Contributions published at Department of Banking and Finance (Pablo Koch Medina)

We adapt the design of four experimental studies on retirement decision-making and conduct replications with a larger online sample from the broader population. We replicate most of the main effects of the original studies. In particular, we confirm that consumption decisions are less efficient when subjects need to borrow from the future than when they need to save from the present. When subjects collect retirement benefits as lump sum instead of annuities, they choose to retire later, as suggested by the original study. We also confirm that savings are higher when they are incentivized with matching contributions than when incentivized with tax rebates. However, when faced with varying survival risks, subjects in our replication make only partial adjustments to spending paths when ambiguity is reduced. We also propose a further experimental research agenda in related topics and discuss practical issues on subject recruitment, attrition, and redesign of complex tasks.

Conditional heteroskedasticity of the error terms is a common occurrence in financial factor models, such as the CAPM and Fama–French factor models. This feature necessitates the use of heteroskedasticity consistent (HC) standard errors to make valid inference for regression coefficients. In this paper, we show that using weighted least squares (WLS) or adaptive least squares (ALS) to estimate model parameters generally leads to smaller HC standard errors compared to ordinary least squares (OLS), which translates into improved inference in the form of shorter confidence intervals and more powerful hypothesis tests. In an extensive empirical analysis based on historical stock returns and commonly used factors, we find that conditional heteroskedasticity is pronounced and that WLS and ALS can dramatically shorten confidence intervals compared to OLS, especially during times of financial turmoil.

This paper studies how to incorporate observable factors in difference-in-differences and document their empirical relevance. We show that even under random assignment directly adding factors with unit-specific loadings into the difference-in-differences estimation results in biased estimates. This bias, which we term the “bad time control problem” arises when the treatment effect covaries with the factor variation. Researchers often control for factor structures by using: (i) unit time trends, (ii) pre-treatment covariates interacted with a time trend and (iii) group-time dummies. We show that all these methods suffer from the bad time control problem and/or omitted factor bias. We propose two solutions to the bad time control problem. To evaluate the relevance of the factor structure we study US housing returns. Adding macroeconomic factors shows that factors have additional explanatory power and estimated factor loadings differ systematically across geographic areas. This results in substantially altered treatment effects.

We study binary opinion formation in a large population where individuals are influenced by the opinions of other individuals. The population is characterised by the existence of (i) communities where individuals share some similar features, (ii) opinion leaders that may trigger unpredictable opinion shifts in the short term (iii) some degree of incomplete information in the observation of the individual or public opinion processes. In this setting, we study three different approximate mechanisms: common sampling approximation, independent sampling approximation, and, what will be our main focus in this paper, McKean-Vlasov (or mean-field) approximation. We show that all three approximations perform well in terms of different metrics that we introduce for measuring population level and individual level errors. In the presence of a common noise represented by the major influencers opinions processes, and despite the absence of idiosyncratic noises, we derive a propagation of chaos type result. For the particular case of a linear model and particular specifications of the major influencers opinion dynamics, we provide additional analysis, including long term behavior and fluctuations of the public opinion. The theoretical results are complemented by some concrete examples and numerical analysis, illustrating the formation of echo-chambers, the propagation of chaos, and phenomena such as snowball effect and social inertia.

Deloitte Luxembourg’s MOMENTUM Conference, its flagship sustainability event, is a stage for collaboration, knowledge sharing, and action. This year’s edition furthered discussions from the 27th session of the Conference of the Parties to the UN Framework Convention on Climate Change (COP27) in November 2022.

What do asset managers believe regarding the financial performance of Environmental, Social, and Governance (ESG) investment strategies? We address this question by exploring the relationship between fund managers’ co-ownership and portfolio ESG performance. Managers with more “skin in the game” exhibit significantly lower ESG performance in funds they manage than their peers. ESG performance is sensitive to changes in managerial ownership. Co-investing managers were less likely to increase their stake in high-ESG stocks after an exogenous shock in ESG-driven fund flows. Moreover, the negative effect of managerial ownership on ESG performance is stronger for managers paid to maximize assets under management, and weaker for managers paid exclusively to maximize financial returns. Overall, the results are contrary to what one would expect if managers really considered ESG strategies an enhanced form of portfolio management.

