12 search hits
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Temporal information gaps and market efficiency: a dynamic behavioural analysis
(2009)
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Björn-Christopher Witte
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Locational Price Spreads and the Pricing of Contracts for Difference: Evidence from the Nordic Market
(2009)
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Jan Marckhoff
Jens Wimschulte
- In electricity markets, not only does the risk of substantial price variations over time exist, but so does the risk of price variations over space, as prices between locations can differ due to transmission congestion. To manage this risk, Contracts for Difference (CfDs), i.e., forwards on the spread between a particular area price and the (unconstrained) system price, were introduced at the Scandinavian electricity exchange Nord Pool at the end of 2000. We empirically investigate the pricing of these CfDs over the period 2001 through 2006 and find that CfD prices contain significant risk premia. Their sign and magnitude, however, differ substantially between areas and delivery periods, because areas are subject to transmission congestion to a varying extent. While the relation between risk premia and time-to-maturity is not uniform for CfDs, there is a negative relation for implied area and system forwards, which can be explained by the relative hedging demand of market participants. In addition, we find that risk premia of CfDs and implied area forwards vary systematically with the variance and skewness of the underlying spot prices. This confirms both implications of the Bessembinder and Lemmon [Bessembinder, H., Lemmon, M.L., 2002. Equilibrium pricing and optimal hedging in electricity forward markets. Journal of Finance, 57, 1347–1382] model.
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The interplay of theory and observation: a proposition for structured research on human behavior on the web
(2009)
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Pascal Jürgens
Andreas Jungherr
Benjamin Heitmann
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A Requirements Analysis of Business-To-Business Integration
(2009)
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Andreas Schönberger
Christian Wilms
Guido Wirtz
- Ever fiercer competition has forced enterprises not only to optimize their own operations but also to cooperate with their suppliers and customers along their supply chains. Thus, competition today usually takes place between supply chains and not between individual enterprises. Business-To-Business integration (B2Bi) is a major task of supply chain management (SCM), and although it already has been researched for years, B2Bi is still an area of active research with a plethora of research questions and according approaches. Hence, management of B2Bi projects necessitates the identification of relevant requirements which is a far from trivial task. This paper identifies a core set of B2Bi challenges and deduces a comprehensive set of B2Bi requirements that are particularly useful for tackling the challenges identified. The derivation of B2Bi requirements follows an inductive approach that is based on the analysis of integration standards, reference architectures and related literature. In order to operationalize the B2Bi requirements for further analysis and concrete B2Bi projects, the requirements are classified according to the abstraction layers of a B2Bi schema. Thus, this report not only offers a requirements check list for B2Bi projects but also helps in deciding when to address which requirements during the course of a B2Bi project.
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Analysis of Incomplete Survey Data - Multiple Imputation via Bayesian Bootstrap Predictive Mean Matching
(2009)
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Florian Koller-Meinfelder
- Multiple Imputation (MI) is a general purpose approach to impute partially incomplete data. The proposed method - Bayesian Bootstrap Predictive Mean Matching - is a variant that incorporates the robustifying properties of a nearest neighbour technique (Predictive Mean Matching) into MI.
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The Bible in Context. Essay Collection
(2009)
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Lovemore Togarasei
- This volume opens the series BiAS. Bible in Context is a collection of 9 essays discussing how biblical texts are read and interpreted in different contexts. The book discusses such contexts as Bible translation, HIV and AIDS, urban feminist Christology, denominationalism, conversion in African Christianity, environmental crisis, political conflict, land reform and women dress code. It analyses the ways in which context determines the reading processes and interpretations given to specific biblical texts. The book basically demonstrates that biblical interpretation is influenced by the contexts of the readers and the interpreters.
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Proceedings of the KI 2009 Workshop on Complex Cognition
(2009)
- The KI ´09 workshop on Complex Cognition was a joint venture of the Cognition group of the Special Interest Group Artificial Intelligence of the German Computer Science Society (Gesellschaft für Informatik) and the German Cognitive Science Association. Dealing with complexity has become one of the great challenges for modern information societies. To reason and decide, plan and act in complex domains is no longer limited to highly specialized professionals in restricted areas such as medical diagnosis, controlling technical processes, or serious game playing. Complexity has reached everyday life and affects people in such mundane activities as buying a train ticket, investing money, or connecting a home desktop to the internet. Research in cognitive AI can contribute to supporting people navigating through the jungle of everyday reasoning, decision making, planning and acting by providing intelligent support technology. Lessons learned from expert systems research of the nineteen-eighties show that the aim should not be to provide for fully automated systems which can solve specialized tasks autonomously but instead to develop interactive assistant systems where user and system work together by taking advantage of the respective strengths of human and machine. To accomplish a smooth collaboration between humans and intelligent systems, basic research in cognition is a necessary precondition. Insights into cognitive structures and processes underlying successful human reasoning and planning can provide suggestions for algorithm design. Even more important, insights into restrictions and typical errors and misconceptions of the cognitive systems provide information about those parts of a complex task from which the human should be relieved. For successful human-computer interaction in complex domains it has, furthermore, to be decided which information should be presented when, in what way, to the user. We strongly believe that symbolic approaches of AI and psychological research of higher cognition are at the core of success for the endeavor to create intelligent assistant system for complex domains. While insight into the neurological processes of the brain and into the realization of basic processes of perception, attention and senso-motoric coordination are important for the basic understanding of the principles of human intelligence, these processes have a much too fine granularity for the design and realization of interactive systems which must communicate with the user on knowledge level. If human system users are not to be incapacitated by a system, system decisions must be transparent for the user and the system must be able to provide explanations for the reasons of its proposals and recommendations. Therefore, even when some of the underlying algorithms are based on statistical or neuronal approaches, the top-level of such systems must be symbolical and rule-based. The papers presented at this workshop on complex cognition give an inspiring and promising overview of current work in the field which can provide first building stones for our endeavor to create knowledge level intelligent assistant systems for complex domains. The topics cover modelling basic cognitive processes, interfacing subsymbolic and symbolic representations, dealing with continuous time, Bayesian identification of problem solving strategies, linguistically inspired methods for assessing complex cognitive processes and complex domains such as recognition of sketches, predicting changes in stocks, spatial information processing, and coping with critical situations.
