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A Literature Review on Wetlands in Accra (2019)

Wiegleb, Viviana

This literature review was conducted to identify important wetlands in the Greater Accra Region and to illustrate dominant research trends, prevailing perspectives and corresponding research gaps. Six wetlands systems were identified as most significant lagoon systems, namely the Densu Delta, Sakumo, Muni-Pomadze, Keta, Korle and Songor Lagoons. Research foci for each of the respective wetlands were extrapolated and summarized in a category system. The frequency of different categories illustrates that natural science’s perspectives dominate, as most of Accra’s lagoons have been studied with regard to their ecological, physical and chemical properties. The development of research interest over time and focus on ecological baseline conditions are related to the designation of Ramsar Sites and orientation of national policies towards environmental protection. A research gap was identified, as studies link their findings to human activities but neglect the connection between governance variables and environmental developments. It is suggested to expand the natural science’s perspective on Accra’s wetlands to account for social and political aspects in order to develop a holistic and more sustainable management strategy.

What is driving the Water-Energy-Food Nexus? Discourses, knowledge and politics of an emerging resource governance concept (2018)

Wiegleb, Viviana ; Bruns, Antje

In the context of accelerated global socio-environmental change, the Water-Energy-Food Nexus has received increasing attention within science and international politics by promoting integrated resource governance. This study explores the scientific nexus debates from a discourse analytical perspective to reveal knowledge and power relations as well as geographical settings of nexus research. We also investigate approaches to socio-nature relations that influence nexus research and subsequent political implications. Our findings suggest that the leading nexus discourse is dominated by natural scientific perspectives and a neo-Malthusian framing of environmental challenges. Accordingly, the promoted cross-sectoral nexus approach to resource governance emphasizes efficiency, security, future sustainability, and poverty reduction. Water, energy, and food are conceived as global trade goods that require close monitoring, management and control, to be achieved via quantitative assessments and technological interventions. Within the less visible discourse, social scientific perspectives engage with the social, political, and normative elements of the Water-Energy-Food Nexus. These perspectives criticize the dominant nexus representation for itsmanagerial, neoliberal, and utilitarian approach to resource governance. The managerial framing is critiqued for masking power relations and social inequalities, while alternative framings acknowledge the political nature of resource governance and socio-nature relations. The spatial dimensions of the nexus debate are also discussed. Notably, the nexus is largely shaped by western knowledge, yet applied mainly in specific regions of the Global South. In order for the nexus to achieve integrative solutions for sustainability, the debate needs to overcome its current discursive and spatial separations. To this end, we need to engage more closely with alternative nexus discourses, embrace epistemic pluralism and encourage multi-perspective debates about the socio-nature relations we actually intend to promote.

Construction of optimal quantizers for Gaussian measures on Banach spaces (2008)

Wilbertz, Benedikt

In this thesis, we investigate the quantization problem of Gaussian measures on Banach spaces by means of constructive methods. That is, for a random variable X and a natural number N, we are searching for those N elements in the underlying Banach space which give the best approximation to X in the average sense. We particularly focus on centered Gaussians on the space of continuous functions on [0,1] equipped with the supremum-norm, since in that case all known methods failed to achieve the optimal quantization rate for important Gauss-processes. In fact, by means of Spline-approximations and a scheme based on the Best-Approximations in the sense of the Kolmogorov n-width we were able to attain the optimal rate of convergence to zero for these quantization problems. Moreover, we established a new upper bound for the quantization error, which is based on a very simple criterion, the modulus of smoothness of the covariance function. Finally, we explicitly constructed those quantizers numerically.

