master thesis in banking

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Master of Science in Finance and Banking

Thesis titles.

MSc in Finance and Banking Theses Titles, by Academic Year

Luigi Barbieri, Comparative Performance Analysis of Sustainable and Conventional Funds, Advisor: Prof. Rocco Ciciretti

Riccardo Battistelli, Drawdown Analysis, Advisor: Prof. Tommaso Proietti

Riccardo Cammarata, Bitcoin Impact on the World's Economic Landscape, Advisor: Prof. Nicoletta Ciocca

Aleksander Campus, Credit Losses in Peer-to-Peer Lending: A quantile Regression Approach, Advisor: Prof. Alessio Farcomeni

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

Andrea Di Guida, Covariance Matrix Estimatio: A Comparative Analysis, Advisor: Prof. Tommaso Proietti

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

Andrea Lupascu, Assessing the Effects of ESG Scores on M&A Transactions: An Event Study Approach, Advisor: Prof. Rocco Ciciretti

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

Leonardo Marsano, Bond Portfolio Strategies: A Comparative Analysis of iShares iBonds, Traditional Bond ETFs and Individual Bonds Using the Black-Litterman Model, Advisor: Prof. Ugo Pomante

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

Davide Ruggeri , Does Corporate Social Responsibility Influence the Mean of Payment in M&A? Empirical Evidence from Asia Pacific, Advisor: Prof. Stefano Caiazza

Alexander Toernqvist , Generative Adversarial Networks: A Novel Approach to Predictive Modelling in Finance, Advisor: Prof. Alessandro Ramponi

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

Open Access Theses and Dissertations

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• Corpus ID: 214621877

Master Thesis in Banking and Finance

• Christos Iossifidis
• Published 2010
• Business, Economics

Figures and Tables from this paper

98 References

Financial sector policy and the poor: selected findings and issues.

• Highly Influential

Microfinance Investment Funds: Objectives, Players, Potential

• 11 Excerpts

Cautious Resilience: The Impact of the Global Financial Crisis on Latin American and Caribbean Microfinance Institutions

State of the microcredit summit campaign report 2011, latin america and the caribbean: u.s. policy and key issues for congress in 2012, on mission drift in microfinance institutions, microfinance mission drift, growth and vulnerabilities in microfinance, development economics through the decades: a critical look at 30 years of the world development report, related papers.

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MSc Bankfin: Master’s Thesis

At the beginning of the 3 rd or 4 th semester (depending on whether the student is full or part time) a thesis must be written.

The goal of the thesis is the students to explore critically, through explicit empirical analysis, various topics in banking and finance.

Students have two options: a) to propose a topic related to their current employment or related to the students’ research interest or b) to choose one of the topics suggested by the teaching staff.

Following the submission of an application from the students in which they provide the title of the thesis and the name of the supervisor, the Coordination Assembly submits a recommendation to the general Assembly of the department about the assignment of the thesis to the recommended supervisor, while at the same time establishes a 3-member committee which plans to evaluate the merit of the thesis (a member of this committee must be the supervisor).

The supervisor must be a member of the department’s staff, while the remaining two members of the committee could be either members of the staff or members of the staff coming from other departments or universities and are related to the graduate program.

The thesis could be written either in Greek or in English.

The thesis is submitted at the end of the 3 rd or 4 th semester, while it is approved by the supervisor and then the students can defend it in public to the student’s committee.

A thesis is considered successful (based on the 1-10 grading scale) if it receives at least five (5). If the quality of the thesis does not receive a passing grade, then the committee is asking the student to improve it or to modify certain parts or to radically change its whole picture; in that case, the student received a 6-month extension and then to resubmit it after taking explicitly into account all the recommended changes.

It is mandatory for all theses to get published onto the digital platform of “DIONE”, following the guidelines set by the Senate of the University of Piraeus.

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Dissertation Topic in Finance

• Updated on  
• Jan 11, 2024

Also known as the study of investments, Finance is a combination of two interrelated subjects – how money is handled and the process of obtaining money. One of the reasons why postgraduate students struggle with their Finance dissertation topics is that they do not spend enough time planning it. It is important for students to be extremely careful while writing a finance dissertation as it contributes a lot to their respective degrees. This blog provides you with the best topics, a dissertation structure, and more. 

