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Time-resolved pump-probe action spectroscopy on isolated organic dyes and supramolecular photocatalysts (2017)

Dimitri Imanbaew

Continuous-Time Portfolio Optimization under Partial Information and Convex Constraints: Deriving Explicit Results (2017)

Christian Vonwirth

In this thesis we explicitly solve several portfolio optimization problems in a very realistic setting. The fundamental assumptions on the market setting are motivated by practical experience and the resulting optimal strategies are challenged in numerical simulations. We consider an investor who wants to maximize expected utility of terminal wealth by trading in a high-dimensional financial market with one riskless asset and several stocks. The stock returns are driven by a Brownian motion and their drift is modelled by a Gaussian random variable. We consider a partial information setting, where the drift is unknown to the investor and has to be estimated from the observable stock prices in addition to some analyst’s opinion as proposed in [CLMZ06]. The best estimate given these observations is the well known Kalman-Bucy-Filter. We then consider an innovations process to transform the partial information setting into a market with complete information and an observable Gaussian drift process. The investor is restricted to portfolio strategies satisfying several convex constraints. These constraints can be due to legal restrictions, due to fund design or due to client's specifications. We cover in particular no-short-selling and no-borrowing constraints. One popular approach to constrained portfolio optimization is the convex duality approach of Cvitanic and Karatzas. In [CK92] they introduce auxiliary stock markets with shifted market parameters and obtain a dual problem to the original portfolio optimization problem that can be better solvable than the primal problem. Hence we consider this duality approach and using stochastic control methods we first solve the dual problems in the cases of logarithmic and power utility. Here we apply a reverse separation approach in order to obtain areas where the corresponding Hamilton-Jacobi-Bellman differential equation can be solved. It turns out that these areas have a straightforward interpretation in terms of the resulting portfolio strategy. The areas differ between active and passive stocks, where active stocks are invested in, while passive stocks are not. Afterwards we solve the auxiliary market given the optimal dual processes in a more general setting, allowing for various market settings and various dual processes. We obtain explicit analytical formulas for the optimal portfolio policies and provide an algorithm that determines the correct formula for the optimal strategy in any case. We also show optimality of our resulting portfolio strategies in different verification theorems. Subsequently we challenge our theoretical results in a historical and an artificial simulation that are even closer to the real world market than the setting we used to derive our theoretical results. However, we still obtain compelling results indicating that our optimal strategies can outperform any benchmark in a real market in general.

Measuring Accountability in Nonprofit Organizations: The Impact of Nonprofit Governance on Accountability (2017)

Sophie Mentges Elena Klug

As there is a rising interest in accountability issues and governance in nonprofit organizations, this work aims to give some notions on the context of these two topics. Hence, within this work, a theoretical framework is developed, whereby the correlation of accountability and governance in nonprofit organizations shall be measured. This framework suggests, that in nonprofit organizations, nonprofit governance, represented by board members and professionals, has an influence on compliance, as a component of accountability. In respect to the board members, it is supposed that, board competence, transparency, stakeholder relationship and (public) trust are positively related to compliance. Furthermore, it is assumed, referring to professionals, that the variables performance, training or development and satisfaction are positively and empowerment is negatively correlated with compliance. These assumptions are based on a thorough theoretical literature research. Furthermore, a questionnaire is designed to measure the correlations. This questionnaire will be amplified in a discussion following to the explanation of the research model. Concluding, some limitations on the research model are given, which should be taken into account by undertaking the questionnaire.

Complete Functional Verification (2009)