Random changes in firms' stock index membership have important implications on sell-side analysts' career outcomes. Covered firms moving from the bottom of Russell 1000 to the top of Russell 2000 significantly increase an analyst's likelihood of moving to a high-status broker or receiving a career-first All-Star Analyst nomination - particularly for early-career analysts. This is reflected in analyst recommendations. For firms that are just above the index threshold - that might move to Russell 2000 if their share price decreases slightly - analyst recommendations are significantly more negative around the time of defining the index weights that determine index membership.

Through a survey and analyses of observational data, we provide systematic evidence that institutional investors value and demand climate risk disclosures. The survey reveals the investors have a strong demand for climate risk disclosures, and many actively engage their portfolio firms for improvements. Empirical analyses of holdings data corroborate this evidence by showing a significantly positive association between climate-conscious institutional ownership and better firm-level climate risk disclosure. We establish further evidence of institutional investors’ influence on firms’ climate risk disclosures by examining a shock to the climate risk disclosure demand of French institutional investors (French Article 173).

Nachhaltiges Investieren hat sich zum Mainstream entwickelt. Doch das rasante Wachstum und intransparente Anlageprodukte schüren verbreitet Skepsis.

Evolutionary Finance (EF) explores financial markets as evolving biological systems. Investors pursuing diverse investment strategies compete for the market capital. Some "survive" and some "become extinct". A central goal is to identify evolutionary stable (in one sense or another) investment strategies. The problem is analyzed in a framework combining stochastic dynamics and evolutionary game theory. Most of the models currently considered in EF assume that asset payo¤s are exogenous and depend only on the underlying stochastic process of states of the world. The present work develops a model where the payo¤s are endogenous: they depend on the share of total market wealth invested in the asset.

Wie beeinflussen der demografische Wandel und der Klimawandel die Entscheidungen von Finanzmarktakteuren? Welche spezifischen Herausforderungen und Auswirkungen ergeben sich für verschiedene zivilgesellschaftliche Akteure wie beispielsweise Rentner/innen, Eigenheimbesitzer/innen, Erben/-innen, Privatanleger/innen im Allgemeinen, Banken, und Firmen? Um diesen Fragen nachzugehen, veranstaltete das ZEW Mannheim am 27. und 28. April 2023 eine Konferenz zum Thema Altern und nachhaltige Finanzen.

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This thesis investigates the bank lending channel in China from three perspectives: its overall impact on banks’ balance sheets (deposits and loans) and macroeconomic variables (production and financialization), the supply-side effect and the assumption of imperfect substitutability, and the external finance premium. Multiple VAR models are utilized, and the effects of uncertainty stemming from COVID-19 and lockdown measures are analyzed by comparing results across different sample periods. Using monthly data from January 2011 to December 2022, the findings demonstrate the existence of an efficient bank lending channel in China, with the main leakage occurring within the banking system rather than the stock market. The efficiency of the bank lending channel in altering banks’ balance sheets is undermined by the uncertainty associated with COVID-19 and lockdown measures. However, the assumption of imperfect substitutability is found to be invalid for firms without access to corporate bonds throughout the entire period. These results highlight the need for policymakers and researchers to place greater emphasis on the development of alternative transmission channels through financial markets and the improvement of regulations to achieve more effective policy implementation that impacts economic entities. I