This Blog Includes:

What is a finance dissertation, why finance dissertation topics are important, tips to find excellent dissertation topics on finance, writing tips for finance dissertation, how to plan your work on a finance dissertation, how to structure a finance dissertation, finance dissertation general topics , topics related to india, mba dissertation topics, banking dissertation topics , accounting dissertation topics, research project example, final consideration and conclusion.

Finance dissertations, as the name implies, are pieces of writing that study a certain finance topic chosen by the student. The subjects covered include anything from the stock market to banking and risk management to healthcare finance. This dissertation gives the student academic self-assurance and personal happiness in the subject of finance. Finance writing necessitates substantial research in order to produce a compelling report.

The majority of students have no idea why finance dissertation themes are so crucial. However, put yourself in the shoes of your lecturer. You’ve already read hundreds of theses. The majority of them covered the same ground — issues that you’re already tired of hearing about. Then there’s a topic with a distinct, intriguing theme. Something that piques your interest and entices you to read more. Wouldn’t you give those pupils some extra credit? You’d do it! This is why there are so many fantastic finance dissertation topics. You can get extra points for your efforts. The topic of your paper might mean the difference between a good and a terrific grade.

It’s difficult to come up with anything unique and interesting. There are, nevertheless, ways to come up with interesting ideas. Here are a few pointers on how to locate them:

• Read a fantastic finance dissertation and find for areas where further study is needed.
• Go to the library and read a couple theses to get some ideas.
• Inquire with a writing agency about some ideas from one of their professional dissertation writers.
• In writing forums and blogs, ask for assistance. If you ask gently, people will give you some excellent suggestions.
• Look for ideas on the internet, but don’t use them exactly as they are. Make them distinctive by changing them.
• Talk to other students who are working on their dissertations and find out what other ideas they had before settling on the present topic.
• Narrow down your topic : Your financial topic should be narrowed down to a certain niche. It should concentrate on a single area, such as microfinance, microfinance, or online banking.
• Verify your facts: Finance is a topic that requires a great deal of logical analysis of statistical data. As a result, double-check facts and statistics using credible sources before using them in your paper.
• Write concisely: You should condense a financial paper into a tight, succinct work, unlike other papers with extended narrative narratives. At this length, the adage of ‘short is sweet’ theoretically applies.
• Arrange your data neatly: A report that is crammed with numbers and graphs may turn off a reader at first glance. Know how and when to utilise your data for a great financial thesis.
• Write simply: Avoid using jargon that might be confusing to a non-technical reader. When technical terminology are required, utilise accessible examples to convey them. In a finance dissertation, simplicity is king. So make good use of it.

Dissertation submission is very important to obtain a PG Degree. You are supposed to submit the work by the end of your study course, so by the last year of your degree, you may have got enough ideas and problems dealing with finance. While starting with a finance dissertation topic you should always remember that the purpose of a Finance Dissertation is to demonstrate your research ability, how you analyze specific data and come up with a conclusion. Mentioned below is a step to step guide for you to start working with:

Step 1 : Choose a relevant and interesting topic for your research

Step 2 : Discuss and receive feedback from your supervisor

Step 3 : Finalise the research methods to prove the significance of the selected topic

Step 4 : Gather the required data from relevant sources

Step 5 : Conduct the research and analyse the acquired results

Step 6 : Work on the outline of your dissertation

Step 7 : Make a draft and proofread it. Discuss with your advisors if any changes are to be made

Step 8 : Make the required corrections. 