Joerg Bormann

The dissertation describes a practically proven, particularly efficient approach for the verification of digital circuit designs. The approach outperforms simulation based verification wrt. final circuit quality as well as wrt. required verification effort. In the dissertation, the paradigm of transaction based verification is ported from simulation to formal verification. One consequence is a particular format of formal properties, called operation properties. Circuit descriptions are verified by proof of operation properties with Interval Property Checking (IPC), a particularly strong SAT based formal verification algorithm. Furtheron, a completeness checker is presented that identifies all verification gaps in sets of operation properties. This completeness checker can handle the large operation properties that arise, if this approach is applied to realistic circuits. The methodology of operation properties, Interval Property Checking, and the completeness checker form a symbiosis that is of particular benefit to the verification of digital circuit designs. On top of this symbiosis an approach to completely verify the interaction of completely verified modules has been developed by adaptation of the modelling theories of digital systems. The approach presented in the dissertation has proven in multiple commercial application projects that it indeed completely verifies modules. After reaching a termination criterion that is well defined by completeness checking, no further bugs were found in the verified modules. The approach is marketed by OneSpin Solutions GmbH, Munich, under the names "Operation Based Verification" and "Gap Free Verification".

The Split tree for option pricing (2017)

Merima Nurkanović

In this dissertation convergence of binomial trees for option pricing is investigated. The focus is on American and European put and call options. For that purpose variations of the binomial tree model are reviewed. In the first part of the thesis we investigated the convergence behavior of the already known trees from the literature (CRR, RB, Tian and CP) for the European options. The CRR and the RB tree suffer from irregular convergence, so our first aim is to find a way to get the smooth convergence. We first show what causes these oscillations. That will also help us to improve the rate of convergence. As a result we introduce the Tian and the CP tree and we proved that the order of convergence for these trees is \(O \left(\frac{1}{n} \right)\). Afterwards we introduce the Split tree and explain its properties. We prove the convergence of it and we found an explicit first order error formula. In our setting, the splitting time \(t_{k} = k\Delta t\) is not fixed, i.e. it can be any time between 0 and the maturity time \(T\). This is the main difference compared to the model from the literature. Namely, we show that the good properties of the CRR tree when \(S_{0} = K\) can be preserved even without this condition (which is mainly the case). We achieved the convergence of \(O \left(n^{-\frac{3}{2}} \right)\) and we typically get better results if we split our tree later.

Mathematical modelling of interacting fibre structures and non-woven materials (2017)

Christian Nessler

Non–woven materials consist of many thousands of fibres laid down on a conveyor belt under the influence of a turbulent air stream. To improve industrial processes for the production of non–woven materials, we develop and explore novel mathematical fibre and material models. In Part I of this thesis we improve existing mathematical models describing the fibres on the belt in the meltspinning process. In contrast to existing models, we include the fibre–fibre interaction caused by the fibres’ thickness which prevents the intersection of the fibres and, hence, results in a more accurate mathematical description. We start from a microscopic characterisation, where each fibre is described by a stochastic functional differential equation and include the interaction along the whole fibre path, which is described by a delay term. As many fibres are required for the production of a non–woven material, we consider the corresponding mean–field equation, which describes the evolution of the fibre distribution with respect to fibre position and orientation. To analyse the particular case of large turbulences in the air stream, we develop the diffusion approximation which yields a distribution describing the fibre position. Considering the convergence to equilibrium on an analytical level, as well as performing numerical experiments, gives an insight into the influence of the novel interaction term in the equations. In Part II of this thesis we model the industrial airlay process, which is a production method whereby many short fibres build a three–dimensional non–woven material. We focus on the development of a material model based on original fibre properties, machine data and micro computer tomography. A possible linking of these models to other simulation tools, for example virtual tensile tests, is discussed. The models and methods presented in this thesis promise to further the field in mathematical modelling and computational simulation of non–woven materials.

A measurement method for characterising micro lead on ground shaft surfaces (2017)

Philipp Arnecke

The detection and characterisation of undesired lead structures on shaft surfaces is a concern in production and quality control of rotary shaft lip-type sealing systems. The potential lead structures are generally divided into macro and micro lead based on their characteristics and formation. Macro lead measurement methods exist and are widely applied. This work describes a method to characterise micro lead on ground shaft surfaces. Micro lead is known as the deviation of main orientation of the ground micro texture from circumferential direction. Assessing the orientation of microscopic structures with arc minute accuracy with regard to circumferential direction requires exact knowledge of both the shaft’s orientation and the direction of surface texture. The shaft’s circumferential direction is found by calibration. Measuring systems and calibration procedures capable of calibrating shaft axis orientation with high accuracy and low uncertainty are described. The measuring systems employ areal-topographic measuring instruments suited for evaluating texture orientation. A dedicated evaluation scheme for texture orientation is based on the Radon transform of these topographies and parametrised for the application. Combining the calibration of circumferential direction with the evaluation of texture orientation the method enables the measurement of micro lead on ground shaft surfaces.

