Developments in Forecast Combination and Portfolio Choice / Edition 1

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Overview

Developments in Forecast Combination and Portfolio Choice focuses on the following three themes: model and forecast combinations; structural change and long memory, controlling downside risk and investment strategies. Written by leading international researchers and practitioners, his book deals efficiently with three key questions facing portfolio managers. How to achieve greater forecasting accuracy; how to deal with structural change in asset allocation models and how to control downside risk, i.e. the risk of loss, in portfolio management.

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Product Details

Meet the Author

CHRISTIAN L. DUNIS is Girobank Professor of Banking and Finance atLiverpool Business School, and Director of its Centre forInternational Banking, Economics and Finance (CIBEF). He is also aconsultant to asset management firms and an Official Reviewerattached to the European Commission for the evaluation ofapplications to Finance of emerging software technologies. He is anEditor of the European Journal of Finance and has published widelyin the field of financial market analysis and forecasting.

ALLAN TIMMERMANN is Professor of Economics at University ofCalifornia, San Diego. He is on the editorial board of the Journalof Forecasting and Journal of Business and Economic Statistics. Hisresearch is concerned with modelling the dynamics andpredictability of returns in financial markets. ProfessorTimmermann has held positions at Birkbeck College and the LondonSchool of Economics.

JOHN MOODY is the Director of the Computational Finance program anda Professor of Computer Science at the Oregon Graduate Institute.His research interests include computational finance, time seriesanalysis and machine learning. Professor Moody has held positionsat Yale University and the Institute for Theoretical Physics.

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Table of Contents

Contributors.

About the Contributors.

Series Preface.

Preface

THEME I MODEL AND FORECAST COMBINATIONS

What Exactly Should We Be Optimising? Criterion Risk inMulticomponent and Multimodel Forecasting (A. Neil Burgess).

A Meta-parameter Approach to the Construction of Forecasting Modelsfor Trading Systems (Neville Towers and A. Neil Burgess).

The Use of Market Data and Model Combination to Improve ForecastAccuracy (Christian L. Dunis, Jason Laws and Sté phaneChauvin).

21 Nonlinear Ways to Beat the Market (George T. Albanis and Roy A.Batchelor).

Predcting High Performance Stocks Using Dimensionality ReductionTechniques Based on Neural Networks (George T. Albanis and Roy A.Batchelor).

THEME II STRUCTURAL CHANGE AND LONG MEMEORY

Structural Change and Long Memory in Volatility: New Evidence fromDaily Exchange Rates (Michel Beine and Sé bastienLaurent).

Long-run Volatility Dependencies in Intraday Data and Mixture ofNormal Distributions (Auré lie Boubel and Sé bastienLaurent).

Comparison of Parameter Esitmation Methods in Cyclical Long MemoryTime Series (Laurent Ferrara and Dominique Guegan).

THEME III CONTROLLING DOWNSIDE RISK AND INVESTMENT STRATEGIES

Building a Mean Downside Risk Portfolio Frontier (Gustavo M. deAthayde).

Implementing Discrete-Time Dynamic Investment Strategies withDownside Risk: A Comparison of Returns and Investment Policies(Mattias Persson).

Portfolio Optimisation in a Downside Risk Framework (RiccardoBramante and Barbara Cazzaniga).

The Three-moment CAPM: Theoretical Foundations and an Asset PricingModel Comparison in a Unified Framework (Emmanuel Jurczwnko andBertrand Maillet).

Stress-testing Correlations: An Application to Portfolio RiskManagement (Frederick Bourgoin.)

Index.

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