Step 9 : Draft the final dissertation

Also Read: Check out the Top Course in Finance

There are so many different ways you can structure your dissertation. But the most common and universally accepted way is as follows:

• Introduction
• Literature review
• Methodology
• Analysis of the data and Significance/Implications of the acquired results

Also Read: Executive MBA in Finance

Finance Dissertation Topics

Finance is an extensive field, you can explore a lot of areas related to finance to choose a dissertation topic. Here we’ve mentioned the best finance dissertation topics to make it easier for you:

Mentioned below are some of the topics related to the recent issues in the world:

• The negative impact of microfinance in developing countries.
• The effects of population growth on economic growth in China
• Cryptocurrency: Are we ready to digitalise the monetary world?
• Analyzing the financial statements of VISA and MasterCard
• Why do banks oppose digital currency?
• Risks and benefits associated with digital money transferring technology

Also Read: Top MBA course to pursue

• Investing in India’s technology sector – obstacles and opportunities
• Foreign investment and its effects on economic growth in India
• The effect of corporation investments in the economic development of the community
• Comparing financial development in Asia and Europe
• Did the banks help Small Medium Enterprises to grow in India in the last 5 years?
• The Indian Economic Crisis of 1991

Best MBA Dissertation Topics

Be careful while choosing an MBA Dissertation Topic as it involves more intense study. Make sure the topic you’ve chosen remains within your field of study. We’ve listed some of the best topics you can choose for an MBA Dissertation:

• Management skills an entrepreneur need
• The place of communication for effective management in the workplace
• How technology took over management
• The impact of good leadership in an organization
• How does a strong social media presence affect a company’s marketing strategies?
• Human resource management in non-profit organizations
• The importance of employee motivation programs on productivity
• Management’s socio-cultural background and how it influences leadership relationships
• How do employment benefits impact employee and company’s productivity?
• Business team performance in multinational corporations

Best Finance Universities in the USA

• Study on Future Options in Markets in India
• Gold as an Investable Commodity in India
• Study on Impact Of Corruption On FDI Inflows In India
• The Impact Of The Money Supply On Economic Growth In India
• Capital Structure Of The Business Enterprises In Delhi NCR
• GST And Its Effect on MNC Manufacturing Companies
• Analysis of the Insurance Industry in India
• Analysis of HDFC Bank Finance
• Comparative analysis of HDFC Bank with ICICI bank
• Comparison of Market Share in Public Sector Banks VS Private Sector Banks
• The impact of online banking on the world.
• Risk factors and security issues that are inherent in online banking.
• Fraud and identity theft is accomplished via internet banking.
• Advantages and disadvantages of internet banking for consumers.
• Risk management in investment banking
• The rise of growing banking sectors in developing nations.
• Issues surrounding banking in China’s growing economy.
• The impact of the Federal Reserve on the United States and global economy
• Banking and asset-liability in management.
• The strategies to use online banking technology to attract customers.

All you need to know about  a Banking Course 

• Case study of the impact of industry and public knowledge on the market share index’s fluctuation
• Significance of auditing for large corporations
• Examining India’s country’s tax scheme
• What to consider when investing in financial markets?
• From an accounting perspective, risk-taking in companies and its effects
• Evaluate the differences and similarities between external and internal auditors
• Can taxation be considered a human rights policy? Analyse the problem
• What are the consequences of India’s current tax structure on individuals with a lower income?

Accounting courses

We’ve included a Finance Dissertation Research Example with reference to a Finance Dissertation Structure:

• The Indian Economic Crisis of 1991 – The title of your Finance Dissertation must focus on your research objective.
• Abstract  – The 1991 Indian economic crisis was…………….. imports and other external factors. The abstract part must include a summary of the research problem or objective of the research, the research design and a summary of the results.
• Introduction – The introduction must reflect your research on the Indian Economic Crisis of 1991 in a way that the audience already gets to know what the research is going to include. 

           3.1 Background (background of the study) 

           3.2 Problem Statement (significance of the problem in context)

           3.3 Purpose/Research Questions (What caused the Crisis, how was the crisis revived etc.)

• Review of Literature – The Review of Literature Section must include a theoretical rationale of the problem, the importance of the study, and the significance of the results.
• Methodology – The Methodology Section must include the description of the subjects, research methods used in the data collection and any limitations issues involved.
• Significance/Implications (Results of the Discussion)

*Please note that the above-mentioned structure is only for your reference to get an idea of writing a Finance Dissertation.

