Giffen goods and market making

This paper shows that information effects per se are not responsible for the Giffen goods anomaly affecting competitive traders’ demands in multi- asset, noisy rational expectations equilibrium models. The role that information plays in traders’ strategies also matters. In a market with risk averse, uninformed traders, informed agents have a dual motive for trading: speculation and market making. While speculation entails using prices to assess the effect of private signal error terms, market making requires employing them to disentangle noise traders’ effects in traders’ aggregate orders. In a correlated environment, this complicates a trader’s signal-extraction problem and may generate upward-sloping demand curves. Assuming either (i) that competitive, risk neutral market makers price the assets, or that (ii) the risk tolerance coefficient of uninformed traders grows without bound, removes the market making component from informed traders’ demands, rendering them well behaved in prices.Financial economics, asset pricing, information and market efficiency

Giffen Goods and Market Making

This paper shows that information effects per se are not responsible for the Gi®en goods anomaly affecting competitive traders' demands in multi-asset, noisy rational expectations equilibrium models. The role that information plays in traders' strategies also matters. In a market with risk averse, uninformed traders, informed agents have a dual motive for trading: speculation and market making. While speculation entails using prices to assess the effect of private signal error terms, market making requires employing them to disentangle noise traders' effects in traders' aggregate orders. In a correlated environment, this complicates a trader's signal-extraction problem and may generate upward-sloping demand curves. Assuming either (i) that competitive, risk neutral market makers price the assets, or that (ii) the risk tolerance coefficient of uninformed traders grows without bound, removes the market making component from informed traders' demands, rendering them well behaved in prices.financial economics, asset pricing, information and market efficiency

A Semantic Agent Framework for Cyber-Physical Systems

The development of accurate models for cyber-physical systems (CPSs) is hampered by the complexity of these systems, fundamental differences in the operation of cyber and physical components, and significant interdependencies among these components. Agent-based modeling shows promise in overcoming these challenges, due to the flexibility of software agents as autonomous and intelligent decision-making components. Semantic agent systems are even more capable, as the structure they provide facilitates the extraction of meaningful content from the data provided to the software agents. In this book chapter, we present a multi-agent model for a CPS, where the semantic capabilities are underpinned by sensor networks that provide information about the physical operation to the cyber infrastructure. As a specific example of the semantic interpretation of raw sensor data streams, we present a failure detection ontology for an intelligent water distribution network as a model CPS. The ontology represents physical entities in the CPS, as well as the information extraction, analysis and processing that takes place in relation to these entities. The chapter concludes with introduction of a semantic agent framework for CPS, and presentation of a sample implementation of the framework using C++

Integrative Use of Information Extraction, Semantic Matchmaking and Adaptive Coupling Techniques in Support of Distributed Information Processing and Decision-Making

In order to press maximal cognitive benefit from their social, technological and informational environments, military coalitions need to understand how best to exploit available information assets as well as how best to organize their socially-distributed information processing activities. The International Technology Alliance (ITA) program is beginning to address the challenges associated with enhanced cognition in military coalition environments by integrating a variety of research and development efforts. In particular, research in one component of the ITA ('Project 4: Shared Understanding and Information Exploitation') is seeking to develop capabilities that enable military coalitions to better exploit and distribute networked information assets in the service of collective cognitive outcomes (e.g. improved decision-making). In this paper, we provide an overview of the various research activities in Project 4. We also show how these research activities complement one another in terms of supporting coalition-based collective cognition

Data Mining by Soft Computing Methods for The Coronary Heart Disease Database

For improvement of data mining technology, the advantages and disadvantages on respective data mining methods should be discussed by comparison under the same condition. For this purpose, the Coronary Heart Disease database (CHD DB) was developed in 2004, and the data mining competition was held in the International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES). In the competition, two methods based on soft computing were presented. In this paper, we report the overview of the CHD DB and the soft computing methods, and discuss the features of respective methods by comparison of the experimental results

Practical applications of multi-agent systems in electric power systems

The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur