Dirk Neumann

University of Freiburg, Freiburg, Baden-Württemberg, Germany

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Publications (119)16.13 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Speculative bubbles are commonly referred to situations where stock prices considerably deviate from their fundamentals until the bubbles bust. Bursting of bubbles such as the dot-com or U.S. housing bubble is very costly, so there is a need for mechanisms to detect them. In this paper, we attempt to predict when bubbles may bust using the sentiment of news announcements. Accordingly, we first try to understand how news reception evolves depending on the market phase (boom or bust). The probability of bubble bursts are calculated on the basis of a Markov-regime switching model. The approach is applied and validated using the oil market which appears to be one of the most important markets in the globalized world. Our methodology can be similarly extended to other markets such as gold or wheat.
    Proceedings of the 2014 47th Hawaii International Conference on System Sciences; 01/2014
  • Stefan Feuerriegel, Dirk Neumann
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    ABSTRACT: Due to the integration of intermittent resources of power generation such as wind and solar, the amount of supplied electricity will exhibit unprecedented fluctuations. Electricity retailers can partially meet the challenge of matching demand and volatile supply by shifting power demand according to the fluctuating supply side. The necessary technology infrastructure such as Advanced Metering Infrastructures for this so-called Demand Response (DR) has advanced. However, little is known about the economic dimension and further effort is strongly needed to realistically quantify the financial impact. To succeed in this goal, we derive an optimization problem that minimizes procurement costs of an electricity retailer in order to control Demand Response usage. The evaluation with historic data shows that cost volatility can be reduced by 7.74%; peak costs drop by 14.35%; and expenditures of retailers can be significantly decreased by 3.52%.
    Energy Policy. 01/2014; 65:359–368.
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    Felix Wex, Guido Schryen, Dirk Neumann
    International Journal of Information Systems for Crisis Response and Management. 01/2014;
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    ABSTRACT: Natural disasters, such as earthquakes, tsunamis and hurricanes, cause tremendous harm each year. In order to reduce casualties and economic losses during the response phase, rescue units must be allocated and scheduled efficiently. As this problem is one of the key issues in emergency response and has been addressed only rarely in literature, this paper develops a corresponding decision support model that minimizes the sum of completion times of incidents weighted by their severity. The presented problem is a generalization of the parallel-machine scheduling problem with unrelated machines, non-batch sequence-dependent setup times and a weighted sum of completion times – thus, it is NP-hard. Using literature on scheduling and routing, we propose and computationally compare several heuristics, including a Monte Carlo-based heuristic, the joint application of 8 construction heuristics and 5 improvement heuristics, and GRASP metaheuristics. Our results show that problem instances (with up to 40 incidents and 40 rescue units) can be solved in less than a second, with results being at most 10.9% up to 33.9% higher than optimal values. Compared to current best practice solutions, the overall harm can be reduced by up to 81.8%.
    European Journal of Operational Research 01/2014; 235(3):697–708. · 2.04 Impact Factor
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    ABSTRACT: Information Systems play an important role in achieving sustainable solutions for the global economy. In particular, Information Systems are inevitable when it comes to the transition from the "current" to the "smart" power grid. This enables an improved balancing of both electricity supply and demand, by shifting load --- based on the projected supply gap and electricity prices --- on the demand side smartly. As this requires a specific Information System, namely a Demand Response system, we address the challenge of designing such a system by utilizing the design science approach: determining general requirements, deducing the corresponding information requirements, analyzing the information flow, designing a suitable Information System, demonstrating its capability, and, finally, evaluating the design. The design process is reiterated fully until a viable solution, i.e. an IS artifact, has been developed. This paper describes both the design process as such and the final IS artifact. Moreover, we summarize our lessons learnt from using and adopting the design science approach within this practical, bottom-up case study.
    Proceedings of the 8th international conference on Design Science at the Intersection of Physical and Virtual Design; 06/2013
  • F. Wex, N. Widder, M. Liebmann, D. Neumann
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    ABSTRACT: Extreme events (such as natural disasters, political upheaval, economic crises) typically have a strong impact on crude oil markets and related price fluctuations and may eventually emerge to global oil crises. This study attempts to early detect such events based on the predictive power of online news messages. Text mining algorithms are used to turn unstructured news into actionable information and to determine which news can be regarded as relevant for the oil market. Over 45 million news messages have been examined. A decision support system is constructed which uses an indicator metric to set off an alarm based on information gathered from current and historic news stories. Regression analyses statistically attest the predictive power of online news messages and thus demonstrate the potential of the early warning system. The effect on the price of crude oil is statistically significant.