Choosing the right topic for your Finance dissertation to plan the work, all the above-mentioned aspects must be given equal importance. This blog has included the best dissertation topic in finance in MBA, accounting, and banking you can choose while writing a dissertation.

Finance research papers and dissertations should be prepared in a way that answers the core question while also being relevant to the remainder of the study. For example, if the dissertation’s major question is “what is the link between foreign exchange rates and the interest rates of a specific country,” the dissertation should provide suitable illustrations to help illustrate the topic. It should also go through the major and minor concerns that are relevant to this topic. Furthermore, utilise proper language to ensure that the article is readily understood by readers. The overall purpose of the project is to produce a well-written, well-researched, and well-supported dissertation.

It takes around 2 years to complete an MBA in India while 1 year to complete a full-time MBA in other countries.

A finance dissertation must be 100-300 pages long.

It takes around 5 years to obtain a Doctorate in Finance.

Hopefully, this blog assisted you in finding out your finance dissertation topics and structure for your course. If you require any assistance regarding your application process while enrolling for your further studies, our experts at Leverage Edu are just one click away. Call us anytime at 1800 572 000 for a free counselling session!

Damanpreet Kaur Vohra

Daman is an author with profound expertise in writing engaging and informative content focused on EdTech and Study Abroad. With a keen understanding of these domains, Daman excels at creating complex concepts into accessible, reader-friendly material. With a proven track record of insightful articles, Daman stands as a reliable source for providing content for EdTech and Study Abroad.

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Master Thesis

Students intending to write a master thesis at the chair of banking and financial services should have acquired the necessary methodological and theoretical knowledge in order to work on a specific subject. Accordingly we require students to have successfully completed exams in one of the following core courses: „Banking & Finance”, „Management of Financial Institutions" or „Banking & Investments“. Furthermore a successful participation in one of the seminars at the Chair for Banking and Financial Services is desirable but not required.

The starting point of your thesis is to study and analyze the relevant literature. You should focus on scientific literature in journals.  As the reader of your work will likely have a university level education in the particular subject, you do not have to summarize and repeat content of lectures and course books. Further a personal contribution to the literature is desirable. A contribution can be made by augmenting a theoretical model or by estimating an econometric analysis.

Your thesis should not exceed 50 pages (+/- 20%). You can choose between Arial with front size 11 or Times New Roman with front size of 12. Leave a margin of 2.5 cm on both sides and at the top and 2 cm at the bottom. Use standard citations of scientific journals. You must write your thesis in English (German only in exceptional cases).

Choice of topic

You can either submit a topic of your own topic or choose a topic proposed by our chair. In case you want to work on your own a topic you need to consider that your proposal relates to the chair of banking and financial services. An overview of our research topics is given under "research” . Theoretical and empirical theses are possible. The topic of your thesis is finalized in a discussion with your supervisor.

Application

Applications or general inquiries can be sent to [email protected]

Application Deadlines

Summer term 2024: 15.03.2024

Winter term 2024/25: 31.08.2024

The Hohenheim Data Laboratory offers access to multiple, very large data banks.

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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

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.

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

Please guide me on selecting research titles

I am doing financial engineering. , can you please help me choose a dissertation topic?

I’m studying Banking and finance (MBA) please guide me on to choose a good research topic.

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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 Thesis in Banking and Finance

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Prof. Onafowokan Oluyombo

Microfinance is fast becoming a household name globally due to its acceptance as a means of reaching those that were not served by the conventional big banks. The survival of microfinance institutions in any country depends majorly on the overall political and economic environment of such a nation. However, the greatest challenge the microfinance institutions will face globally in pursuance of its financial intermediary role is how best to manage its credit and risk exposures in comparison with the rising competition, sophistication and turbulent economic and social environment especially in developing nations. After examining different concept of microfinance and risk management, this paper focus on those peculiar risks associated with microfinance business and suggested how regulators and operators in the sector can best guide against distress or imminent collapse while striking a balance between profitability and unhealthy risk exposure.

