Reviewing the hedge funds literature II:hedge funds' returns and risk management characteristics

This paper summarizes the literature on hedge funds (HFs) developed over the last two decades, particularly that which relates to risk management characteristics (a companion piece investigates the managerial characteristics of HFs). It discusses the successes and the shortfalls to date in developing more sophisticated risk management frameworks and tools to measure and monitor HF risks, and the empirical evidence on the role of the HFs and their investment behaviour and risk management practices on the stability of the financial system. It also classifies the HF literature considering the most recent contributions and, particularly, the regulatory developments after the 2007 financial crisis

Information Systems and Stock Return Volatility

Measuring Information Systems (IS) value has been constantly attracting much attention and debate within the IS research community. Since information systems effects are often difficult to quantify, traditional payoff evaluation methods often yield conflicting results. In this paper we suggest that some information systems can be evaluated on the basis of their effect on stock return volatility. Systems which facilitate information sharing and decision-making can improve the quality of company information to stakeholders, thus reducing surprise levels in financial markets. Specifically, these systems can lead to more consistent and predictable company performance. Hence, we hypothesize that information systems can help to reduce a company’s stock return volatility. To test this hypothesis, we have conducted an empirical analysis on a sample of firms that have deployed a Business Intelligence (BI) system. The results indicate a significant reduction in stock return volatility after BI deployment

Finding Elephant flows for optical networks

Optical networks are fast and reliable networks that enable, amongst others, dedicated light paths to be established for elephant IP flows. Elephant IP flows are characterized by being small in number, but long in time and high in traffic volume. Moving these flows from the general IP network to dedicated light paths can be beneficial for both the elephant flows as well as the general IP network. Elephant flows over light paths would benefit from receiving better Quality of Service (at the optical level there is no jitter and far more bandwidth) and, at the same time, IP networks would be off-loaded and therefore offer better Quality of Service to the remaining, smaller IP flows. Identifying elephant flows in large scale IP networks is therefore an important task in order to effectively manage the network. In practice such flows are generally characterized using 5-tuple flow definition (source/destination address/port and protocol), which may be too restrictive for the purpose of establishing optical light paths. In this paper we evaluate different flow definitions at different levels of granularity. Using measurements at a large national research network, we compare our alternative flow definitions to the traditional 5-tuple definition. We show that the discovery of elephant flows eligible to be transferred over light paths can better be reached using less restrictive flow definitions

R&D and knowledge dynamics in university-industry relationships in biotech and pharmaceuticals: An agent-based model

In the last two decades, University-Industry Relationships have played an outstanding role in shaping innovation activities in Biotechnology and Pharmaceuticals. Despite the growing importance and the considerable scope of these relationships, there still is an intensive and open debate on their short and long term effects on the research system in life sciences. So far, the extensive literature on this topic has not been able to provide a widely accepted answer. This work introduces a new way to analyse University-Industry Relationships (UIRs) which makes use of an agent-based simulation model. With the help of simulation experiments and the comparison of different scenario results, new insights on the effects of these relationships on the innovativeness of the research system can be gained. In particular, focusing on knowledge interactions among heterogeneous actors, we show that: (i) universities tend to shift from a basic to an applied research orientation as a consequence of relationships with industry, (ii) universities' innovative capabilities benefit from industry financial resources but not so much from cognitive resources of the companies, (iii) biotech companies' innovative capabilities largely benefit from the knowledge interaction with universities and (iv) adequate policies in terms of public basic research funding can contrast the negative effects of UIRs on university research orientation. --University-Industry Relationships,Knowledge Dynamics,University Patenting,Technology Transfer,Agent-Based Modelling

Fiscal Shocks and Fiscal Risk Management

We use the returns on a set of international financial securities to identify exogenous shocks to the Canadian federal surplus. We find that a large portion of the variation in the surplus can be replicated by a linear combination of these returns and that the rising debt observed in the 1980s and 1990s was a result of adverse exogenous shocks and a delayed response by the government to these shocks. We develop a formal framework to evaluate the potential gains from a fiscal risk management strategy, using these securities to hedge against exogenous shocks. We show that fiscal risk management can generate significant welfare gains by enhancing the sustainability of fiscal policy and thereby lowering average tax rates. Nous utilisons les rendements de plusieurs actifs financiers internationaux pour identifier les chocs exogènes au surplus fédéral canadien. Nous trouvons qu'une grande proportion de la variation du surplus peut être répliquée par une combinaison linéaire de ces rendements et que la dette croissante observée durant les années 1980 et 1990 était le résultat de chocs exogènes négatifs et d'une réponse retardée du gouvernement face à ces chocs. Nous développons un cadre formel permettant d'évaluer les gains potentiels provenant d'une stratégie de gestion du risque fiscal utilisant ces actifs pour se couvrir contre des chocs exogènes. Nous montrons que la gestion du risque fiscal peut générer des gains en bien-être significatifs en améliorant la soutenabilité de la politique fiscale et ainsi en réduisant les taux d'imposition moyens.Fiscal policy, sustainability, asset pricing, risk management

WARP : speeding up the software development process

Estágio realizado na Qimonda Portugal, S. ATese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 200

A Methodology for Modelling Mobile Agent-Based Systems (Mobile agent Mobility Methodology - MaMM)

Mobile agents are a particular type of agents that have all the characteristics of an agent and also demonstrate the ability to move or migrate from one node to another in a network environment. Mobile agents have received considerable attention from industry and the research community in recent times due to the fact that their special characteristic of migration help address issues such as network overload, network latency and protocol encapsulation. Due to the current focus in exploiting agent technology mainly in a research environment, there has been an influx of software engineering methodologies for developing multi-agent systems. However, little attention has been given to modelling mobile agents. For mobile agent-based systems to become more widely accepted there is a critical need for a methodology to be developed to address various issues related to modelling mobility of agent . This research study provides an overview of the current approaches, methodologies and modelling languages that can be used for developing multi-agent systems. The overview indicates extensive research on methodologies for modelling multi-agent systems and little on mobility in mobile agent-based systems. An original contribution in this research known as Mobile agent-based Mobility Methodology (MaMM) is the methodology for modelling mobility in mobile agent-based systems using underlying principles of Genetic Algorithms (GA) with emphasis on fitness functions and genetic representation. Delphi study and case studies were employed in carrying out this research