Investors face a number of challenges when seeking to estimate the prospective performance of a long-only investment in commodity futures. For instance, historically, the average annualized excess return of individual commodity futures has been approximately zero and commodity futures returns...

Investors face numerous challenges when seeking to estimate the prospective performance of a longonly investment in commodity futures. For instance, historically, the average annualized excess return of the average individual commodity futures has been approximately zero and commodity futures...

The futures-implied petroleum cracking spread is examined for overreaction and subsequent mean reversion via a mechanical trading rule: when the implied margin is greater (less) than estimated refining costs a short (long) spread position is entered. The trading rule results in statistically...

Price series that are 21.5 years long for six agricultural futures markets, corn, soybeans, wheat, hogs, coffee and sugar, possess characteristics consistent with nonlinear dynamics. Three nonlinear models, ARCH, long memory and chaos, are able to produce these symptoms. Using daily, weekly and...

This paper studies the correlation of agricultural prices with stock market dynamics. We discuss the possible role of financial and macroeconomic factors in driving this time-varying relation, with the aim of understanding what caused positive correlation between agricultural commodities and...

This paper relates to internet, noise trading and commodity futures prices. The theoretical framework is the Mixture Distribution Hypothesis (MDH) that posits a joint dependence of return volatility and information. We use two different proxies for the observed component of information flows,...

This paper analyses futures prices for four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) and five agricultural commodities (corn, oats, soybean oil, soybeans and wheat), over the period 1986-2010. Using CCC and DCC multivariate GARCH models, we find that...

This paper analyses futures prices for four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) and five agricultural commodities (corn, oats, soybean oil, soybeans and wheat), over the period 1986-2010. Using CCC and DCC multivariate GARCH models, we find that...

This paper evaluates how different types of speculation affect the volatility of commodities’ futures prices. We adopt four indexes of speculation: Working’s T, the market share of non-commercial traders, the percentage of net long speculators over total open interest in future markets,...

The close relationship between commodity future and cash prices is critical for the effectiveness of risk management and the functioning of price discovery. However, in recent years, commodity futures prices, across the board, have appeared increasingly detached from prices on physical markets....