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

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,

CASH AND FUTURES PRICE RELATIONSHIPS FOR NONSTORABLE COMMODITIES: AN EMPIRICAL ANALYSIS USING A GENERAL THEORY

Empirical analysis examines the presence of basis risk, speculative component, and expected maturity basis component in basis relationships for nonstorable commodities. The results indicate that all three above components exist in both cattle and hog markets. The basis risk and speculative components vary across contracts. Hog markets showed seasonality, which helps explain the hog basis more accurately. Flexibility in making the marketing decision strengthens the explanation of intertemporal price relationships for both cattle and hogs beyond that previously attributed to only feed prices.Demand and Price Analysis, Marketing,

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

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,

Agricultural Applications of Value-at-Risk Analysis: A Perspective

Value-at-Risk (VaR) determines the probability of a portfolio of assets losing a certain amount in a given time period due to adverse market conditions with a particular level of confidence. Value-at-Risk has received considerable attention from financial economists and financial practitioners for its use in risk reporting, in particular the risks of derivatives. This paper provides a "state-of-the-art" review of VaR estimation techniques and empirical findings found in the finance literature. The ability of VaR estimates to represent large losses associated with tail events varies among procedure, confidence level, and data used. To date, there is no consensus to the most appropriate estimation technique. Potential applications of Value-at-Risk are suggested in the context of agricultural risk management. In the wake of the Hedge-to-Arrive crisis, the lifting of agricultural trade options by the CFTC, and the decreased government participation, VaR seems to have a place in the agricultural risk manager's toolkit.Value-at-Risk, risk management, estimation procedures

OPTIMAL HEDGING STRATEGIES FOR THE U.S. CATTLE FEEDER

Multiproduct optimal hedging for simulated cattle feeding is compared to alternative hedging strategies using weekly price data for 1983-95. Out-of-sample means and variances of hedged feeding margins using estimated hedge ratios for four commodities suggest that there is no consistent domination pattern among the alternative strategies, leaving the hedging decision up to the agent's degree of risk aversion. However, all hedging strategies significantly reduce the feeding margin's means and variances compared to no hedging, with variance reduction always exceeding 50%. Hedging results appear quite sensitive to the data set and its size.cattle feeding, hedge ratios, hedging strategies, multiproduct hedging, optimal hedging, Marketing,

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.