A Framework for Multiobjective and Uncertain Resource Allocation Problems in Survey Sampling based on Conic Optimization (2025)

Willems, Felix

In most textbooks optimal sample allocation is tailored to rather theoretical examples. However, in practice we often face large-scale surveys with conflicting objectives and many restrictions on the quality and cost at population and subpopulation levels. This multiobjectiveness results in a multitude of efficient sample allocations, each giving different weight to a single survey purpose. Additionally, since the input data to the allocation problem often relies on supplementary information derived from estimation, historical data, or expert knowledge, allocations might be inefficient when specified for sampling. This doctoral thesis presents a framework for optimal allocation to standard sampling schemes that allows for specifying the tradeoff between different objectives and analyzing their sensitivity to other problem components, aiming to support a decision-maker in identifying an at-most preferred sample allocation. It dedicates a full chapter to each of the following core questions: 1) How to efficiently incorporate quality and cost constraints for large-scale surveys, say, for thousands of strata with hundreds of precision and cost constraints? 2) How to handle vector-valued objectives with their components addressing different, possibly conflicting survey purposes? 3) How to consider uncertainty in the input data? The techniques presented can be used separately or in combination as a general problem-solving framework for constrained multivariate and multidomain, possibly uncertain, sample allocation. The main problem is formulated in a way that highlights the different components of optimal sample allocation and can be taken as a gateway to develop solution strategies to each of the questions above, while shifting the focus between different problem aspects. The first question is addressed through a conic quadratic reformulation, which can be efficiently solved for large problem instances using interior-point methods. Based on this the second question is tackled using a weighted Chebyshev minimization, which provides insight into the sensitivity of the problem and enables a stepwise procedure for considering nonlinear decision functionals. Lastly, uncertainty in the input data is addressed through regularization, chance constraints and robust problem formulations.

Southern Ocean sea-ice leads: first insights into regional lead patterns, seasonality, and trends, 2003–2023 (2025)

Willmes, Sascha ; Dubey, Umesh ; Heinemann, Günther

Sea-ice leads play a key role in the climate system by facilitating heat and moisture exchanges between the ocean and atmosphere, as well as by providing essential habitats for marine life. This study presents new insights from a gap-filled monthly dataset on sea-ice leads in the Southern Ocean and a first comprehensive analysis of spatial patterns, seasonal variability, and long-term trends of wintertime (April to September) sea-ice leads over a 21-year period (2003–2023). Our findings reveal that leads are ubiquitous in the Southern Ocean and show distinct spatial patterns with maximum lead frequencies close to the coastline, over the shelf break, and close to seafloor ridges and peaks. We see a strong seasonal variability in lead occurrence, with lead frequencies peaking in mid-winter. Weak but significant trends in lead frequencies are shown for the presented period for individual regions and months. Rather small changes in lead occurrence over the 21 years suggest stable wintertime sea-ice compactness despite the observed strong fluctuations and recent anomalies in sea-ice extent. Expanding upon previous work of lead detection in Antarctic sea ice, this study provides first results on the long-term regional, seasonal, and inter-annual variability of sea-ice leads in the Southern Ocean and can thereby contribute to an improved understanding of air–sea-ice–ocean interactions in the climate system. It also underscores the need for further investigation into the individual contributions of atmospheric and oceanic drivers to sea-ice lead formation in the Antarctic.

Patterns of wintertime Arctic sea-ice leads and their relation to winds and ocean currents (2023)

Willmes, Sascha ; Heinemann, Günther ; Schnaase, Frank

We use a novel sea-ice lead climatology for the winters of 2002/03 to 2020/21 based on satellite observations with 1 km2 spatial resolution to identify predominant patterns in Arctic wintertime sea-ice leads. The causes for the observed spatial and temporal variabilities are investigated using ocean surface current velocities and eddy kinetic energies from an ocean model (Finite Element Sea Ice–Ice-Shelf–Ocean Model, FESOM) and winds from a regional climate model (CCLM) and ERA5 reanalysis, respectively. The presented investigation provides evidence for an influence of ocean bathymetry and associated currents on the mechanic weakening of sea ice and the accompanying occurrence of sea-ice leads with their characteristic spatial patterns. While the driving mechanisms for this observation are not yet understood in detail, the presented results can contribute to opening new hypotheses on ocean–sea-ice interactions. The individual contribution of ocean and atmosphere to regional lead dynamics is complex, and a deeper insight requires detailed mechanistic investigations in combination with considerations of coastal geometries. While the ocean influence on lead dynamics seems to act on a rather long-term scale (seasonal to interannual), the influence of wind appears to trigger sea-ice lead dynamics on shorter timescales of weeks to months and is largely controlled by individual events causing increased divergence. No significant pan-Arctic trends in wintertime leads can be observed.