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The conviction that microfinance contributes to the reduction of poverty has attracted various investors in the sector. With the continuous growth of investments in microfinance, if the social motive is the most plausible, one would expect countries with high rates of poverty and financial exclusion to be the most attractive for investments in this sector. Aiming to understand whether the distribution of investments in different regions is led by the attractiveness of these regions in terms of risk and return or rather in terms of social impact, we use aggregate data on funds invested in the sector through Microfinance Investment Vehicles (MIVs) to study the spread of investments in microfinance around the world. It comes from the results that investments are attracted by financial performance of MFIs in the different regions, considering the return on assets and the return on equity. Further, the expenses over the assets ratio which influences negatively the variation of the investments destination suggests that regions with high cots MFIs don't receive much funds from investors. On the other side, investments seem to be oriented towards regions in which there are already institutions offering financial services, but regions with less access to financial services don't look to be the destination of investments. Is search for profit the most important driver for investments in microfinance? The results seem to go in that direction, but further research with a wider and deeper database would bring more light. However, the outcomes allow us to confirm that even if it is believed to be a poverty fighting tool, not all the investments in the microfinance sector aim the contribution to poverty reduction.

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Our knowledge about microfinance in developing countries has been greatly enriched in recent years by the experience of numerous institutions. Different sound technologies and practices of financial services to all segments of the population have emerged; there is no single best practice or optimal approach that could be simply replicated. People and institutions have to find out what suits them best. Through trial and error, they gain the experience which may then be cast into lasting innovations. Five case studies are presented, each with its own lessons concerning viability, sustainability, and outreach: two from Indonesia, two from Nepal, and one from India. In addition, lessons are drawn from the recent financial crisis in Indonesia concerning the importance of a triad of framework conditions: prudential deregulation, macroeconomic stability, and adequate bank supervision. The data are largely based on the author?s field research and consultancy work. --

Simon Grima

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Erin Gaede receives Master’s Thesis Award from the Rural Sociological Society

To explain the stigma around homelessness and housing insecurity, scholars tend to rely on urban samples and focus on the hypervisibility, what I call the  physical hypervisibility,  of people sleeping in public spaces, on park benches, and public transportation. Unlike in urban contexts, people experiencing housing insecurity in rural areas are often unseen: they are doubling up with friends and family, living in their vehicles, abandoned buildings, and state parks. As such, rural housing insecurity is often referred to as “hidden.” This hiddenness gives us reason to suspect that theories built on hypervisibility and urban samples cannot fully account for the stigma around homelessness and housing insecurity across different geographic contexts. Based on six months of ethnographic fieldwork and 37 in-depth interviews in five rural counties in Wisconsin, this paper finds that the relationship between stigma and rural housing insecurity hinges on its  social hypervisibility . In the absence of public services and infrastructure, people experiencing housing hardships in rural areas rely on the strong ties of their dense social networks, making their struggles known to others, even when they are not directly observed, such as in urban contexts. This  social hypervisibility  then facilitates stigma by shaping people’s relationships, behavior, and opportunities to climb out of poverty. These findings indicate the need to further examine how the experience of stigma, poverty, and housing insecurity vary across different geographic contexts.

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UC Davis Agricultural and Resource Economics

Are masters alum kyle nabors receives best young researcher award at 2024 irmc conference.

• Graduate Students

July 2, 2024

Kyle Nabors, 2024 ARE Masters graduate, won the Best Young Researcher Award for presenting his master’s thesis “Information in Central Bank Sentiment: An Analysis of Fed and ECB Communication” at the 2024 International Risk Management Conference in Milan, Italy.

Nabors presented on June 25 during the financial markets session of the conference. The Best Young Researcher Award is awarded to the best paper presenting a relevant empirical study related to conference topics. This year’s conference title was “Risk Management Models, Policies, and Practices in Times of High Interest Rates Uncertainty.”

Congratulations to Kyle for this prestigious award!

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Who Are the Far-Right Groups Behind the U.K. Riots?

After a deadly stabbing at a children’s event in northwestern England, an array of online influencers, anti-Muslim extremists and fascist groups have stoked unrest, experts say.

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By Esther Bintliff and Eve Sampson

Esther Bintliff reported from London, and Eve Sampson from New York.

