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Abstract:
The noise trader sentiment model of De Long, Shleifer, Summers, and Waldmann (1990a) is applied to futures markets. The theoretical results predict that overly optimistic (pessimistic) noise traders result in market prices that are greater (less) than fundamental value. Thus, returns can be predicted using the level of noise trader sentiment. The null rational expectations hypothesis is tested against the noise trader alternative using a commercial market sentiment index as a proxy for noise trader sentiment. Fama-MacBeth cross-sectional regressions test if noise traders create a systematic bias in futures prices. The time-series predictability of futures returns using known sentiment levels is tested in a Cumby-Modest market timing framework and a more general causality specification. The empirical results lead to the following conclusions. First, there is no evidence that noise trader sentiment creates a systematic bias in futures prices. Second, predictable market returns using noise trader sentiment is not characteristic of futures markets in general. Third, futures market returns at weekly intervals are characterized by low-order positive autocorrelation with relatively small autoregressive parameters. In those instances where there is evidence of noise trader effects, it is at best limited to isolated markets and particular specifications.

Abstract:
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.

Abstract:
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.

Abstract:
Value-at-Risk, known as VaR, gives a prediction of potential portfolio losses, with a certain level of confidence, that may be encountered over a specified time period due to adverse price movements in the portfolio's assets. For example, a VaR of 1 million dollars at the 95% level of confidence implies that overall portfolio losses should not exceed 1 million dollars more than 5% of the time over a given holding period. This research examines the effectiveness of VaR measures, developed using alternative estimation techniques, in predicting large losses in the cattle feeding margin. Results show that several estimation techniques, both parametric and non-parametric, provide well-calibrated estimates of VaR such that violations (losses exceeding the VaR estimate) are commensurate with the desired level of confidence. In particular, estimates developed using JP Morgan's Risk Metrics methodology appear robust for instruments that have linear payoff structures such as cash commodity prices.

Abstract:
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.

Abstract:
Considerable research effort has focused on the forecasting of asset return volatility. Debate in this area centers around the performance of time series models, in particular GARCH, relative to implied volatility from observed option premiums. Existing literature suggests that the performance of any volatility forecast is sensitive to both the data and forecast horizon of interest. This paper rigorously examines the performance of several alternative volatility forecasts for fed cattle, feeder cattle, and corn cash price returns. Forecasts include time series, implied volatility, and composite specifications. The results provide considerable insight into the performance of these alternative volatility forecasting procedures over a range of relevant forecast horizons. The evidence suggests that composite methods be used when both time series and implied volatilities are available. Insight is also gained into the performance of procedures used for scaling one-period volatility forecasts to longer horizons. However, consistent with the existing volatility forecasting literature, this research confirms the difficulty in finding a "best" volatility forecasting method across alternative data sets and horizons.

Abstract:
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.

Abstract:
We propose a behavioral decision-making model to investigate what factors, observable as well as unobservable, owner-managers consider regarding futures contract usage. The conceptual model consists of two phases, reflecting the two-stage decision structure of manager's use of futures. In the first phase owner-managers consider whether futures are within the market choice set for the enterprise. In the second phase the owner-manager decides whether or not to initiate a futures position when confronted with a concrete choice situation. In both phases owner-manager's beliefs and perceptions play an important role. The proposed model is tested on a data set of Dutch farmers, based on computer-assisted personal interviews. Because we incorporate latent variables (e.g., perceptions and beliefs) in both phases, we propose an estimation procedure that takes the measurement error of these latent variables explicitly into account. The implications of the behavioral decision-making model for futures contract design are derived.

Abstract:
Price series that are 21.5 years long for six agricultural futures markets, corn, soybeans, wheat, hogs, coffee, and sugar, exhibit time-varying volatility, carry long-range dependence, and portray excessive skewness and kurtosis, though they are covariance stationary. This suggests that the series contain nonlinear dynamics. ARCH and long memory are the two stochastic nonlinear models that are able to produce these symptoms. Though standard ARCH tests suggest that all series might contain ARCH effects, further diagnostics show that the series cannot be ARCH processes. The martingale difference null cannot be rejected by the ARCH model. Three long memory techniques, the classical R/S analysis, the modified R/S analysis, and the AFIMA model, are applied to test the martingale difference null against the long memory alternative. The nonparametric method, the classical R/S analysis, suggests there might be long memory structures in the series. However, two other more robust tests, the modified R/S analysis and the AFIMA model, confirm the case of sugar, but reject this proposition for the other five markets.

Abstract:
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.