A Penalty Branch-and-Bound Method for Piecewise Convex Objective Functions (2023)

Winkel, Lukas

Die Dissertation beschäftigt sich mit einer neuartigen Art von Branch-and-Bound Algorithmen, deren Unterschied zu klassischen Branch-and-Bound Algorithmen darin besteht, dass das Branching durch die Addition von nicht-negativen Straftermen zur Zielfunktion erfolgt anstatt durch das Hinzufügen weiterer Nebenbedingungen. Die Arbeit zeigt die theoretische Korrektheit des Algorithmusprinzips für verschiedene allgemeine Klassen von Problemen und evaluiert die Methode für verschiedene konkrete Problemklassen. Für diese Problemklassen, genauer Monotone und Nicht-Monotone Gemischtganzzahlige Lineare Komplementaritätsprobleme und Gemischtganzzahlige Lineare Probleme, präsentiert die Arbeit verschiedene problemspezifische Verbesserungsmöglichkeiten und evaluiert diese numerisch. Weiterhin vergleicht die Arbeit die neue Methode mit verschiedenen Benchmark-Methoden mit größtenteils guten Ergebnissen und gibt einen Ausblick auf weitere Anwendungsgebiete und zu beantwortende Forschungsfragen.

From Financial Stability to Digital Payments: Empirical Insights into Central Banking (2025)

Wischnewsky, Arina

The new millennium has been characterized by rising digitalization, the proliferation of shadow banking, and significant advancements in machine learning and natural language processing. These trends present both challenges and opportunities, which my dissertation addresses. This cumulative dissertation investigates critical aspects of financial stability, monetary policy, and the transition towards cashless economies through three distinct but interrelated studies. The first paper examines the risk-taking channel of monetary policy transmission within the euro area, focusing on shadow banks. Through vector autoregressive models, it assesses the impact of conventional and unconventional monetary policy shocks on shadow banks' asset growth and risk asset ratios. The results indicate that lower interest rates lead to a portfolio reallocation towards riskier assets and a general expansion of assets in shadow banks. In the case of conventional monetary policy shocks, both effects last three times as long as in the case of unconventional monetary policy shocks. Country-specific as well as sector-specific estimations confirm these findings. This study bridges gaps in the existing literature, especially in the eurozone, by highlighting the significant role shadow banks play in monetary policy transmission, suggesting implications for financial regulation and stability. The second paper explores the influence of financial stability considerations on US monetary policy, particularly during the Great Recession. Utilizing natural language processing and machine learning techniques on congressional hearings, this study constructs indicators for financial stability sentiment expressed by the Federal Reserve Chairs. Empirical analysis is conducted using Taylor-rule models, revealing that negative financial stability sentiment is associated with a more accommodative monetary policy stance, even before the Great Recession. This work provides new insights into the integration of financial stability concerns into monetary policy frameworks, demonstrating the need for a balanced approach to economic stability. The article suggests that under a dual mandate, such as that of the Federal Reserve, financial stability can, to some extent, already be factored into monetary policy deliberations. The third paper sheds new light on ``cash paradox'' by uncovering the factors of the cashless transition that has not been entirely understood so far. Using a comprehensive dataset across 65 countries, the study employs panel data models to explain the paradox (increasing demand for central bank money despite soaring digitalization), especially among technologically advanced countries, e.g., Japan. Empirical evidence suggests that digitalization is not significantly associated with higher reliance on physical cash. It uncovers a unique non-linear relationship between trust and cash usage (``Arch of Trust'') which holds after addressing potential endogeneity issues using 2SLS estimation. Opposed to the widespread misinterpretations of Keynes' (1937) reasons for holding cash, the findings highlight that distrust is the key factor unlocking two distinct puzzles in economics, linking cash hoarding with ``missing'' funds on capital markets and slower shift toward digital payments in low-trust societies. A key insight is the role of trust as a (social) insurance, cushion or safety net, dampening the perception of risk and reducing precautionary and transactionary demand for physical cash, while encouraging a shift towards riskier alternatives. This, in turn, is connected to the third puzzle, the ``paradox of prudence.'' A shift from riskier investments to safer assets, cash, may be prudent at the individual level but risky for the overall economy, a concern for macroprudential policymakers. Additionally, the research highlights the critical role of culture in driving the global movement towards cashless economies. Moreover, cultures that are more self-expression-oriented (which is the main cultural dimension) and culturally closer to Sweden are associated with less cash-intensive economies. These insights are vital for macroprudential regulators as well as for policymakers designing payment systems and CBDC in culturally diverse regions like the Eurozone. Collectively, these papers contribute to a deeper understanding of monetary policy, financial stability, and the transition from cash-based to (nearly) cashless societies, offering significant theoretical and practical implications for academics, regulators and central bankers.