Violent unrest has erupted in several towns and cities in Britain in recent days, and further disorder broke out on Saturday as far-right agitators gathered in demonstrations around the country.

The violence has been driven by online disinformation and extremist right-wing groups intent on creating disorder after a deadly knife attack on a children’s event in northwestern England, experts said.

A range of far-right factions and individuals, including neo-Nazis, violent soccer fans and anti-Muslim campaigners, have promoted and taken part in the unrest, which has also been stoked by online influencers .

Prime Minister Keir Starmer has vowed to deploy additional police officers to crack down on the disorder. “This is not a protest that has got out of hand,” he said on Thursday. “It is a group of individuals who are absolutely bent on violence.”

Here is what we know about the unrest and some of those involved.

Where have riots taken place?

The first riot took place on Tuesday evening in Southport, a town in northwestern England, after a deadly stabbing attack the previous day at a children’s dance and yoga class. Three girls died of their injuries, and eight other children and two adults were wounded.

The suspect, Axel Rudakubana , was born in Britain, but in the hours after the attack, disinformation about his identity — including the false claim that he was an undocumented migrant — spread rapidly online . Far-right activists used messaging apps including Telegram and X to urge people to take to the streets.

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Nishikori wins in Montreal for first victory in an ATP Masters 1000 tournament since 2021

Japan’s Ken Nishikori returns a shot to USA’s Alex Michelson during their first round match at the National Bank Open tennis tournament in Montreal, Tuesday, Aug. 6, 2024. (Ryan Remiorz/The Canadian Press via AP)

Japan’s Ken Nishikori returns a shot to USA’s Alex Michelsonn during their first round match at the National Bank Open tennis tournament in Montreal, Tuesday, Aug. 6, 2024. (Ryan Remiorz/The Canadian Press via AP)

USA’s Alex Michelson returns a shot to Japan’s Ken Nishikori during their first round match at the National Bank Open tennis tournament in Montreal, Tuesday, Aug. 6, 2024. (Ryan Remiorz/The Canadian Press via AP)

USA’s Alex Michelson serves to Japan’s Ken Nishikori during their first round match at the National Bank Open tennis tournament in Montreal, Tuesday, Aug. 6, 2024. (Ryan Remiorz/The Canadian Press via AP)

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MONTREAL (AP) — Kei Nishikori rallied to beat Alex Michelsen 3-6, 7-5, 6-4 on Tuesday in the first round of National Bank Open, earning his first victory in an ATP Masters 1000 event in three years.

The 2014 U.S. Open runner-up from Japan has battled injuries in recent years and hadn’t won a match in a Masters 1000 event, the level below the four Grand Slam tournaments, since Indian Wells in 2021. He was a finalist in the Canadian tournament in 2016, falling to Novak Djokovic.

Nishikori will face No. 8 seed Stefanos Tsitsipas in the next round.

Another oft-injured past finalist in a Grand Slam tournament had to withdraw when Canadian Milos Raonic pulled out before his first-round match against No. 13 seed Holger Rune with a shoulder injury.

“I tried to warm up for my match today and the thing that was most difficult was the serve. I don’t think I would’ve been able to be competitive by any means,” said Raonic, who had felt pain in his shoulder over the past 48 hours.

“I’ve had a lot of moments (in my career) where I haven’t been able to play, but I’d say this is probably the most difficult one. I haven’t played here in five years, and I don’t know if I’ll ever come back to Montreal.”

Rune went on to beat Roberto Bautista Agut, who had lost in the final round of qualifying, 6-2, 3-6, 6-2.

Pablo Carreño Busta, the 2022 tournament champion, beat Fabian Marozsan 6-7 (8), 7-6 (6), 6-3 for his first ATP Tour victory since the first round of the 2023 Australian Open. The Spanish player was off the tour for 15 months because of an elbow injury.

Other first-round winners included No. 15 Alejandro Tabilo, who beat Frances Tiafoe in straight sets, No. 16 seed Karen Khachanov and Italy’s Lorenzo Sonego.

AP tennis: https://apnews.com/hub/tennis