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In the last years, much effort went into the design of robust anaphor resolution algorithms. Many algorithms are based on antecedent filtering and preference strategies that are manually designed. Along a different line of research, corpus-based approaches have been investigated that employ machine-learning techniques for deriving strategies automatically. Since the knowledge-engineering effort for designing and optimizing the strategies is reduced, the latter approaches are considered particularly attractive. Since, however, the hand-coding of robust antecedent filtering strategies such as syntactic disjoint reference and agreement in person, number, and gender constitutes a once-for-all effort, the question arises whether at all they should be derived automatically. In this paper, it is investigated what might be gained by combining the best of two worlds: designing the universally valid antecedent filtering strategies manually, in a once-for-all fashion, and deriving the (potentially genre-specific) antecedent selection strategies automatically by applying machine-learning techniques. An anaphor resolution system ROSANA-ML, which follows this paradigm, is designed and implemented. Through a series of formal evaluations, it is shown that, while exhibiting additional advantages, ROSANAML reaches a performance level that compares with the performance of its manually designed ancestor ROSANA.
We consider Schwarz maps for triangles whose angles are rather general rational multiples of pi. Under which conditions can they have algebraic values at algebraic arguments? The answer is based mainly on considerations of complex multiplication of certain Prym varieties in Jacobians of hypergeometric curves. The paper can serve as an introduction to transcendence techniques for hypergeometric functions, but contains also new results and examples.
As a sign of ambivalence in the regulatory definition of capital adequacy for credit risk and the quest for more efficient refinancing sources collateral loan obligations (CLOs) have become a prominent securitisation mechanism. This paper presents a loss-based asset pricing model for the valuation of constituent tranches within a CLO-style security design. The model specifically examines how tranche subordination translates securitised credit risk into investment risk of issued tranches as beneficial interests on a designated loan pool typically underlying a CLO transaction. We obtain a tranchespecific term structure from an intensity-based simulation of defaults under both robust statistical analysis and extreme value theory (EVT). Loss sharing between issuers and investors according to a simplified subordination mechanism allows issuers to decompose securitised credit risk exposures into a collection of default sensitive debt securities with divergent risk profiles and expected investor returns. Our estimation results suggest a dichotomous effect of loss cascading, with the default term structure of the most junior tranche of CLO transactions (“first loss position”) being distinctly different from that of the remaining, more senior “investor tranches”. The first loss position carries large expected loss (with high investor return) and low leverage, whereas all other tranches mainly suffer from loss volatility (unexpected loss). These findings might explain why issuers retain the most junior tranche as credit enhancement to attenuate asymmetric information between issuers and investors. At the same time, the issuer discretion in the configuration of loss subordination within particular security design might give rise to implicit investment risk in senior tranches in the event of systemic shocks. JEL Classifications: C15, C22, D82, F34, G13, G18, G20
Asset securitisation as a risk management and funding tool : what does it hold in store for SMES?
(2005)
The following chapter critically surveys the attendant benefits and drawbacks of asset securitisation on both financial institutions and firms. It also elicits salient lessons to be learned about the securitisation of SME-related obligations from a cursory review of SME securitisation in Germany as a foray of asset securitisation in a bank-centred financial system paired with a strong presence of SMEs in industrial production. JEL Classification: D81, G15, M20
In this paper, I examine the potential of mobile alerting services empowering investors to react quickly to critical market events. Therefore, an analysis of short-term (intraday) price effects is performed. I find abnormal returns to company announcements which are completed within a timeframe of minutes. To make use of these findings, these price effects are predicted using pre-defined external metrics and different estimation methodologies. Compared to previous research, the results provide support that artificial neural networks and multiple linear regression are good estimation models for forecasting price effects also on an intraday basis. As most of the price effect magnitude and effect delay can be estimated correctly, it is demonstrated how a suitable mobile alerting service combining a low level of user-intrusiveness and timely information supply can be designed.
The current study was part of a series of environment related studies of the Jabal Akhdar sponsored by the Sultan Qaboos University, Al Khoud, Sultanate of Oman. The present study aimed to establish the range, habitat, status and population of breeding species in the area, review the historical perspective and list migrant and visitor species noted during the survey.
We propose a new framework for modelling the time dependence in duration processes being in force on financial markets. The pioneering ACD model introduced by Engle and Russell (1998) will be extended in a manner that the duration process will be accompanied by an unobservable stochastic process. The Discrete Mixture ACD framework provides us with a general methodology which puts the idea into practice. It is established by introducing a discrete-valued latent regime variable which can be justified in the light of recent market microstructure theories. The empirical application demonstrates its ability to capture specific characteristics of intraday transaction durations while alternative approaches fail. JEL classification: C41, C22, C25, C51, G14.
When one considers the results of social scientific surveys, secularisation in Germany seems to be a more or less linear process of erosion of what is traditionally named religiosity. The percentage of citizens who affirm that they are “religious”, believe in God or otherworldly beings, hope for life after death or participate regularly in the praxis of a religious community has been – by and large – steadily declining for decades. This decline has occurred over the succeeding generations: The younger the generation, the fewer “religious” people in it. But the process of secularisation is apparent not only in this persistent quantitative shrinkage from generation to generation. Above all it also manifests itself – this is the thesis of the article – in the transformation of the habitus formations and contents of faith of the generations. The essence of ongoing secularisation naturally is reflected most clearly in its contemporary state of development which is represented in the youngest adult generation. Therefore the analysis of this generation is particularly interesting for the sociology of religion. But the article does not confine to analyze this generation. After indicating some basic premises of the sociology of generations and the notion of secularisation presupposed in this paper, the succession of generations in Germany is outlined hypothetically, from the so-called generation of ´68 to the youngest adult generation, concluding with some remarks about the progress of secularisation.