Some aspects of the optimization over the copositive and the completely positive cone (2014)

Witzel, Julia

Copositive programming is concerned with the problem of optimizing a linear function over the copositive cone, or its dual, the completely positive cone. It is an active field of research and has received a growing amount of attention in recent years. This is because many combinatorial as well as quadratic problems can be formulated as copositive optimization problems. The complexity of these problems is then moved entirely to the cone constraint, showing that general copositive programs are hard to solve. A better understanding of the copositive and the completely positive cone can therefore help in solving (certain classes of) quadratic problems. In this thesis, several aspects of copositive programming are considered. We start by studying the problem of computing the projection of a given matrix onto the copositive and the completely positive cone. These projections can be used to compute factorizations of completely positive matrices. As a second application, we use them to construct cutting planes to separate a matrix from the completely positive cone. Besides the cuts based on copositive projections, we will study another approach to separate a triangle-free doubly nonnegative matrix from the completely positive cone. A special focus is on copositive and completely positive programs that arise as reformulations of quadratic optimization problems. Among those we start by studying the standard quadratic optimization problem. We will show that for several classes of objective functions, the relaxation resulting from replacing the copositive or the completely positive cone in the conic reformulation by a tractable cone is exact. Based on these results, we develop two algorithms for solving standard quadratic optimization problems and discuss numerical results. The methods presented cannot immediately be adapted to general quadratic optimization problems. This is illustrated with examples.

The Firepower of Work Craving: When Self-Control Is Burning under the Rubble of Self-Regulation (2017)

Wojdylo, Kamila ; Baumann, Nicola ; Kuhl, Julius

Work craving theory addresses how work-addicted individuals direct great emotion-regulatory efforts to weave their addictive web of working. They crave work for two main emotional incentives: to overcompensate low self-worth and to escape (i.e., reduce) negative affect, which is strategically achieved through neurotic perfectionism and compulsive working. Work-addicted individuals" strong persistence and self-discipline with respect to work-related activities suggest strong skills in volitional action control. However, their inability to disconnect from work implies low volitional skills. How can work-addicted individuals have poor and strong volitional skills at the same time? To answer this paradox, we elaborated on the relevance of two different volitional modes in work craving: self-regulation (self-maintenance) and self-control (goal maintenance). Four hypotheses were derived from Wojdylo- work craving theory and Kuhl- self-regulation theory: (H1) Work craving is associated with a combination of low self-regulation and high self-control. (H2) Work craving is associated with symptoms of psychological distress. (H3) Low self-regulation is associated with psychological distress symptoms. (H4) Work craving mediates the relationships between self-regulation deficits and psychological distress symptoms at high levels of self-control. Additionally, we aimed at supporting the discriminant validity of work craving with respect to work engagement by showing their different volitional underpinnings. Results of the two studies confirmed our hypotheses: whereas work craving was predicted by high self-control and low self-regulation and associated with higher psychological distress, work engagement was predicted by high self-regulation and high self-control and associated with lower symptoms of psychological distress. Furthermore, work styles mediated the relationship between volitional skills and symptoms of psychological distress. Based on these new insights, several suggestions for prevention and therapeutic interventions for work-addicted individuals are proposed.