Product Pricing with Additive Influences - Algorithms and Complexity Results for Pricing in Social Networks (2017)

Florian David Schwahn

We introduce and investigate a product pricing model in social networks where the value a possible buyer assigns to a product is influenced by the previous buyers. The selling proceeds in discrete, synchronous rounds for some set price and the individual values are additively altered. Whereas computing the revenue for a given price can be done in polynomial time, we show that the basic problem PPAI, i.e., is there a price generating a requested revenue, is weakly NP-complete. With algorithm Frag we provide a pseudo-polynomial time algorithm checking the range of prices in intervals of common buying behavior we call fragments. In some special cases, e.g., solely positive influences, graphs with bounded in-degree, or graphs with bounded path length, the amount of fragments is polynomial. Since the run-time of Frag is polynomial in the amount of fragments, the algorithm itself is polynomial for these special cases. For graphs with positive influence we show that every buyer does also buy for lower prices, a property that is not inherent for arbitrary graphs. Algorithm FixHighest improves the run-time on these graphs by using the above property. Furthermore, we introduce variations on this basic model. The version of delaying the propagation of influences and the awareness of the product can be implemented in our basic model by substituting nodes and arcs with simple gadgets. In the chapter on Dynamic Product Pricing we allow price changes, thereby raising the complexity even for graphs with solely positive or negative influences. Concerning Perishable Product Pricing, i.e., the selling of products that are usable for some time and can be rebought afterward, the principal problem is computing the revenue that a given price can generate in some time horizon. In general, the problem is #P-hard and algorithm Break runs in pseudo-polynomial time. For polynomially computable revenue, we investigate once more the complexity to find the best price. We conclude the thesis with short results in topics of Cooperative Pricing, Initial Value as Parameter, Two Product Pricing, and Bounded Additive Influence.

An Integer Network Flow Problem with Bridge Capacities (2017)

Horst W. Hamacher Anika Kinscherff

In this paper a modified version of dynamic network ows is discussed. Whereas dynamic network flows are widely analyzed already, we consider a dynamic flow problem with aggregate arc capacities called Bridge Problem which was introduced by Melkonian [Mel07]. We extend his research to integer flows and show that this problem is strongly NP-hard. For practical relevance we also introduce and analyze the hybrid bridge problem, i.e. with underlying networks whose arc capacity can limit aggregate flow (bridge problem) or the flow entering an arc at each time (general dynamic flow). For this kind of problem we present efficient procedures for special cases that run in polynomial time. Moreover, we present a heuristic for general hybrid graphs with restriction on the number of bridge arcs. Computational experiments show that the heuristic works well, both on random graphs and on graphs modeling also on realistic scenarios.

Characterization of Structures, Fragmentation Pathways and Magnetism of Mononuclear and Oligonuclear Transition Metal Complexes in Isolation (2017)

Johannes Lang

This thesis comprises several independent research studies on transition metal complexes as trapped ions in isolation. Electrospray Ionization (ESI) serves to transfer ions from solution into the gas phase for mass spectrometric investigations. Subsequently, a variety of experimental and theoretical methods provide fundamental insights into molecular properties of the isolated complexes: InfraRed (Multiple) Photon Dissociation (IR-(M)PD) spectroscopy provides information on binding motifs and molecular structures at cryo temperatures as well as at room temperature. Collision Induced Dissociation (CID) serves to elucidate molecular fragmentation pathways as well as relative stabilities of the complexes at room temperature. Quantum chemical calculations via Density Functional Theory (DFT) substantiate the experimental results and deepen the fundamental insights into the molecular properties of the complexes. Magnetic couplings between metal centers in oligonuclear complexes are investigated by Broken Symmetry DFT modelling and X Ray Magnetic Circular Dichroism (XMCD) spectroscopy.

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