Abstract:
This paper develops an alternative view on the motivation to hedge. A conceptual model shows how hedging facilitates contract relationships between firms and can solve conflicts between firms. In this model, firms' contract preferences, level of power and conflicts in contractual relationships are driving usage of futures contracts. The model shows how using futures markets can provide a jointly preferred contracting arrangement, thereby enhancing relationships between firms. The robust nature of the conceptual model is empirically examined through a computer-guided study of various firms.

Abstract:
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 data set and its size.

Abstract:
This study investigates whether U.S. corn merchants can effectively manage the overnight price risk of cash corn purchased after the Chicago Board of Trade closes at 1:15 p.m. on either the electronic Project A market or in the corn contract traded on the Tokyo Grain Exchange. Three scenarios are examined: 1) overnight hedges; 2) day-to-day hedges; and 3) two-day hedges. Overnight hedges are the least effective of the three scenarios on both markets. E-hedging on Project A is more effective than hedging in Tokyo, yet trading of corn futures contracts on Project A remains relatively thin and illiquid. Steps need to be taken to encourage more trading of this contract.

Abstract:
The statistical forecasting efficiency of new crop corn and soybean futures is the topic of frequent academic inquiry. However, few studies address the usefulness of these forecasts to economic agents? decision making. Each year Central Illinois producers are faced with the decision to plant either corn or soybeans on marginal acreage. Agronomic concerns aside, these decisions hinge on the expected relative return of corn versus soybeans, which is largely a function of expected new crop prices. Do new crop futures prices reliably guide producers into the correct production decision? The results suggest that over the entire period of the analysis, futures markets provide only marginal decision-making information to the producer; however, more recent signals do appear to be useful. Further analysis explores several possible factors that could explain why the signals have improved so significantly since 1985.

Abstract:
In order to assure survival, futures exchanges around the world are in constant search of new futures contracts that will generate a profitable level of trading volume. Introducing new futures contracts may increase or decrease the volume for those contracts already listed. 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 differ regarding assets traded and market liquidity (Amsterdam Exchanges versus Chicago Board of Trade) we show the usefulness of the proposed method. The method may also be used to evaluate the benefits for exchanges that plan to internationalize their activities by merging with another exchange or by cross listing other exchanges' futures contracts.

Abstract:
The relationship between farmers' behavioral attitudes and use of futures contracts is examined, taking into account non-directly observable variables and the heterogeneity of farmers. The relationships are tested on a stratified data sample of 440 farmers. Cluster analysis and covariance structure equation models are used to validate the relationships. Farmers are found not to be homogenous regarding the factors influencing their use of futures. Heterogeneity at the segment level masked important effects at the aggregate level, notably risk attitude. Furthermore, several psychological constructs for farmers related to market orientation, risk exposure, market performance and entrepreneurial behavior play important roles in their use of futures contracts.

Abstract:
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.

Abstract:
The informational value of USDA corn and soybean production forecasts is investigated for the period 1971-1992. Three tests of informational content are considered: i) a relative forecast accuracy test, ii) a price reaction test, and iii) a willingness-to-pay test. Overall, the results suggest USDA corn and soybean forecasts provide valuable information to commodity markets. This value, however, does appear to have declined, especially since the mid-1980s. This is consistent with large declines in the cost of information due to technological improvements in computers, communications equipment, remote-sensing satellites, etc.

Abstract:
Using settlement prices and 9 years of daily commitments for large reporting traders in the frozen pork bellies futures market, we find that these traders generate significant profits and the distribution of trader returns over time is not random. Further analysis finds that a subset of large elite traders possesses significant forecasting ability, indicating that they not only are able to consistently anticipate the direction of price changes but are also on the right side of the market when large price changes occur. Hence, certain futures market traders accumulate trading experience and knowledge, permitting them to accrue considerable wealth.

Abstract:
The study investigates price relationships and linkages among different markets using daily futures prices of corn, live hogs, crude oil, Treasury bills, and deutsche marks with two alternative time series techniques. Results suggest that price linkages consistent over time are extremely limited.

Abstract:
This study examines the spot and futures price relationships using the cointegration approach for two storable commodities, corn and soybeans, over a thirteen-year period 1980 to 1992. It is found that specifying a time dimension in the cointegration relation is important to finding evidence of cointegration. However, evidence of cointegration relations between the spot and futures prices is in general weak. In those cases where cointegration exists, the information of cointegration, as represented by the error correction term, contributes only slightly to hedging effectiveness. And, taking the estimation error into account, including the information of the error correction term does not generally improve the optimal hedging ratio. Finally, the information of cointegration was not found very useful for price forecasting, based on conditional efficiency and market timing criteria. All in all, identification of cointegrated price relationships in commodity spot and futures markets seems limiting, and when cointegration is found, its impact is minimal.