Generalized Synchronization and Intersection Non-Emptiness of Finite-State Automata (2022)

Wolf, Petra

The main focus of this work is to study the computational complexity of generalizations of the synchronization problem for deterministic finite automata (DFA). This problem asks for a given DFA, whether there exists a word w that maps each state of the automaton to one state. We call such a word w a synchronizing word. A synchronizing word brings a system from an unknown configuration into a well defined configuration and thereby resets the system. We generalize this problem in four different ways. First, we restrict the set of potential synchronizing words to a fixed regular language associated with the synchronization under regular constraint problem. The motivation here is to control the structure of a synchronizing word so that, for instance, it first brings the system from an operate mode to a reset mode and then finally again into the operate mode. The next generalization concerns the order of states in which a synchronizing word transitions the automaton. Here, a DFA A and a partial order R is given as input and the question is whether there exists a word that synchronizes A and for which the induced state order is consistent with R. Thereby, we study different ways for a word to induce an order on the state set. Then, we change our focus from DFAs to push-down automata and generalize the synchronization problem to push-down automata and in the following work, to visibly push-down automata. Here, a synchronizing word still needs to map each state of the automaton to one state but it further needs to fulfill some constraints on the stack. We study three different types of stack constraints where after reading the synchronizing word, the stacks associated to each run in the automaton must be (1) empty, (2) identical, or (3) can be arbitrary. We observe that the synchronization problem for general push-down automata is undecidable and study restricted sub-classes of push-down automata where the problem becomes decidable. For visibly push-down automata we even obtain efficient algorithms for some settings. The second part of this work studies the intersection non-emptiness problem for DFAs. This problem is related to the problem of whether a given DFA A can be synchronized into a state q as we can see the set of words synchronizing A into q as the intersection of languages accepted by automata obtained by copying A with different initial states and q as their final state. For the intersection non-emptiness problem, we first study the complexity of the, in general PSPACE-complete, problem restricted to subclasses of DFAs associated with the two well known Straubing-Thérien and Cohen-Brzozowski dot-depth hierarchies. Finally, we study the problem whether a given minimal DFA A can be represented as the intersection of a finite set of smaller DFAs such that the language L(A) accepted by A is equal to the intersection of the languages accepted by the smaller DFAs. There, we focus on the subclass of permutation and commutative permutation DFAs and improve known complexity bounds.

Diagnostic Competencies of Teachers: Accuracy of Judgment, Sources of Bias, and Consequences of (Mis-)Judgment (2017)

Wollschläger, Rachel

Educational assessment tends to rely on more or less standardized tests, teacher judgments, and observations. Although teachers spend approximately half of their professional conduct in assessment-related activities, most of them enter their professional life unprepared, as classroom assessment is often not part of their educational training. Since teacher judgments matter for the educational development of students, the judgments should be up to a high standard. The present dissertation comprises three studies focusing on accuracy of teacher judgments (Study 1), consequences of (mis-)judgment regarding teacher nomination for gifted programming (Study 2) and teacher recommendations for secondary school tracks (Study 3), and individual student characteristics that impact and potentially bias teacher judgment (Studies 1 through 3). All studies were designed to contribute to a further understanding of classroom assessment skills of teachers. Overall, the results implied that, teacher judgment of cognitive ability was an important constant for teacher nominations and recommendations but lacked accuracy. Furthermore, teacher judgments of various traits and school achievement were substantially related to social background variables, especially the parents" educational background. However, multivariate analysis showed social background variables to impact nomination and recommendation only marginally if at all. All results indicated differentiated but potentially biased teacher judgments to impact their far-reaching referral decisions directly, while the influence of social background on the referral decisions itself seems mediated. Implications regarding further research practices and educational assessment strategies are discussed. The implications on the needs of teachers to be educated on judgment and educational assessment are of particular interest and importance.