Das Ziel dieser Arbeit ist es, dass die Leser*innen ein tieferes Verständnis bezüglich Zombie-Unternehmen erhalten und sich deren Gefahren in der Wirtschaft bewusst werden. Im Rahmen dessen wird anfangs erklärt, welche Kennzahlen ein Zombie-Unternehmen charakterisieren, wobei im Allgemeinen gesagt werden kann, dass diese Unternehmen eine hohe Verschuldung, sowie eine geringe Rentabilität aufweisen. Dabei begünstigen finanziell schwache Banken, ein ineffizientes Insolvenzregime, sowie ein niedriges Zinsniveau und Finanzkrisen die Entstehung und Aufrechthaltung von nicht lebensfähigen Unternehmen. In den meisten Fällen betrifft dies kleine und mittlere Unternehmen mit einem Umsatz von weniger als 500 Millionen US-Dollar. Im Vergleich zu gesunden Unternehmen weisen die Zombie-Firmen eine geringere Investitionstätigkeit wie eine halb so hohe Arbeits- und Gesamtproduktivität auf. Zugleich binden sie begrenzte Ressourcen, wie Human- und Finanzkapital in der Branche, was zur Folge hat, dass gesunde Unternehmen ihr Potenzial nicht ausschöpfen können. Durch die Verzerrung des Marktes gibt es ein Überangebot, daraus resultiert eine geringere Gewinnmarge und höhere Barrieren für Markteinsteiger. Die Immobilienbranche weist mit rund acht Prozent den höchsten Anteil an Zombie-Unternehmen in der Wirtschaft auf. Viele Wissenschaftler*innen sehen mit der Verbesserung der Insolvenzreglungen und der Stabilisierung der schwachen Banken essenzielle Massnahmen, um die Entstehung beziehungsweise Aufrechthaltung der Zombie-Unternehmen zu hemmen.

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This thesis examines the potential impact of social media on the financial markets and associated dangers. The focus lays on the share prices and volume charts of GameStop, AMC Entertainment, Blackberry and Bed Bath & Beyond within the time frame from July 2020 to December 2021. Twitter serves as the social media platform for this analysis. The objective of this analysis is to determine whether the volume and share price movements occur after a corresponding rise or fall in number of tweets. Notably, this investigation reveals a noteworthy correlation and highlights the existence of substantial dangers.

Diese Arbeit untersucht die Auswirkungen von ESG-Exclusions auf die risikoadjustierte Performance eines Portfolios. Dazu werden 22 Exclusions sowohl einzeln als auch in thematischen Gruppen auf das Portfolio der Schweizer Krankenversicherung CSS angewendet. Die daraus entstehenden Exclusion-Portfolios werden anhand der Rendite, Sharpe-Ratio, Tracking-Error, Information-Ratio und in verschiedenen Faktor-Modellen ¨uber den Zeitraum von 2010 bis 2022 verglichen. Die Resultate zeigen, dass die verschiedenen Exclusions unterschiedliche Auswirkungen auf die Portfolios haben. Die Mehrzahl der Exclusions f¨uhrt zu einer besseren absoluten und risikoadjustierten Rendite bzw. zu besseren Performancemassen. Jedoch sind diese Resultate abh¨angig vom gew¨ahlten Zeitraum, wie rollierende Berechnungen zeigen.

Nachhaltige Firmenkredite sind ein aufkommendes Thema im Schweizer Kreditmarkt. Zusätzlich zur Kreditfähigkeit und -würdigkeit beinhaltet die Bonitätsprüfung eine Nachhaltigkeitskomponente, wodurch die Informationengrundmenge steigt. Somit ist die Forschungsfrage naheliegend, ob sich die Informationsasymmetrien zwischen Kreditgeber und -nehmer vergrössern, sobald ein Kredit als nachhaltig deklariert wird. Zur Beantwortung der Forschungsfrage wird eine qualitative Forschungsmethode angewendet, wobei Experten aus vier verschiedenen Schweizer Banken interviewt werden. Der Fokus liegt auf den Nachhaltigkeitskriterien und deren Einfluss auf die Informationsasymmetrien. Die Ergebnisse zeigen, dass die Informationsasymmetrien bei nachhaltigen Krediten tendenziell schwächer wirken, da das zu finanzierende Unternehmen genauer analysiert wird und somit eine engere Kundenbeziehung entsteht.

This thesis aims to bring finance and machine learning together and examines whether a model can be created that is used to evaluate if the US stock market can be outperformed using solely freely available data excluding paid financial services of data providers entirely. Said examination is done for two time dimensions yearly and quarterly with a focus on both the complete market and a sector-based approach. Different machine learning techniques such as logistic regression, random forest, gradient boosting, and support vector machine are being used and applied for the task at hand. Although the results are less than ideal, the model performance may improve over time when more data is added. However, the sector-based results are more promising due to some sectors scoring higher in the examined model performance metrics. II