Commodities have become an important component of many investors' portfolios and the focus of much political controversy over the past decade. This book utilizes structural models to provide a better understanding of how commodities' prices behave and what drives them. It exploits differences across commodities and examines a variety of predictions of the models to identify where they work and where they fail. The findings of the analysis are useful to scholars, traders and policy makers who want to better understand often puzzling - and extreme - movements in the prices of commodities from aluminium to oil to soybeans to zinc.

Commodity prices tend to be volatile, and volatility itself varies over time. changes in volatility can affect market variables by directly affecting the marginal value of storage, and by affecting a component of the total marginal cost of productions: the opportunity cost of exercising the option to produce the commodity now rather than waiting for more price information. I examine the role of volatility in short-run commodity market dynamics, as well as the determinants of volatility itself. Specifically, I develop a model describing the joint dynamics of inventories, spot and futures prices, and volatility, and estimate it using daily and weekly data for the petroleum complex: crude oil, heating oil, and gasoline.

Fluctuations of commodity prices, most notably of oil, capture considerable attention and have been tied to important economic effects. This book advances our understanding of the consequences of these fluctuations, providing both general analysis and a particular focus on the countries of the Pacific Rim.

This book examines the issue of price volatility in agricultural commodities markets and how this phenomenon has evolved in recent years. The factors underlying the price spike of 2007-08 appear to be global and macroeconomic in nature, including the rapid growth in demand by developing countries, the international financial crisis, and exchange rate movements. Some of these factors are new, appearing as influences on price volatility only in the last decade. Although volatility has always been a feature of agricultural commodity markets, the evidence suggests that volatility has increased in certain commodity markets. A growing problem is that agricultural price shocks and volatility disrupt agricultural markets, economic incentives and incomes. With increased globalization and integration of financial and energy markets with agricultural commodity markets, the relationships between markets are expanding and becoming more complex. When a crisis such as a regional drought, food safety scare or a financial crisis hits a particular market, policy-makers often do not know the extent to which it will impact on other markets and affect producer, consumer and trader decisions. Including contributions from experts at the World Bank, the Food and Agriculture Organization of the United Nations, the USDA, and the European Commission, the research developed throughout the chapters of this book is based on current methodologies that can be used to analyze price volatility and provide directions for understanding this volatility and the development of new agricultural policies. The book highlights the challenges facing policy makers in dealing with the changing nature of agricultural commodities markets, and offers recommendations for anticipating price movements and managing their consequences. It will be a practical guide for both present and future policy-makers in deciding on potential price-stabilizing interventions, and will also serve as a useful resource for researchers and students in agricultural economics.

This book provides fresh insights into concepts, methods and new research findings on the causes of excessive food price volatility. It also discusses the implications for food security and policy responses to mitigate excessive volatility. The approaches applied by the contributors range from on-the-ground surveys, to panel econometrics and innovative high-frequency time series analysis as well as computational economics methods. It offers policy analysts and decision-makers guidance on dealing with extreme volatility.

This paper studies the volatility of commodity prices on the basis of a large dataset of monthly prices observed in international trade data from the United States over the period 2002 to 2011. The conventional wisdom in academia and policy circles is that primary commodity prices are more volatile than those of manufactured products, even though most of the existing evidence does not actually attempt to measure the volatility of prices of individual goods or commodities. Rather the literature tends to focus on trends in the evolution and volatility of ratios of price indexes composed of multiple commodities and products. This approach can be misleading. Indeed, the evidence presented in this paper suggests that on average prices of individual primary commodities may be less volatile than those of individual manufactured goods.

Commodity prices exhibit different characteristics than traditional asset classes. This paper provides an in-depth analysis of the corresponding price dynamics transferring a time series approach originally proposed by Chan et al. (1992) to the field of commodities. One unrestricted and eight restricted stochastic models are assessed and empirically tested. Besides an incorporated mean reversion feature, the model also allows the volatility to change with the underlying price. Daily data of 22 commodities out of different sectors are taken into consideration. Generic front month future contracts form July 24, 1997 to January 6, 2011 were used for the analysis (3511 observations), further splitting the time series into a bull (2002 - 2006) and bear market regime (2007 - 2008). Generalized Method of Moments (GMM) are applied to estimate the unknown parameters and a &u9672 goodness-of-fit test is run to evaluate which models capture best the dynamics of the corresponding commodities for different market regimes. In line with Geman and Shih (2009) we find that the CEV exponent &u947 plays a very important role in the modeling of commodity price dynamics whereas the mean reversion effect disappears for most of the commodities for the different periods under analysis.