Do we know what we think we know? - Transferability of findings from randomized controlled trials to routine care treatment settings (2017)

Wucherpfennig, Felix

Numerous RCTs demonstrate that cognitive behavioral therapy (CBT) for depression is effective. However, these findings are not necessarily representative of CBT under routine care conditions. Routine care studies are not usually subjected to comparable standardizations, e.g. often therapists may not follow treatment manuals and patients are less homogeneous with regard to their diagnoses and sociodemographic variables. Results on the transferability of findings from clinical trials to routine care are sparse and point in different directions. As RCT samples are selective due to a stringent application of inclusion/exclusion criteria, comparisons between routine care and clinical trials must be based on a consistent analytic strategy. The present work demonstrates the merits of propensity score matching (PSM), which offers solutions to reduce bias by balancing two samples based on a range of pretreatment differences. The objective of this dissertation is the investigation of the transferability of findings from RCTs to routine care settings.

Model-Based Prediction and Estimation Using Incomplete Survey Data (2023)

Wölwer, Anna-Lena

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.

Group singing through the lens of polyvagal theory: A pilot study in patients with Parkinson's disease (2025)

Wünnenberg, Elke ; Baumann, Nicola

There is a need to counteract the chronic progression of Parkinson’s disease (PD). This complex challenge requires new theoretical frameworks and practical strategies. In this study, we implemented group singing in line with the Singing Hospitals format and examined it through the lens of Polyvagal Theory to evaluate its potential benefits for people with PD. According to Polyvagal Theory, facilitating a shift in autonomic states from defense to safety and social engagement may enhance physiological regulation and thereby promote well-being across physical, mental, emotional, and social dimensions. In a pilot study, we recruited patients with PD and examined their responses to two group singing formats (weekly sessions: N1 = 13, one-day-workshop: N2 = 14) and a non-singing control group (N3 = 22). We designed scales of physical, mental, emotional, and social states that PD patients rated before and after eight one-hour singing sessions (N1) or an eight-hour singing workshop (N2). Findings show that PD patients benefited from group singing across both settings (large effect size: d = 2.43). Furthermore, self-reported interoceptive sensibility, used as a proxy for polyvagal autonomic reactivity, showed a substantial reduction in discomfort after weekly singing, while remaining constant in the control group (large effect size: d = 0.94). We observed the predicted singing-dependent effects and interpreted them as a shift in autonomic regulation consistent with Polyvagal Theory. Singing may represent a feasible, low-threshold resource for coping. Furthermore, Polyvagal Theory may provide an innovative framework for PD and help to bridge motor and non-motor symptoms.

Path to entrepreneurship and business succession: Antecedents and performance consequences (2017)

Xi, Guoqian

Entrepreneurship is a process of discovering and exploiting opportunities, during which two crucial milestones emerge: in the very beginning when entrepreneurs start their businesses, and in the end when they determine the future of the business. This dissertation examines the establishment and exit of newly created as well as of acquired firms, in particular the behavior and performance of entrepreneurs at these two important stages of entrepreneurship. The first part of the dissertation investigates the impact of characteristics at the individual and at the firm level on an entrepreneur- selection of entry modes across new venture start-up and business takeover. The second part of the dissertation compares firm performance across different entrepreneurship entry modes and then examines management succession issues that family firm owners have to confront. This study has four main findings. First, previous work experience in small firms, same sector experience, and management experience affect an entrepreneur- choice of entry modes. Second, the choice of entry mode for hybrid entrepreneurs is associated with their characteristics, such as occupational experience, level of education, and gender, as well as with the characteristics of their firms, such as location. Third, business takeovers survive longer than new venture start-ups, and both entry modes have different survival determinants. Fourth, the family firm- decision of recruiting a family or a nonfamily manager is not only determined by a manager- abilities, but also by the relationship between the firm- economic and non-economic goals and the measurability of these goals. The findings of this study extend our knowledge on entrepreneurship entry modes by showing that new venture start-ups and business takeovers are two distinct entrepreneurship entry modes in terms of their founders" profiles, their survival rates and survival determinants. Moreover, this study contributes to the literature on top management hiring in family firms: it establishes family firm- non-economic goals as another factor that impacts the family firm- hiring decision between a family and a nonfamily manager.

