Developments in forecast combination and portfolio choice

Contributors About the Contributors. Series Preface Preface THEME I MODEL AND FORECAST COMBINATIONS What Exactly Should We Be Optimising? Criterion Risk in Multicomponent and Multimodel Forecasting (A. Neil Burgess) A Meta-parameter Approach to the Construction of Forecasting Models for Trading Systems (Neville Towers and A. Neil Burgess) The Use of Market Data and Model Combination to Improve Forecast Accuracy (Christian L. Dunis, Jason Laws and Sti phane Chauvin) 21 Nonlinear Ways to Beat the Market (George T. Albanis and Roy A. Batchelor) Predcting High Performance Stocks Using Dimensionality Reduction Techniques Based on Neural Networks (George T. Albanis and Roy A. Batchelor) THEME II STRUCTURAL CHANGE AND LONG MEMEOR Structural Change and Long Memory in Volatility: New Evidence from Daily Exchange Rates (Michel Beine and Si bastien Laurent) Long-run Volatility Dependencies in Intraday Data and Mixture of Normal Distributions (Auri lie Boubel and Si bastien Laurent) Comparison of Parameter Esitmation Methods in Cyclical Long Memory Time Series (Laurent Ferrara and Dominique Guegan) THEME III CONTROLLING DOWNSIDE RISK AND INVESTMENT STRATEGIES Building a Mean Downside Risk Portfolio Frontier (Gustavo M. de Athayde) Implementing Discrete-Time Dynamic Investment Strategies with Downside Risk: A Comparison of Returns and Investment Policies (Mattias Persson) Portfolio Optimisation in a Downside Risk Framework (Riccardo Bramante and Barbara Cazzaniga) The Three-moment CAPM: Theoretical Foundations and an Asset Pricing Model Comparison in a Unified Framework (Emmanuel Jurczwnko and Bertrand Maillet) Stress-testing Correlations: An Application to Portfolio Risk Management (Frederick Bourgoin.) Index.