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A Realistic Approach for the Autonomic Management of Component-Based Enterprise Systems
(2009)
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Jens Bruhn
- During the last decades, information technology has been characterized by constantly increasing performance of available hardware resources. This development allows the assignment of more and more complex tasks to software systems while at the same time leading to a massive increase of inherent complexity of applied systems. The expected further increase of complexity in the future demands for an explicit addressing of complexity. The concept of Component Orientation represents an approach for complexity reduction during the development and configuration of software through functional decomposition. With the vision of Autonomic Computing there does exist an approach for addressing complexity during the operation and maintenance of software systems. In this context, the approach is based on the idea of assigning low level-management tasks to the managed system itself. The concept of Component Orientation leads to the establishment of system architectures out of clearly distinguishable building blocks. Therefore, Component Orientation seems to provide a promising foundation for realizing the vision of Autonomic Computing. This thesis presents a realistic infrastructure for the autonomic management of component-based enterprise systems. The application area of such systems leads to special requirements for managed systems and is highly affected by the complexity problem. As a foundation for the proposed approach, a well established component standard was chosen to guarantee the practical relevance of applied concepts and techniques. The applied standard is Enterprise JavaBeans, version 3.0. The proposed infrastructure is designed and realized in a generic fashion. It provides a platform upon which solutions for different application areas of Autonomic Computing can be realized. Autonomic entities are supported through a programming interface which represents a system on three interrelated levels and allows its management: On the top-level, the underlying software of a managed system is considered. The middle layer addresses the system architecture. Runtime interactions within the system are represented on the lowest layer. On this foundation, a system can be managed in a holistic, model-based way. The runtime management of a system is enabled through a specially developed component which must be integrated into the affected environment. This component is compliant with the applied component standard and does not require any adjustment of the underlying component platform. Finally, a tool is provided which supports the establishment of manageability through the automated execution of required adjustments of components. The management of a system is realized transparently for its constituent elements during runtime. On the whole, the development of enterprise software is not affected by a potential application of the presented infrastructure.
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Concepts and Evaluation of Psychological Models of Empathy
(2009)
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Sibylle Enz
Carsten Zoll
Martin Diruf
- This paper provides an overview over contemporary empathy research, including concepts and definitions as well as descriptions of empathic processes and outcomes. Based on these theoretical foundations, three different approaches to model empathy are described: a low-level computational approach, an OCC-based approach, and an empathy model inspired by PSI, a general psychological theory of psychic functioning. Ideas on how these models could be implemented in agents are discussed and preliminary efforts to evaluate the plausibility and believability of the empathic processes and outcomes are drafted.
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Proceedings of the ACM SIGPLAN Workshop on Approaches and Applications of Inductive Programming (AAIP 2009)
(2009)
- Inductive programming is concerned with the automated construction of declarative, often functional, recursive programs from incomplete specifications such as input/output examples. The inferred program must be correct with respect to the provided examples in a generalising sense: it should be neither equivalent to them, nor inconsistent. Inductive programming algorithms are guided explicitly or implicitly by a language bias (the class of programs that can be induced) and a search bias (determining which generalised program is constructed first). Induction strategies are either generate-and-test or example-driven. In generate-and-test approaches, hypotheses about candidate programs are generated independently from the given specifications. Program candidates are tested against the given specification and one or more of the best evaluated candidates are developed further. In analytical approaches, candidate programs are constructed in an example-driven way. While generate-and-test approaches can -- in principle -- construct any kind of program, analytical approaches have a more limited scope. On the other hand, efficiency of induction is much higher in analytical approaches. Inductive programming is still mainly a topic of basic research, exploring how the intellectual ability of humans to infer generalised recursive procedures from incomplete evidence can be captured in the form of synthesis methods. Intended applications are mainly in the domain of programming assistance -- either to relieve professional programmers from routine tasks or to enable non-programmers to some limited form of end-user programming. Furthermore, in the future, inductive programming techniques might be applied to further areas such as supporting the inference of lemmata in theorem proving or learning grammar rules. Inductive automated program construction has been originally addressed by researchers in artificial intelligence and machine learning. During the last years, some work on exploiting induction techniques has been started also in the functional programming community. Therefore, the third workshop on |Approaches and Applications of Inductive Programming| took place for the first time in conjunction with the ACM SIGPLAN International Conference on Functional Programming (ICFP 2009). The first and second workshop were associated with the International Conference on Machine Learning (ICML 2005) and the European Conference on Machine Learning (ECML 2007). AAIP´09 aimed to bring together researchers from the functional programming and the artificial intelligence communities, working in the field of inductive functional programming, and advance fruitful interactions between these communities with respect to programming techniques for inductive programming algorithms, the identification of challenge problems and potential applications. For everybody interested in inductive programming we recommend to visit the website: www.inductive-programming.org.