Double Barrier Options, Bachelor Thesis
• The informativeness of textual tone in M&A conference calls and its effect on stock returns, Master Thesis
• Comparison of Earnings Surprise Measures, Master Thesis
• Intangible Assets and Mergers and Acquisitions, Master Thesis
• The Effects of Expected Volatility on Stock Returns in European Equity Markets, Master Thesis
• The Success of Acquiring vs. Developing Innovation in Research Intensive Industries, Master Thesis
• Robustness of the Distance-to-Default Measure - A Simulation-based Analysis, Bachelor Thesis
• Corporate default risk: predictive power of rule-based classifier models compared to traditional bankruptcy prediction models, Bachelor Thesis
• Analyzing the bid-ask quotes for a FX broker in responds to volatility, Master Thesis
• What are the Most Important Topics for Buy- and Sell-side Analysts? An Investigation of M&A Conference Calls Using Textual Analysis, Bachelor Thesis
• Relationship between Exchange Rate Risk and Stock Prices, Bachelor Thesis
• Hedging Performance of Volatility Products under Different Stochastic Volatility Models, Master Thesis
• Empirical stylized facts of the intra-daily foreign exchange markets, Bachelor Thesis
• Similarity between Firms in Domestic vs. Cross-border M&A Activities: A Text-based Approach, Master Thesis
• Impact of Migration on Cross-border Merger & Acqusition Activities, Master Thesis
• Stock Returns and the Impact of Anaylst Recommendations, Bachelor Thesis
• Portfolio Optimization with Simulation and Backtesting of the Value-at-Risk measure, Bachelor Thesis
• How Does Language in Corporate Public Disclosures Reflect Actual Firm Performance and Influence Stock Market Reactions?, Master Thesis
• Investor Attention and the Cross-section of Stock Return, Master Thesis
• Can Ex-Ante Observable Signals for Investor Sentiment or Company Quality Predict the Long-Term Performance of Initial Public Offerings?
• An Empirical Study of the US Market for New Equity Issues, Master Thesis
• Sentimental Distress: The Analysis of the Tone of 8-K Reports in a Financial Distress Context, Master Thesis
• Expected Option Returns for DAX 30 Options, Bachelor Thesis
• Delta-Hedged Gains and the Market Volatility Risk Premium: Evidence from the German Market, Master Thesis
• The Announcement Effect of Mergers & Acquisitions on Markets and Model-Implied Credit Default Swaps, Master Thesis
• Selecting Characteristics for Parametric Portfolio Selection, Master Thesis
• Relationships Between Implied Volatility Indexes and Stock Index Returns, Bachelor Thesis
• The Information Content of Implied Volatility based on DAX 30 Options, Bachelor Thesis
• Merger and Acquisition Announcement Returns and Synergy Expectations, Master Thesis
• Does competition between investment banks matter for their clients' M&A performance?, Master Thesis
• Monte Carlo Methods for Pricing Asian Options, Bachelor Thesis
• Deterministic Implied Volatility Functions: Empirical Tests for Dax Index Options, Bachelor Thesis
• Modeling Term Structure Using Macroeconomics Factors, Master Thesis
• Estimating the Link Between Default Risk and Stock Returns Using the Implied Cost of Capital, Master Thesis
• Problems of Inference in Single-Firm Event Studies, Bachelor Thesis
• Competition: Theoretical Concepts, Measurement Methods and their Application in the Banking Sector, Bachelor Thesis
• Factor-Model-Based Priors for the Black-Litterman Model
• Portfolio Optimization under a VAR Model of Return, Bachelor Thesis
• An empirical investigation of valuation premia in IPOs versus acquisitions, Bachelor Thesis
• Entry in the Banking Industry: An Empirical Analysis of the Effect of Mergers and Acquisitions, Bachelor Thesis
• Banking competition, venture capitalists and their influence on entrepreneurial activity, Master Thesis
• The effect of institutional ownership on antitakeover defense and the success of hostile takeover bids, Bachelor Thesis
• M&A Transactions and the Role of Related CEO Characteristics, Bachelor Thesis
• Determinants of recovery rates implied by CDS spreads, Master Thesis
• The influence of the source of capital on corporate financing and investment behavior during the financial crisis 2007-2009, Master Thesis
• Der Einfluss von Wettbewerb und Innovationsgrad von Industrien auf die Höhe von Fusionsprämien, Bachelor Thesis
• About the Role of Credit Default Swaps in the Emergence of the 2008 Financial Crisis, Bachelor Thesis
• Assessing Credit Risk Using Option-Implied Information, Master Thesis
• Pricing of Callable Bonds, Bachelor Thesis
• Can Michaud resampling techniques improve mean-variance portfolio optimization?, Bachelor Thesis
• Porfolio Optimization and Ambiguity Aversion, Master Thesis
• Portfolio Optimization Using Implied Covariance Matrix Estimates, Bachelor Thesis
• Institutional cross-holdings and their effect on acquisiton decisions, Bachelor Thesis
• The Limits of Arbitrage: A Literature Review, Bachelor Thesis
• The Role of Correlation Between Market and Credit Risk for Certificate Pricing, Bachelor Thesis
• The Role of Credit Default Swaps in the Emergence of the 2008 Financial Crisis, Bachelor Thesis
• Peer influence on corporate financial policy: An application to cash flow sensitivities, Master Thesis
• Implications of recent changes in banks' market risk framework: empirical examination of different methods for calculation of Value-at-Risk and Expected Shortfall, Master Thesis
• The relationship between Corporate Governance and Credit Risk - A Literature Review, Bachelor Thesis,
• Optimal Delta Hedging: Evidence from DAX Index Options, Bachelor Thesis
• A literature review on institutional investors and competition, Bachelor Thesis
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