    System Sciences (HICSS), 2013 46th Hawaii International Conference on; 01/2013
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    ABSTRACT: This paper investigates whether news momentum can predict medium-term stock index developments. News momentum can be built by aggregating tone of news over the past weeks. We find that news momentum can predict future stock price developments and establish profitable trading strategies that beat buy-and-hold and momentum benchmarks. Trades are issued for significant changes in momentum between current and prior weeks. We ensure stability of our results by using two different news data sets and by analyzing both different investment horizons and aggregation times for our news momentum. Compared to intraday news trading, medium-term momentum trading allows higher investment volumes and can contribute to complex investment decisions also incorporating other qualitative and quantitative factors.
    2013 46th Hawaii International Conference on System Sciences. 01/2013;
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    F. Wex, G. Schryen, D. Neumann
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    ABSTRACT: Decision support systems play an increasingly important role in disaster management research. Coordination of rescue units during disaster response is one of the many areas which may benefit from this development. Time pressure, resource shortages, different capabilities of rescue units and the interdependence of scheduling and allocation tasks belong to the key challenges which emergency operation centers have to cope with. This paper proposes a non-linear optimization model and suggests a Monte Carlo-based heuristic solution procedure. We computationally benchmark our heuristic with a procedure that is applied in practice. Results of our study show that the Monte-Carlo heuristic is superior to the state-of-the art approach in terms of aggregated harm by up to 40%. However, our simulations also reveal that the time our heuristic needs to process medium-sized instances (100 incidents, 50 rescue units) on a PC is a few hours and that more powerful real-time computing capabilities are required.
    System Sciences (HICSS), 2013 46th Hawaii International Conference on; 01/2013
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    ABSTRACT: In the last century, the costs of powering datacenters have increased so quickly, that datacenter power bills now dwarf the IT hardware bills. Many large infrastructure programs have been developed in the past few years to reduce the energy consumption of datacenters, especially with respect to cooling requirements. Although these methods are effective in lowering the operation costs they do require large upfront investments. It is therefore not surprising that some datacenters have been unable to utilize the above means and as a result are still struggling with high energy bills. In this work we present a cheap addition to or an alternative to such investments as we propose the use of intelligent, energy efficient, system allocation mechanisms in place of current packaged system schedulers available in modern hardware infrastructure cutting server power costs by 40%. We pursue both the quest for (1) understanding the energy costs generated in operation as well has how to utilize this information to (2) allocate computing tasks efficiently in a cost minimizing optimization approach. We were able to underline the energy savings potential of our models compared to current state-of-the-art schedulers. However, since this allocation problem is complex (NP-hard) we investigated various model approximations in a trade-off between computational complexity and allocative efficiency. As a part of this investigation, we evaluate how changes in system configurations impact the goodness of our results in a full factorial parametric evaluation.
    European Journal of Operational Research 10/2012; 222(1):157–167. · 2.04 Impact Factor
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    ABSTRACT: We demonstrate how insider trading analysis may benefit from textual analysis. We analyze reported insider trading behavior and explain the association between corporate as well as 3rd-party news announcements on directors’ dealings activity. Previous approaches are extended by adding the sentiment of news to the research setting. We find strong evidence that insiders follow the stock market adage “Buy on bad news, sell on good news”: They tend to buy (sell) securities in those years where their respective companies issue negative (positive) news. Likewise, insiders tend to buy (sell) stocks in years when 3rd-party news coverage is pessimistic (optimistic). The impact of corporate news on insider trading is higher than for 3rd-party news, as corporate news are subject to direct influence by the insiders. We also find that insiders buy when next year’s news improves compared to the current year. Looking more concretely into the language, we also demonstrate that insiders buy when expressing insecurity and uncertainty. Overall, the findings reveal additional insights for insider trading analysis and demonstrate how finance may benefit from textual analysis.
    07/2012;
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    ABSTRACT: Effective information systems have become key to sustainable business practices. However rising costs of operation and a growing system complexity are driving the search for a more efficient delivery of corporate computing. New technologies in the emerging service world such as cloud computing provide powerful alternatives to traditional IT operation concepts. Nonetheless, executive decision makers still have reservations about migrating to this new technology. In addition to security concerns, a key issue is the still prevailing lack of strict SLAs in these service offerings. In fact, service providers hesitate to offer strictly binding SLAs because assessing economic risk exposure is a major challenge. In this paper, we present a novel model for sustainable SLA design for enterprise information systems. Our model combines various state-of-the-art concepts from the field of system management and balances the failure risk with the cost of operation. More concretely, our model helps IT decision makers to understand the relationship between the operation cost and the service quality. Consequently, the minimum economic price of a service and the corresponding operation strategy, given the customer requirements and the infrastructure characteristics, can be determined based on our approach.