Revue as a Liminal Theatre Genre (2019)

Yamanashi, Makiko

This thesis discusses revue as a significantly inter-cultural genre in the history of global theatre. During the ‘modernisation’ period in Europe, America and Japan, most major urban cities experienced a boom in revue venues and performances. Few studies about revue have yet been done in theatre studies or in urban cultural studies. My thesis will attempt to reevaluate and redefine revue as a highly intercultural theatre genre by using the concept of liminality. In other words, the aim is to examine revue as a genre built on ‘modern composition of betweenness’, bridging seemingly opposing elements, such as the foreign and the domestic, the classic and the innovative, the traditional and the modern, the professional and the amateur, high and low culture, and the feminine and the masculine. The goal is to regard revue as a liminal genre constructed amidst the negotiations between these binaries, existing in a state of constant flux. The purpose of this approach is to capture revue as a transitory phenomena in five dimensions: conceptual, spatial, temporal, categorical and physical. Over the course of six chapters, this inter-disciplinary discussion will reveal the reasons why and the ways by which revue came to establish its prominent position in the Japanese theatre industry. The whole structure is also an attempt to provide plausible ways to apply sociological considerations to theatre studies.

Some Preconditioners in Optimization with Partial Differential Equations (2013)

Ye, Xuancan

Krylov subspace methods are often used to solve large-scale linear equations arising from optimization problems involving partial differential equations (PDEs). Appropriate preconditioning is vital for designing efficient iterative solvers of this type. This research consists of two parts. In the first part, we compare two different kinds of preconditioners for a conjugate gradient (CG) solver attacking one partial integro-differential equation (PIDE) in finance, both theoretically and numerically. An analysis on mesh independence and rate of convergence of the CG solver is included. The knowledge of preconditioning the PIDE is applied to a relevant optimization problem. The second part aims at developing a new preconditioning technique by embedding reduced order models of nonlinear PDEs, which are generated by proper orthogonal decomposition (POD), into deflated Krylov subspace algorithms in solving corresponding optimization problems. Numerical results are reported for a series of test problems.

Do Personality Traits, Trust and Fairness Shape the Stock-Investing Decisions of an Individual? (2023)

Yousefi Amin, Masoud

This thesis is comprised of three projects, all of which are fundamentally connected to the choices that individuals make about stock investments. Differences in stock market participation (SMP) across countries are large and difficult to explain. The second chapter focuses on differences between Germany (low SMP) and East Asian countries (mostly high SMP). The study hypothesis is that cultural differences regarding social preferences and attitudes towards inequality lead to different attitudes towards stock markets and subsequently to different SMPs. Using a large-scale survey, it is found that these factors can, indeed, explain a substantial amount of the country differences that other known factors (financial literacy, risk preferences, etc.) could not. This suggests that social preferences should be given a more central role in programs that aim to enhance SMP in countries like Germany. The third chapter documented the importance of trust as well as herding for stock ownership decisions. The findings show that trust as a general concept has no significant contribution to stock investment intention. A thorough examination of general trust elements reveals that in group and out-group trust have an impact on individual stock market investment. Higher out group trust directly influences a person's decision to invest in stocks, whereas higher in-group trust increases herding attitudes in stock investment decisions and thus can potentially increase the likelihood of stock investments as well. The last chapter investigates the significance of personality traits in stock investing and home bias in portfolio selection. Findings show that personality traits do indeed have a significant impact on stock investment and portfolio allocation decisions. Despite the fact that the magnitude and significance of characteristics differ between two groups of investors, inexperienced and experienced, conscientiousness and neuroticism play an important role in stock investments and preferences. Moreover, high conscientiousness scores increase stock investment desire and portfolio allocation to risky assets like stocks, discouraging home bias in asset allocation. Regarding neuroticism, a higher-level increases home bias in portfolio selection and decreases willingness to stock investment and portfolio share. Finally, when an investor has no prior experience with portfolio selection, patriotism generates home bias. For experienced investors, having a low neuroticism score and a high conscientiousness and openness score seemed to be a constant factor in deciding to invest in a well-diversified international portfolio

