Financial regulation has dramatically evolved and strengthened since the crisis on both sides of the Atlantic, with enhanced international coordination through the G-20 and the Financial Stability Board and, at the regional level, a definite contribution from the European Union. However the new regulatory environment has its critics, with many divergent voices arguing that over-regulation has become a root cause of our current economic stagnation.This book provides a bigger picture view of the impact and future of financial regulation in the EU, exploring the relationship between microeconomic incentives and macroeconomic growth, regulation and financial integration, and the changes required in economic policy to further European integration. Bringing together contributions from law, economics and management science, it offers readers an accessible but rigorous understanding of the current state of play of the regulatory environment, and on the future challenges.Coverage will include:o A review of the recent regulatory changes from a legal and economic perspectiveo Analysis of how the economic model of financial institutions and entities is impacted by the new frameworkso How to improve securitization and new instruments under MIFID IIo Issues in the enhanced supervision under delegated acts for AIFMD, CRR-CRD IV and Solvency IIo How long term funding can be supplied in lieu of the non-conventional monetary policieso A new architecture for a safer and more efficient European financial system Financial Regulation in the EU provides much needed clarity on the impact of new financial regulation and the future of the economy, and will prove a must have reference for all those working in, researching and affected by these changes.
This book introduces the novel artificial intelligence technique of polymodels and applies it to the prediction of stock returns. The idea of polymodels is to describe a system by its sensitivities to an environment, and to monitor it, imitating what a natural brain does spontaneously. In practice this involves running a collection of non-linear univariate models. This very powerful standalone technique has several advantages over traditional multivariate regressions. With its easy to interpret results, this method provides an ideal preliminary step towards the traditional neural network approach.
The first two chapters compare the technique with other regression alternatives and introduces an estimation method which regularizes a polynomial regression using cross-validation. The rest of the book applies these ideas to financial markets. Certain equity return components are predicted using polymodels in very different ways, and a genetic algorithm is described which combines these different predictions into a single portfolio, aiming to optimize the portfolio returns net of transaction costs. Addressed to investors at all levels of experience this book will also be of interest to both seasoned and non-seasoned statisticians.