Mind Coskewness: A Performance Measure for Prudent, Long-Term Investors

This study examines how negative skewness a¤ects the behaviour of prudent investors. It also shows how the commonly used frame- work in the intertemporal asset pricing and the dynamic portfolio- consumption choice literature can generate negative skewness in asset reutrns. Given this impact, an extra premium is required in order to hold an asset with negatively coskewed returns. This premium was, on average, 2.09% p.a. for the UK stock market universe. Hence, a new performance measure, the intercept of the Harvey-Siddique two-factor asset pricing model is suggested for prudent, long-term investors. Us- ing this model, the performance of UK unit trusts is examined over the period 1991-2005. Despite exhibiting signi.cantly negative mana- gerial ability, trust managers were successful in reaping part of this negative coskewness premium.

Malware Classification based on Call Graph Clustering

Each day, anti-virus companies receive tens of thousands samples of potentially harmful executables. Many of the malicious samples are variations of previously encountered malware, created by their authors to evade pattern-based detection. Dealing with these large amounts of data requires robust, automatic detection approaches. This paper studies malware classification based on call graph clustering. By representing malware samples as call graphs, it is possible to abstract certain variations away, and enable the detection of structural similarities between samples. The ability to cluster similar samples together will make more generic detection techniques possible, thereby targeting the commonalities of the samples within a cluster. To compare call graphs mutually, we compute pairwise graph similarity scores via graph matchings which approximately minimize the graph edit distance. Next, to facilitate the discovery of similar malware samples, we employ several clustering algorithms, including k-medoids and DBSCAN. Clustering experiments are conducted on a collection of real malware samples, and the results are evaluated against manual classifications provided by human malware analysts. Experiments show that it is indeed possible to accurately detect malware families via call graph clustering. We anticipate that in the future, call graphs can be used to analyse the emergence of new malware families, and ultimately to automate implementation of generic detection schemes.Comment: This research has been supported by TEKES - the Finnish Funding Agency for Technology and Innovation as part of its ICT SHOK Future Internet research programme, grant 40212/0

On monetary policy and stock market anomalies

This study utilizes a macro-based VAR framework to investigate whether stock portfolios formed on the basis of their value, size and past performance characteristics are affected in a differential manner by unexpected US monetary policy actions during the period 1967-2007. Full sample results show that value, small capitalization and past loser stocks are more exposed to monetary policy shocks in comparison to growth, big capitalization and past winner stocks. Subsample analysis, motivated by variation in the realized premia and parameter instability, reveals that monetary policy shocks’ impact on these portfolios is significant and pronounced only during the pre-1983 period.Monetary policy, Federal funds rate, Market anomalies, Credit channel, Risk premia

Effects of immigration on population growth and structures in Greece - A spatial approach

From the early 1990s, Greece has been experiencing a strong immigration flow consisting of various nationality groups with different demographic profiles and structures. The immigrant population is not uniformly distributed spatially and consists of various nationality groups with different demographic behaviours. Therefore, the examination of the implications of immigration on the population size and structure at a low geographical level, according to the nationality composition of the foreign population, is useful in finding population structures which are impossible to observe otherwise. This paper examines the impact of immigration on the population size, age and sex structure of the population in Greek municipalities. In order to do this, statistical clustering techniques have been utilised to define homogeneous groups of municipalities with respect to the nationality composition of their foreign population as well as the impact of immigration on their size and demographic characteristics.

Testing for persistence in mutual fund performance and the ex post verification problem: Evidence from the Greek market

The present study examines a series of performance measures as an attempt to resolve the ex post verification problem. These measures are employed to test the performance persistence hypothesis of domestic equity funds in Greece, during the period 1998-2004. Correctly adjusting for risk factors and documented portfolio strategies explains a significant part of the reported persistence. The intercept of the augmented Carhart regression is proposed as the most appro- priate performance measure. Using this measure, weak evidence for persistence, only before 2001, is documented. The growth of the fund industry, the direction of flows to past winners and the integration in the international nancial system are suggested to be the reasons for the absence of performance persistence

Unprecedented chemical transformation: crystallographic evidence for 1,1,2,2-tetrahydroxyethane captured within an Fe6Dy3 single molecule magnet

A nonanuclear {Fe6Dy3} coordination cluster displaying SMM behaviour in which an unprecedented chemical transformation provides structural information for the existence of 1,1,2,2-tetrahydroxyethane is reported

Information literacy and peer-to-peer infrastructures: An autopoietic perspective

This article argues that an autopoietic perspective of human communities would allow to understand societies as self-organized systems and thus promote information literacy as a facilitator of social development. Peer-to-peer (P2P) social dynamics generate public information available worldwide in digital repositories, websites and bibliographic resources. However, processing such amount of data is not achievable by a single central-controlled system. We claim that distributed and heterogeneous networks of coordinated mechanisms, composed by both specialized human and artificial agents, are needed to improve information retrieval, knowledge inference and decision-making, but also to produce social value, goods and services. Handling these issues implies the collective construction of global semantic networks but also the active labor of knowledge producers and consumers. We conclude that information literacy is as much important as any technical implementation and, therefore, may lead to networks of Commons-oriented communities which would utilize P2P infrastructuresVasilis Kostakis acknowledges funding for facilities used in this research by IUT (19-13) of the Estonian Ministry of Education and Researc

Motor Nucleus of the Trigeminal Nerve

This report contains a summary of expression patterns for genes that are enriched in the motor nucleus of the trigeminal nerve (V) of the pons. All data is derived from the Allen Brain Atlas (ABA) in situ hybridization mouse project. The structure's location and morphological characteristics in the mouse brain are described using the Nissl data found in the Allen Reference Atlas. Using an established algorithm, the expression values of the motor nucleus of the trigeminal nerve were compared to the values of its larger parent structure, in this case the pons, for the purpose of extracting regionally selective gene expression data. The highest ranking genes were manually curated and verified. 50 genes were then selected and compiled for expression analysis. The experimental data for each gene may be accessed via the links provided; additional data in the sagittal plane may also be accessed using the ABA. Correlations between gene expression in the motor nucleus of the trigeminal nerve and the rest of the brain, across all genes in the coronal dataset (~4300 genes), were derived computationally. A gene ontology table (derived from DAVID Bioinformatics Resources 2007) is also included, highlighting possible functions of the 50 genes selected for this report. 
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