Contributions in Merlin

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In complex natural environments, auditory and visual information often have to be processed simultaneously. Previous functional magnetic resonance imaging (fMRI) studies focused on the spatial localization of brain areas involved in audiovisual (AV) information processing, but the temporal characteristics of AV information flow in these regions remained unclear. In this study, we used fMRI and a novel information-theoretic approach to study the flow of AV sensory information. Subjects passively perceived sounds and images of objects presented either alone or simultaneously. Applying the measure of mutual information, we computed for each voxel the latency in which the blood oxygenation level-dependent signal had the highest information content about the preceding stimulus. The results indicate that, after AV stimulation, the earliest informative activity occurs in right Heschl's gyrus, left primary visual cortex, and the posterior portion of the superior temporal gyrus, which is known as a region involved in object-related AV integration. Informative activity in the anterior portion of superior temporal gyrus, middle temporal gyrus, right occipital cortex, and inferior frontal cortex was found at a later latency. Moreover, AV presentation resulted in shorter latencies in multiple cortical areas compared with isolated auditory or visual presentation. The results provide evidence for bottom-up processing from primary sensory areas into higher association areas during AV integration in humans and suggest that AV presentation shortens processing time in early sensory cortices.

Over the years, the software engineering community has developed various tools to support the specification, development, and maintainance of software. Many of these tools use proprietary data formats to store artifacts which hamper interoperability. However, the Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. Ontologies are used define the concepts in the domain of discourse and their relationships and as such provide the formal vocabulary applications use to exchange data. Beside the Web, the technologies developed for the Semantic Web have proven to be useful also in other domains, especially when data is exchanged between applications from different parties. Software engineering is one of these domains in which recent research shows that Semantic Web technologies are able to reduce the barriers of proprietary data formats and enable interoperability. In this tutorial, we present Semantic Web technologies and their application in software engineering. We discuss the current status of ontologies for software entities, bug reports, or change requests, as well as semantic representations for software and its documentation. This way, architecture, design, code, or test models can be shared across application boundaries enabling a seamless integration of engineering results.

Graphical models are omnipresent in the software engineering field, but most current graphical modeling languages do not scale with the increasing size and complexity of today’s systems. The navigation in the diagrams becomes a major problem especially if different aspects of the system are scattered over multiple, only loosely coupled diagrams. In this paper we present the hierarchical navigation capabilities of the Adora modeling tool. The user of this tool can freely control the level of detail in different parts of the model to reduce the size and complexity of the diagrams being displayed. Our fisheye visualization technique makes it possible to integrate all modeling aspects (structure, data, behavior, etc.) in one coherent model while keeping the size and complexity of the diagrams within reasonable limits.

Futures contracts on the New York Mercantile Exchange are the most liquid instruments for trading crude oil, which is the world’s most actively traded physical commodity. Under normal market conditions, traders can easily find counterparties for their trades, resulting in an efficient market with virtually no return predictability. Yet even this extremely liquid instrument suffers from liquidity shocks that induce periods of increased volatility and significant return predictability. This paper identifies an important and recurring cause of these shocks: the accumulation of extreme and opposing positions by the two main trader classes in the market, namely hedgers and speculators. As positions become extreme, approaching their historical limits, counterparties for trades become scarce and prices must adjust to induce trade. These liquidity-induced price adjustments are found to be driven by systematic speculative behavior and are determined to be significant.

We analyze how directors with financial expertise affect corporate decisions. Using a novel panel data set, we find that financial experts exert significant influence, though not necessarily in the interest of shareholders. When commercial bankers join boards, external funding increases and investment-cash flow sensitivity decreases. However, the increased financing flows to firms with good credit but poor investment opportunities. Similarly, investment bankers on boards are associated with larger bond issues but worse acquisitions. We find little evidence that financial experts affect compensation policy. The results suggest that increasing financial expertise on boards may not benefit shareholders if conflicting interests (e.g., bank profits) are neglected.

We propose a new method for pricing options based on GARCH models with filtered historical innovations. In an incomplete market framework, we allow for different distributions of historical and pricing return dynamics, which enhances the model's flexibility to fit market option prices. An extensive empirical analysis based on S&P 500 index options shows that our model outperforms other competing GARCH pricing models and ad hoc Black-Scholes models. We show that the flexible change of measure, the asymmetric GARCH volatility, and the nonparametric innovation distribution induce the accurate pricing performance of our model. Using a nonparametric approach, we obtain decreasing state-price densities per unit probability as suggested by economic theory and corroborating our GARCH pricing model. Implied volatility smiles appear to be explained by asymmetric volatility and negative skewness of filtered historical innovations.