Sanctions and public enforcement of insider trading laws in Europe

The recent financial crisis triggered an increasing demand for financial regulation to counteract the potential negative economic effects of the evermore complex operations and instruments available on financial markets. As a result, insider trading regulation counts amongst the relatively recent but particularly active regulation battles in Europe and overseas. Claims for more transparency and equitable securities markets proliferate, ranging from concerns about investor protection to global market stability. The internationalization of the world’s securities market has challenged traditional notions of regulation and enforcement. Considering that insider trading is currently forbidden all over Europe, this study follows a law and economics approach in identifying how this prohibition should be enforced. More precisely, the study investigates first whether criminal law is necessary under all circumstances to enforce insider trading; second, if it should be introduced at EU level. This study provides evidence of law and economics theoretical logic underlying the legal mechanisms that guide sanctioning and public enforcement of the insider trading prohibition by identifying optimal forms, natures and types of sanctions that effectively induce insider trading deterrence. The analysis further aims to reveal the economic rationality that drives the potential need for harmonization of criminal enforcement of insider trading laws within the European environment by proceeding to a comparative analysis of the current legislations of height selected Member States. This work also assesses the European Union’s most recent initiative through a critical analysis of the proposal for a Directive on criminal sanctions for Market Abuse. Based on the conclusions drawn from its close analysis, the study takes on the challenge of analyzing whether or not the actual European public enforcement of the laws prohibiting insider trading is coherent with the theoretical law and economics recommendations, and how these enforcement practices could be improved.

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

Stig Strömholm, Copyright and the Conflict of Laws: A Comparative Survey

Heymanns Verlag 2010, 88 p., ISBN 978-3-452-27300-0