Determining the Structure of Diversification (2015)

Yuan, Shuonan

The classic Capital Asset Pricing Model and the portfolio theory suggest that investors hold the market portfolio to diversify idiosyncratic risks. The theory predicts that expected return of assets is positive and that reacts linearly on the overall market. However, in reality, we observe that investors often do not have perfectly diversified portfolios. Empirical studies find that new factors influence the deviation from the theoretical optimal investment. In the first part of this work (Chapter 2) we study such an example, namely the influence of maximum daily returns on subsequent returns. Here we follow ideas of Bali et al. (2011). The goal is to find cross-sectional relations between extremely positive returns and expected average returns. We take account a larger number of markets worldwide. Bali et al. (2011) report with respect to the U.S. market a robust negative relation between MAX (the maximum daily return) and the expected return in the subsequent time. We extent substantially their database to a number of other countries, and also take more recent data into account (until end of 2009). From that we conclude that the relation between MAX and expected returns is not consistent in all countries. Moreover, we test the robustness of the results of Bali et al. (2011) in two time-periods using the same data from CRSP. The results show that the effect of extremely positive returns is not stable over time. Indeed we find a negative cross-sectional relation between the extremely positive returns and the average returns for the first half of the time series, however, we do not find significant effects for the second half. The main results of this chapter serve as a basis for an unpublished working paper Yuan and Rieger (2014b). While in Chapter 2 we have studied factors that prevent optimal diversification, we consider in Chapter 3 and 4 situations where the optimal structure of diversification was previously unknown, namely diversification of options (or structured financial products). Financial derivatives are important additional investment form with respect to diversification. Not only common call and put options, but also structured products enable investors to pursue a multitude of investment strategies to improve the risk-return profile. Since derivatives become more and more important, diversification of portfolios with dimension of derivatives is of particularly practical relevance. We investigate the optimal diversification strategies in connection with underlying stocks for classical rational investors with constant relative risk aversion (CRRA). In particular, we apply Monte Carlo method based on the Black-Scholes model and the Heston model for stochastic volatility to model the stock market processes and the pricing of the derivatives. Afterwards, we compare the benchmark portfolio which consists of derivatives on single assets with derivatives on the index of these assets. First we compute the utility improvement of an investment in the risk-free assets and plain-vanilla options for CRRA investors in various scenarios. Furthermore, we extend our analysis to several kinds of structured products, in particular capital protected notes (CPNs), discount certificates (DCs) and bonus certificates (BCs). We find that the decision of an investor between these two diversification strategies leads to remarkable differences. The difference in the utility improvement is influenced by risk-preferences of investors, stock prices and the properties of the derivatives in the portfolio. The results will be presented in Chapter 3 and are the basis for a yet unpublished working paper Yuan and Rieger (2014a). To check furthermore whether underlyings of structured products influence decisions of investors, we discuss explicitly the utility gain of a stock-based product and an index-based product for an investor whose preferences are described by cumulative prospect theory (CPT) (Chapter 4, compare to Yuan (2014)). The goal is that to investigate the dependence of structured products on their underlying where we put emphasis on the difference between index-products and single-stock-products, in particular with respect to loss-aversion and mental accounting. We consider capital protected notes and discount certificates as examples, and model the stock prices and the index of these stocks via Monte Carlo simulations in the Black-Scholes framework. The results point out that market conditions, particularly the expected returns and volatility of the stocks play a crucial role in determining the preferences of investors for stock-based CPNs and index-based CPNs. A median CPT investor prefers the index-based CPNs if the expected return is higher and the volatility is lower, while he prefers the stock-based CPNs in the other situation. We also show that index-based DCs are robustly more attractive as compared to stock-based DCs for CPT investors.

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