Commodity market behavior in different states of economy

The past decade witnessed wide swings in commodity prices, which has spurred renewed interest in non-fuel commodities. In 2008 Ben Bernanke, then chairman of the US Federal Reserve, identified commodity prices as one of the main outstanding issues in the analysis of inflation. However, interpreting commodity price cycles and providing factor attribution is still a widely unsolved riddle. Our project strives to shed some light on these issues. We plan to examine commodity price forecasting models with a focus on non-fuel commodities such as agricultural commodities, metals and minerals, where predictors include fundamental variables (like production, yields, inventories and weather), macroeconomic variables and financial variables. We aim to systematically compare a large battery of different statistical models, where we also address model uncertainty. In comparing the competing models, we evaluate the forecast performance not only in terms of traditional measures but also in terms of new measures, including, e.g., indicators that assess whether the direction of the price change was correctly forecasted. Under certain conditions these new measures could be economically more relevant than pure statistical measures (based on the difference between the prediction and the realized value). Our main objective is to find out whether the quality of commodity forecasts depends on the state of the economy and what variables are the key players in explaining different commodity classes in different states of the economy. For example, we would like to answer the question whether commodity forecast models provide better predictions in turbulent than in calm times (i.e., in periods of high/low uncertainty). Other examples of different states of the economy which we plan to investigate are recessions/expansions, periods of high/low inflation, periods of high/low interest rates, and periods of different market sentiment (investors attitudes as to anticipated price development in a market).