    01/2012;
  • Tim Pueschel, Fabian Putzke, Dirk Neumann
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    ABSTRACT: Competition on global markets forces enterprises to make use of new applications, reduce process times and cut the costs of their IT-infrastructure. To achieve this commercial users harness the benefits of Cloud computing as they can outsource data storage and computation facilities, while saving on the overall cost of IT ownership. Cloud services can be accessed on demand at any time in a pay-as-you-go manner. However, it is this flexibility of customers that results in great challenges for Cloud service providers. They need to maximize their revenue in the presence of limited fixed resources and uncertainty regarding upcoming service requests while contemporaneously considering their SLAs. To address this challenge we introduce models that can predict revenue and utilization achieved with admission-control policy based revenue management under stochastic demand. This allows providers to significantly increase revenue by choosing the optimum policy.
    01/2012;
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    ABSTRACT: We examine whether stock price effects can be automatically predicted analyzing unstructured textual information in financial news. Accordingly, we enhance existing text mining methods to evaluate the information content of financial news as an instrument for investment decisions. The main contribution of this paper is the usage of more expressive features to represent text and the employment of market feedback as part of our word selection process. In our study, we show that a robust Feature Selection allows lifting classification accuracies significantly above previous approaches when combined with complex feature types. That is because our approach allows selecting semantically relevant features and thus, reduces the problem of over-fitting when applying a machine learning approach. The methodology can be transferred to any other application area providing textual information and corresponding effect data.
    Decision Support Systems. 01/2012; 55(3):1040-1049.
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    Felix Wex, Guido Schryen, Dirk Neumann
    International Journal of Information Systems for Crisis Response and Management. 01/2012; 4(3):23-41.
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    European Conference of Information Systems; 01/2012
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    Felix Wex, Guido Schryen, Dirk Neumann
    International Conference on Information Systems for Crisis Response and Management (ISCRAM) 2012; 01/2012
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    ABSTRACT: The cost of electricity for datacenters is a substantial operational cost that can and should be managed, not only for saving energy, but also due to the ecologic commitment inherent to power consumption. This work proposes, formalizes and numerically evaluates LEAS, a low-energy scheduling model, for clearing scheduling markets, based on the maximization of welfare, subject to utility-level dependant energy costs. We promote energy-efficient policies in management of datacenters, to enhance the efficiency of modernized datacenters. We focus specifically on linear power models, and the implications of the inherent fixed costs related to energy consumption of modern datacenters. We rigorously test the model by running multiple simulation scenarios derived from real workload traces, and evaluate the results using common statistical methods. We conclude with positive results and implications for long-term sustainable management of modern datacenters.
    06/2011;
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    ABSTRACT: We develop a sentiment metric to analyze the tone and information amount in financial corporate announcements. We improve existing text processing methods by developing a different word selection approach that allows quantifying the sentiment of financial announcements in an intuitive, but effective manner. Applying our approach to corporate announcements, we find, first, that our metric provides superior explanatory power for abnormal returns during the day of the announcement. Second, analyst EPS forecast revisions during the month after the announcement show a significant structural relation to relevant announcement text components based on Tonality. Third, observed short-term stock price reactions immediately following the announcement are less related to EPS forecast revisions than relevant text components, allowing a new perspective on analyzing post-announcement-drift based on direct cause-and-effect relation.
    05/2011;
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    19th European Conference on Information Systems, ECIS 2011, Helsinki, Finland, June 9-11, 2011; 01/2011
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    Felix Wex, Guido Schryen, Dirk Neumann
    Proceedings of the 8th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2011); 01/2011

Publication Stats

501 Citations
16.13 Total Impact Points

Institutions

  • 2008–2014
    • University of Freiburg
      • Department of Information Systems Research
      Freiburg, Baden-Württemberg, Germany
    • RWTH Aachen University
      Aachen, North Rhine-Westphalia, Germany
    • Concordia University Montreal
      Montréal, Quebec, Canada
    • Universität Mannheim
      Mannheim, Baden-Württemberg, Germany
  • 2005–2010
    • Karlsruhe Institute of Technology
      • • Institute of Information Management in Engineering
      • • Institute of Telematics
      Carlsruhe, Baden-Württemberg, Germany
  • 2003
    • Université de Montréal
      Montréal, Quebec, Canada