This dissertation examines the relevance of regimes for stock markets. In three research articles, we cover the identification and predictability of regimes and their relationships to macroeconomic and financial variables in the United States. The initial two chapters contribute to the debate on the predictability of stock markets. While various approaches can demonstrate in-sample predictability, their predictive power diminishes substantially in out-of-sample studies. Parameter instability and model uncertainty are the primary challenges. However, certain methods have demonstrated efficacy in addressing these issues. In Chapter 1 and 2, we present frameworks that combine these methods meaningfully. Chapter 3 focuses on the role of regimes in explaining macro-financial relationships and examines the state-dependent effects of macroeconomic expectations on cross-sectional stock returns. Although it is common to capture the variation in stock returns using factor models, their macroeconomic risk sources are unclear. According to macro-financial asset pricing, expectations about state variables may be viable candidates to explain these sources. We examine their usefulness in explaining factor premia and assess their suitability for pricing stock portfolios. In summary, this dissertation improves our understanding of stock market regimes in three ways. First, we show that it is worthwhile to exploit the regime dependence of stock markets. Markov-switching models and their extensions are valuable tools for filtering the stock market dynamics and identifying and predicting regimes in real-time. Moreover, accounting for regime-dependent relationships helps to examine the dynamic impact of macroeconomic shocks on stock returns. Second, we emphasize the usefulness of macro-financial variables for the stock market. Regime identification and forecasting benefit from their inclusion. This is particularly true in periods of high uncertainty when information processing in financial markets is less efficient. Finally, we recommend to address parameter instability, estimation risk, and model uncertainty in empirical models. Because it is difficult to find a single approach that meets all of these challenges simultaneously, it is advisable to combine appropriate methods in a meaningful way. The framework should be as complex as necessary but as parsimonious as possible to mitigate additional estimation risk. This is especially recommended when working with financial market data with a typically low signal-to-noise ratio.

This thesis contains four parts that are all connected by their contributions to the Efficient Market Hypothesis and decision-making literature. Chapter two investigates how national stock market indices reacted to the news of national lockdown restrictions in the period from January to May 2020. The results show that lockdown restrictions led to different reactions in a sample of OECD and BRICS countries: there was a general negative effect resulting from the increase in lockdown restrictions, but the study finds strong evidence for underreaction during the lockdown announcement, followed by some overreaction that is corrected subsequently. This under-/overreaction pattern, however, is observed mostly during the first half of our time series, pointing to learning effects. Relaxation of the lockdown restrictions, on the other hand, had a positive effect on markets only during the second half of our sample, while for the first half of the sample, the effect was negative. The third chapter investigates the gender differences in stock selection preferences on the Taiwan Stock Exchange. By utilizing trading data from the Taiwan Stock Exchange over a span of six years, it becomes possible to analyze trading behavior while minimizing the self-selection bias that is typically present in brokerage data. To study gender differences, this study uses firm-level data. The percentage of male traders in a company is the dependent variable, while the company’s industry and fundamental/technical aspects serve as independent variables. The results show that the percentage of women trading a company rises with a company’s age, market capitalization, a company’s systematic risk, and return. Men trade more frequently and show a preference for dividend-paying stocks and for industries with which they are more familiar. The fourth chapter investigated the relationship between regret and malicious and benign envy. The relationship is analyzed in two different studies. In experiment 1, subjects had to fill out psychological scales that measured regret, the two types of envy, core self-evaluation and the big 5 personality traits. In experiment 2, felt regret is measured in a hypothetical scenario, and the subject’s felt regret was regressed on the other variables mentioned above. The two experiments revealed that there is a positive direct relationship between regret and benign envy. The relationship between regret and malicious envy, on the other hand, is mostly an artifact of core self-evaluation and personality influencing both malicious envy and regret. The relationship can be explained by the common action tendency of self-improvement for regret and benign envy. Chapter five discusses the differences in green finance regulation and implementation between the EU and China. China introduced the Green Silk Road, while the EU adopted the Green Deal and started working with its own green taxonomy. The first difference comes from the definition of green finance, particularly with regard to coal-fired power plants. Especially the responsibility of nation-states’ emissions abroad. China is promoting fossil fuel projects abroad through its Belt and Road Initiative, but the EU’s Green Deal does not permit such actions. Furthermore, there are policies in both the EU and China that create contradictory incentives for economic actors. On the one hand, the EU and China are improving the framework conditions for green financing while, on the other hand, still allowing the promotion of conventional fuels. The role of central banks is also different between the EU and China. China’s central bank is actively working towards aligning the financial sector with green finance. A possible new role of the EU central bank or the priority financing of green sectors through political decision-making is still being debated.

Survey data can be viewed as incomplete or partially missing from a variety of perspectives and there are different ways of dealing with this kind of data in the prediction and the estimation of economic quantities. In this thesis, we present two selected research contexts in which the prediction or estimation of economic quantities is examined under incomplete survey data. These contexts are first the investigation of composite estimators in the German Microcensus (Chapters 3 and 4) and second extensions of multivariate Fay-Herriot (MFH) models (Chapters 5 and 6), which are applied to small area problems. Composite estimators are estimation methods that take into account the sample overlap in rotating panel surveys such as the German Microcensus in order to stabilise the estimation of the statistics of interest (e.g. employment statistics). Due to the partial sample overlaps, information from previous samples is only available for some of the respondents, so the data are partially missing. MFH models are model-based estimation methods that work with aggregated survey data in order to obtain more precise estimation results for small area problems compared to classical estimation methods. In these models, several variables of interest are modelled simultaneously. The survey estimates of these variables, which are used as input in the MFH models, are often partially missing. If the domains of interest are not explicitly accounted for in a sampling design, the sizes of the samples allocated to them can, by chance, be small. As a result, it can happen that either no estimates can be calculated at all or that the estimated values are not published by statistical offices because their variances are too large.

For decades, academics and practitioners aim to understand whether and how (economic) events affect firm value. Optimally, these events occur exogenously, i.e. suddenly and unexpectedly, so that an accurate evaluation of the effects on firm value can be conducted. However, recent studies show that even the evaluation of exogenous events is often prone to many challenges that can lead to diverse interpretations, resulting in heated debates. Recently, there have been intense debates in particular on the impact of takeover defenses and of Covid-19 on firm value. The announcements of takeover defenses and the propagation of Covid-19 are exogenous events that occur worldwide and are economically important, but have been insufficiently examined. By answering open research questions, this dissertation aims to provide a greater understanding about the heterogeneous effects that exogenous events such as the announcements of takeover defenses and the propagation of Covid-19 have on firm value. In addition, this dissertation analyzes the influence of certain firm characteristics on the effects of these two exogenous events and identifies influencing factors that explain contradictory results in the existing literature and thus can reconcile different views.

The Belt and Road Initiative (BRI) has had a significant impact on China in political, economic, and cultural terms. This study focuses on the cultural domain, especially on scholarship students from the countries that signed bilateral cooperation agreements with China under the BRI. Using an integrated approach combining the difference-in-differences method and the gravity model, we explore the correlation between the BRI and the increasing number of international scholarship students funded by the Chinese government, as well as the determinants of students' decision to study in China. The panel data from 2010 to 2018 show that the launch of BRI has had a positive impact on the number of scholarship students from BRI countries. The number of scholarship recipients from non-BRI countries also increased, but at a much slower rate than those from BRI countries. The sole exception is the United States, which has trended downward for both state-funded and self-funded students.