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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CHRISTIAN L. DUNIS is Girobank Professor of Banking and Finance at Liverpool Business School, and Director of its Centre for International Banking, Economics and Finance (CIBEF). He is also a consultant to asset management firms and an Official Reviewer attached to the European Commission for the evaluation of applications to Finance of emerging software technologies. He is an Editor of the European Journal of Finance and has published widely in the field of financial market analysis and forecasting.
ALLAN TIMMERMANN is Professor of Economics at University of California, San Diego. He is on the editorial board of the Journal of Forecasting and Journal of Business and Economic Statistics. His research is concerned with modelling the dynamics and predictability of returns in financial markets. Professor Timmermann has held positions at Birkbeck College and the London School of Economics.
JOHN MOODY is the Director of the Computational Finance program and a Professor of Computer Science at the Oregon Graduate Institute. His research interests include computational finance, time series analysis and machine learning. Professor Moody has held positions at Yale University and the Institute for Theoretical Physics.
"Dunis, Timmermann and Moody have assembled a fascinating and insightful collection of articles that address the latest developments in forecast combination, long memory, and portfolio choice. These papers present state-of-the-art estimation techniques along with relevant empirical applications. Both academics and practitioners will find this anthology to be a worthy addition to their libraries." -- Joshua Rosenberg, NYU - Stern School of Business
"A modern book on financial econometrics has to consider interesting and relevant topics from the viewpoint of recently developed techniques that have been shown to actually work. This book delivers in all aspects&The many new techniques displayed include the use of loss functions based on economic rather than statistical criteria, the benefits of combining forecasts, dimension reduction, structural changes, and long memory fractional cointegration, neural networks, and high frequency data techniques applied to exchange rates. The authors provide plenty to think about." -- Professor Clive W J Granger, University of California, San Diego
"This book is a welcome addition to the literature on forecasting in financial markets." -- Professor Ken Holden, Liverpool Business School
Developments in Forecast Combination and Portfolio Choice brings together papers that address current frontier research within the field of quantitative finance. Focusing on three core themes of model and forecast combinations; structural change and long memory; and controlling downside risk and investment strategies, the book provides an authoritative collection of readings that are relevant to academics and practitioners alike.
Dunis, Timmermann and Moody have assembled a fascinating and insightful collection of articles that address the latest developments in forecast combination, long memory, and portfolio choice. These papers present state-of-the-art estimation techniques along with relevant empirical applications. Both academics and practitioners will find this anthology to be a worthy addition to their libraries. -- Joshua Rosenberg, NYU - Stern School of Business
A modern book on financial econometrics has to consider interesting and relevant topics from the viewpoint of recently developed techniques that have been shown to actually work. This book delivers in all aspects&The many new techniques displayed include the use of loss functions based on economic rather than statistical criteria, the benefits of combining forecasts, dimension reduction, structural changes, and long memory fractional cointegration, neural networks, and high frequency data techniques applied to exchange rates. The authors provide plenty to think about. -- Professor Clive W J Granger, University of California, San Diego
This book is a welcome addition to the literature on forecasting in financial markets. -- Professor Ken Holden, Liverpool Business School
Developments in Forecast Combination and Portfolio Choice brings together papers that address current frontier research within the field of quantitative finance. Focusing on three core themes of model and forecast combinations; structural change and long memory; and controlling downside risk and investment strategies, the book provides an authoritative collection of readings that are relevant to academics and practitioners alike.
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