A modular agent-based environment for studying stock markets

Artificial stock markets are built with diffuse priors in mind regarding trading strategies and price formation mechanisms. Diffuse priors are a natural consequence of the unknown relation between the various elements that drive market dynamics and the large variety of market organizations, findings, however, might hold only within the specific market settings. In this paper we propose a framework for building agent-based artificial stock markets. We present the mechanism of the framework based on a previously identified list of organizational and behavioural aspects. Within the framework experiments with arbitrary many trading strategies, acting in various market organizations can be conducted in a flexible way, without changing its architecture. In this way experiments of other artificial stock markets, as well as theoretical models can be replicated and their findings compared. Comparisons of the different experimental results might indicate whether findings are due to traders’ behaviour or to the chosen market structure and could suggest how to improve market quality

Mid-term report for the CORE Organic II funded project. “Innovative cropping Practices to increase soil health of organic fruit tree orchards” BIO-INCROP

Activities performed in the first part of BIO-INCROP project concern five of the eight main objectives fixed in the project proposal. They are: Evaluation of soil borne pest and pathogens involved in replant disease Role of rhizospheric bacterial and fungal communities in plant health Selection of naturally available resources to increase microbial diversity and biomass Compost and organic amendments Evaluation of biologically active formulates The document reports main research results and shows main items of dissemination activity performed in the first part of the project

AUK: a simple alternative to the AUC

The area under Receiver Operating Characteristic (ROC) curve, also known as the AUC-index, is commonly used for ranking the performance of data mining models. The AUC has many merits, such as objectivity and ease of interpretation. However, since it is class indifferent, its usefulness while dealing with hig

Addressing health information privacy with a novel cloud-based PHR system architecture

Patient Health Records (PHRs) shift the ownership of health data from health providers to patients. Such a shift poses important challenges from the data privacy point of view. Patients would like to be able to selectively reveal information to other stakeholders and, at the same time, be assured that their health information will not be used improperly once shared. Current PHR systems partially fail to satisfy these requirements. In this paper, we show that both requirements can be satisfied fully when adopting a novel cloud-based PHR system architecture.We expain the role of remote virtual machines in this architecture and use interaction models to reason about privacy implications. Finally, we evaluate MyPHRMachines, a prototypical implementation of the architecture: we demonstrate that the system enables the execution of third party genome analysis services on patientowned genome data while ensuring that (1) such services cannot maliciously store this data and (2) patients can show the analysis results to experts without sharing along their full genome

Financial news analysis using a semantic web approach

In this paper we present StockWatcher, an OWL-based web application that enables the extraction of relevant news items from RSS feeds concerning the NASDAQ-100 listed companies. The application's goal is to present a customized, aggregated view of the news categorized by different topics. We distinguish between four relevant news categories: i) news regarding the company itself, ii) news regarding direct competitors of the company, iii) news regarding important people of the company, and iv) news regarding the industry in which the company is active. At the same time, the system presented in this chapter is able to rate these news items based on their relevance. We identify three possible effects that a news message can have on the company, and thus on the stock price of that company: i) positive, ii) negative, and iii) neutral. Currently, StockWatcher provides support for the NASDAQ-100 companies. The selection of the relevant news items is based on a customizable user portfolio that may consist of one or more of these companies

An open platform for personal health record apps with platform-level privacy protection

One of the main barriers to the adoption of Personal Health Records (PHR) systems is their closed nature. It has been argued in the literature that this barrier can be overcome by introducing an open market of substitutable PHR apps. The requirements introduced by such an open market on the underlying platform have also been derived. In this paper, we argue that MyPHRMachines, a cloud-based PHR platform recently developed by the authors, satisfies these requirements better than its alternatives. The MyPHRMachines platform leverages Virtual Machines as flexible and secure execution sandboxes for health apps. MyPHRMachines does not prevent pushing hospital- or patient-generated data to one of its instances, nor does it prevent patients from sharing data with their trusted caregivers. External software developers have minimal barriers to contribute innovative apps to the platform, since apps are only required to avoid pushing patient data outside a MyPHRMachines cloud. We demonstrate the potential of MyPHRMachines by presenting two externally contributed apps. Both apps provide functionality going beyond the state-of-the-art in their application domain, while they did not require any specific MyPHRMachines platform extension

On the Design of Artificial Stock Markets

Artificial stock markets are designed with the aim to study and understand market dynamics by representing (part of) real stock markets. Since there is a large variety of real stock markets with several partially observable elements and hidden processes, artificial markets differ regarding their structure and implementation. In this paper we analyze to what degree current artificial stock markets reflect the workings of real stock markets. In order to conduct this analysis we set up a list of factors which influence market dynamics and are as a consequence important to consider for designing market models. We differentiate two categories of factors: general, well-defined aspects that characterize the organization of a market and hidden aspects that characterize the functioning of the markets and the behaviour of the traders

A Modular Agent-Based Environment for Studying Stock Markets

Artificial stock markets are built with diffuse priors in mind regarding trading strategies and price formation mechanisms. Diffuse priors are a natural consequence of the unknown relation between the various elements that drive market dynamics and the large variety of market organizations, findings, however, might hold only within the specific market settings. In this paper we propose a framework for building agent-based artificial stock markets. We present the mechanism of the framework based on a previously identified list of organizational and behavioural aspects. Within the framework experiments with arbitrary many trading strategies, acting in various market organizations can be conducted in a flexible way, without changing its architecture. In this way experiments of other artificial stock markets, as well as theoretical models can be replicated and their findings compared. Comparisons of the different experimental results might indicate whether findings are due to traders’ behaviour or to the chosen market structure and could suggest how to improve market quality