Long Agricultural Futures Prices: ARCH, Long Memory, or Chaos Processes?

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 monthly data for the six markets, each of these models is tested against the martingale difference null, one-by-one. Standard ARCH tests suggest that all series might contain ARCH effects, but further diagnostics show that the series are not ARCH processes, failing to reject the null. A long-memory technique, the AFIMA model, fails to find long-memory structures in the data, except for sugar. This allows chaos analysis to be applied directly to the raw data. Carefully specifying phase space, and utilizing correlation dimension and Lyapunov exponent together, the remaining five price series are found to be chaotic processes.futures markets, ARCH, chaos

Optimal Hedging Strategies for the U.S. Cattle Feeder

Multiproduct optimal hedging is compared to alternative hedging strategies as applied to a Midwestern cattle feeder. One-period feeding margin hedge ratios are estimated using weekly cash and futures price data from a simulation of a custom feedlot for 1983 ??? 1995. Hedge ratios are estimated using the last 4 years, 6 years, or all prior data available at the moment of estimation; the ratios demonstrate less variability as the length of the underlying sample increases. Hypothesis of all hedge ratios being equal to each other, that leads to the proportional hedging model, is rejected. Means and variances of hedged feeding margins using the computed hedge ratios suggest that there is no consistent domination pattern among the alternative strategies. For the ratios computed based on all prior data available, all strategies are on the efficient frontier, leaving the hedging decision up to the agent???s degree of risk aversion. All hedging strategies are shown to significantly reduce the feeding margin???s means and variances compared to no hedging, with variance reduction always exceeding 50 percent. Whether a producer chooses multiproduct, single-commodity, or proportional hedge ratios is sensitive to the dataset and its size.published or submitted for publicationnot peer reviewe

A NOTE ON THE FACTORS AFFECTING CORN BASIS RELATIONSHIPS

Empirical tests were made of components of the corn basis in the U.S. utilizing a general theory of intertemporal price relationships for storable commodities. These tests showed that the basis consists of a risk premium, a speculative component, and a maturity basis apart from other factors such as storage costs for storable commodities. The results provide insights into factors affecting basis patterns for corn.Demand and Price Analysis,

Commodity Futures Contract Viability: A Multidisciplinary Approach

We propose a development process of commodity futures contracts in which the decisions and wishes of potential customers are investigated simultaneously with the necessary technical properties that need to be met for trading to take place. Within this framework the relationship between trading volume and hedging effectiveness is examined taking both basis risk and market depth risk into account, and the relationship between owner-manager's characteristics and the probability of using futures is examined, taking latent variables and the heterogeneity of owner-managers into account. The relationships are tested on a set of data gathered in a stratified sample of 440 owner-managers by means of computer-assisted personal interviews and on transaction-specific futures data. Structural equation models and multiple regression models are used to validate the relationships. The hedging effectiveness and the variables that play a role in the owner-manager's use of futures are related to the tools of the exchange.Futures Contracts Design; Multidisciplinarity; Hedging Effectiveness; Choice Behavior; Measurement Error; Segments; Futures Exchange Toolbox

Futures Exchange Innovations: Reinforcement versus Cannibalism

Futures exchanges are in constant search of futures contracts that will generate a profitable level of trading volume. In this context, it would be interesting to determine what effect the introduction of new futures contracts have on the trading volume of the contracts already listed. The introduction of new futures contracts may lead to a volume increase for those contracts already listed and hence, contribute to the success of a futures exchange. On the other hand, the introduction of new futures contracts could lead to a volume decrease for the contracts already listed, thereby undermining the success of the futures exchange accordingly. Using a multi-product hedging model in which the perspective has been shifted from portfolio to exchange management, we study these effects. Using data from two exchanges that are different regarding market liquidity (Amsterdam Exchanges versus Chicago Board of Trade) we show the usefulness of the proposed tool. Our findings have several important implications for a futures exchange's innovation policy.

EVALUATING THE HEDGING POTENTIAL OF THE LEAN HOG FUTURES CONTRACT

The lean hog futures contract is replacing the live hog futures contract at the Chicago Mercantile Exchange beginning with the February 1997 contract. The lean hog futures will be cash settled based on a broad-based lean hog price index, eliminating terminal markets from the price discovery process. Using this index over a twenty-month period as a proxy for the lean hog futures price, this paper compares the hedging effectiveness of the live hog futures contract to the hedging potential of the lean hog futures contract for cash live hogs as well as four cash meat cuts. Frozen pork bellies futures are also examined for the cash meats. Both long-term and short-term hedges are simulated, using the minimum-variance approach, which utilizes only unconditional information, and the Myers-Thompson approach that incorporates conditional information. The results show that the lean hog futures should perform better than either the live hog or the frozen pork bellies futures as a hedging instrument for Omaha cash hogs and cash loins. The strongest evidence of this is for the short-term hedging of cash hogs. For the other three meats, no futures contract demonstrated a clear hedging advantage.Marketing,

USING MECHANICAL TRADING SYSTEMS TO EVALUATE THE WEAK FORM EFFICIENCY OF FUTURES MARKETS

Research and Development/Tech Change/Emerging Technologies,

NONPARAMETRIC KERNEL ESTIMATION OF MULTIPLE HEDGE RATIOS

It is possible for the traditional hedge ratio estimation to produce erroneous guidance to risk managers because of the restrictive assumptions. This study adopts nonparametric locally polynomial kernel estimation to exclude the assumptions. Results from the hog complex find that hedge ratios estimated by local polynomial kernel regression outperform naïve and GARCH models. Because of the potential assumption violations associated with the estimation and implementation of hedge ratios by GARCH models, LPK is a reasonable alternative for estimating hedge ratios to manage price risks.Marketing, Research Methods/ Statistical Methods, Risk and Uncertainty,

THE DISTRIBUTIONAL BEHAVIOR OF FUTURES PRICE SPREADS

The distributional behavior of futures price spreads is examined for four commodities: corn, live cattle, gold and T-bonds. Remarkably different results are found over commodities, time period, and sample size. Actual spread changes for the smaller sample size of gold and T-bonds and for corn produce more normal distributions for weekly than for daily differencing intervals, while all live cattle spreads for actual changes are normally distributed. However, the larger sample size of both gold and T-bonds and the relative spread changes for corn and live cattle do not become more normally distributed under temporal aggregation of the data.corn, futures price spreads, gold, goodness of fit, live cattle, normality tests, spread distributions, T-bonds, Marketing,