7,730 research outputs found

    Information asymmetries and securitization design

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    The strong growth in collateralized debt obligation transactions raises the question how these transactions are designed. The originator designs the transaction so as to maximize her benefit subject to requirements imposed by investors and rating agencies. An important issue in these transactions is the information asymmetry between the originator and the investors. First Loss Positions are the most important instrument to mitigate conflicts due to information asymmetry. We analyse the optimal size of the First Loss Position in a model and the actual size in a set of European collateralized debt obligation transactions. We find that the asset pool quality, measured by the weighted average default probability and the diversity score of the pool, plays a predominant role for the transaction design. Characteristics of the originator play a small role. A lower asset pool quality induces the originator to take a higher First Loss Position and, in a synthetic transaction, a smaller Third Loss Position. The First Loss Position bears on average 86 % of the expected default losses, independent of the asset pool quality. This loss share and the asset pool quality strongly affect the rating and the credit spread of the lowest rated tranche.Securitization, collateralized debt obligations, asset pool quality, First Loss Position, synthetic transactions, tranching

    Minimum Race-Time Planning-Strategy for an Autonomous Electric Racecar

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    Increasing attention to autonomous passenger vehicles has also attracted interest in an autonomous racing series. Because of this, platforms such as Roborace and the Indy Autonomous Challenge are currently evolving. Electric racecars face the challenge of a limited amount of stored energy within their batteries. Furthermore, the thermodynamical influence of an all-electric powertrain on the race performance is crucial. Severe damage can occur to the powertrain components when thermally overstressed. In this work we present a race-time minimal control strategy deduced from an Optimal Control Problem (OCP) that is transcribed into a Nonlinear Problem (NLP). Its optimization variables stem from the driving dynamics as well as from a thermodynamical description of the electric powertrain. We deduce the necessary first-order Ordinary Differential Equations (ODE)s and form simplified loss models for the implementation within the numerical optimization. The significant influence of the powertrain behavior on the race strategy is shown.Comment: Accepted at The 23rd IEEE International Conference on Intelligent Transportation Systems, September 20 - 23, 202

    Subdivision Shell Elements with Anisotropic Growth

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    A thin shell finite element approach based on Loop's subdivision surfaces is proposed, capable of dealing with large deformations and anisotropic growth. To this end, the Kirchhoff-Love theory of thin shells is derived and extended to allow for arbitrary in-plane growth. The simplicity and computational efficiency of the subdivision thin shell elements is outstanding, which is demonstrated on a few standard loading benchmarks. With this powerful tool at hand, we demonstrate the broad range of possible applications by numerical solution of several growth scenarios, ranging from the uniform growth of a sphere, to boundary instabilities induced by large anisotropic growth. Finally, it is shown that the problem of a slowly and uniformly growing sheet confined in a fixed hollow sphere is equivalent to the inverse process where a sheet of fixed size is slowly crumpled in a shrinking hollow sphere in the frictionless, quasi-static, elastic limit.Comment: 20 pages, 12 figures, 1 tabl

    Analytical model for flux saturation in sediment transport

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    The transport of sediment by a fluid along the surface is responsible for dune formation, dust entrainment and for a rich diversity of patterns on the bottom of oceans, rivers, and planetary surfaces. Most previous models of sediment transport have focused on the equilibrium (or saturated) particle flux. However, the morphodynamics of sediment landscapes emerging due to surface transport of sediment is controlled by situations out-of-equilibrium. In particular, it is controlled by the saturation length characterizing the distance it takes for the particle flux to reach a new equilibrium after a change in flow conditions. The saturation of mass density of particles entrained into transport and the relaxation of particle and fluid velocities constitute the main relevant relaxation mechanisms leading to saturation of the sediment flux. Here we present a theoretical model for sediment transport which, for the first time, accounts for both these relaxation mechanisms and for the different types of sediment entrainment prevailing under different environmental conditions. Our analytical treatment allows us to derive a closed expression for the saturation length of sediment flux, which is general and can thus be applied under different physical conditions

    Data Elicitation for Continuous Awareness of Team Climate Characteristics to Improve Organizations’ Creativity

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    The creativeness of a company’s employees depends on the characteristics of working climates, e.g. au-tonomy or appropriate workload. Tools for their assessment exist, but the frequency of their applica-tion is too low to detect the relevant dynamics which characterize the varying challenges of agile and learning organizations. The evaluation of a first prototype to monitor these dynamics by frequently repeating a common online employee survey re-vealed relevant features to overcome a lack of ac-ceptance of answering the same question items in repetition. \ \ Three variables were identified which influence the acceptance of a repeated question: The time since it had last been answered, the user’s current willing-ness to participate and the user’s situation. Based on these variables, a new prototype offers users more self-determination in their rate of participation, allows for assigning dynamic repetition rates to every question item, and exploits context infor-mation to optimize the prompting of users.
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