Recent economic growth in China and other Asian countries has led to increased commodity demand which has caused price rises and accompanying price fluctuations not only for crude oil but also for the many other raw materials. Such trends mean that world commodity markets are once again under intense scrutiny. This book provides new insights into the modeling and forecasting of primary commodity prices by featuring comprehensive applications of the most recent methods of statistical time series analysis. The latter utilize econometric methods concerned with structural breaks, unobserved components, chaotic discovery, long memory, heteroskedasticity, wavelet estimation and fractional integration. Relevant tests employed include neural networks, correlation dimensions, Lyapunov exponents, fractional integration and rescaled range. The price forecasting involves structural time series trend plus cycle and cyclical trend models. Practical applications focus on the price behaviour of more than twenty international commodity markets.
Table of Contents
Contents: Introduction; History of Commodity Price Analysis. Long Run Price Movements: Identifying trends and breaks; Convergence of commodity prices. Medium Run Price Movements: Identifying price cycles; Business cycle impacts. Short Run Price Movements: Color of commodity prices; Wavelet models in the time frequency domain. Price Forecasting: Noisy chaotic dynamics; Structural forecasting models; Prospects for the future; Appendix: resources for future research; Bibliography; Index.
’Modern statistical techniques have greatly enlarged the range and complexity of analysis that can be applied to commodity market studies. Labys pioneers by making the leap from traditional structural models to the broad range of advanced time series methods. This is the first and only book on the frontiers of commodity market modeling.’ F. Gerard Adams, University of Pennsylvania, USA