Options-based forecasts of futures prices in the presence of limit moves

The reported analysis examines a simultaneous estimation option-based approach to forecast futures prices in the presence of daily price limit moves. The procedure explicitly allows for changing implied volatilities by estimating the implied futures price and the implied volatility simultaneously. Using futures and futures options data for three agricultural commodities, it is found that the simultaneous estimation approach accounts for the abrupt changes in implied volatility associated with limit moves and generates more accurate price forecasts than conventional methods that rely on only one implied variable.     

Farmers' Preferences for Crop Insurance Attributes

Utilizing survey data from corn and soybean farmers in the Midwest, this study assesses the relative importance of different features of crop insurance products. Conjoint analysis results indicate that farmers' preferences for flexibility dominate both type of insurance and coverage level. Revenue insurance demand is greater by those who are larger, younger, and farm in more separate locations. Results are significant and consistent by size, insurance usage, leverage, and risk perception. The results permit prediction of market shares of competing insurance products within specific producer segments, and thus also provide guidance for targeting specific producer groups with new product configurations.     

The Term Structure of Implied Forward Volatility: Recovery and Informational Content in the Corn Options Market

Using a flexible method, we develop the term structure of volatility implied by corn futures options with differing maturities, and evaluate its ability to predict subsequent realized price volatility. The implied forward volatilities anticipate realized volatility well. For the nearby interval, the implied forward volatilities provide unbiased forecasts, and are superior to forecasts based on historical volatilities. For more distant intervals, early-year options predict the direction and magnitude of future volatility changes about as well as a three-year moving average and better than a naïve forecast. However, later-year options display less forecast power in part due to reduced trading activity.     

Institutional Portfolios: Diversification through Farmland Investment

This article demonstrates that farmland can enhance the overall performance of institutional portfolios which are currently dominated by stocks, bonds, and business real estate. Unlike previous articles on farmland returns, this article addresses the issue of "smoothing bias" associated with appraisal-based farmland returns. Improved measures of income returns to farmland are also used in developing the estimates of optimal portfolios. Parametric testing revealed that farmland continues to enter the optimal portfolios even for large increases in the variance or for large reductions in the annual returns to farmland.     

Factors influencing producers' perceptions about the importance of government support programmes in agriculture: application of a semi-parametric ordered response model

This article examines factors affecting producers’ perceptions towards the relative importance of government support programmes in agriculture. Specific attention is placed on determining the effect of crop insurance usage on farmers’ views about the importance of government programme payments. Results from a semi-parametric ordered response model shows that producers who use yield- or revenue-based crop insurance products also tend to view government programmes with higher importance, suggesting that crop insurance and direct government support programmes tend to be complements rather than substitutes.     

An Examination of Option-Implied S&P 500 Futures Price Distributions

Expected S&P 500 futures price distributions are derived using no-arbitrage option pricing models. These distributions are parameterized both as the lognormal and as a less restrictive three-parameter Burr-XII distribution. The resulting option-based probability assessments display some evidence of miscalibration very near to expiration and far from expiration, but are accurate over intermediate time ranges. The means of the implied price distributions correspond closely to the contemporaneous futures prices for both distributions, although marginally better with the Burr-XII. The Burr-XII distribution also performs better than the lognormal based on calibration statistics, and hence, is used to recalibrate estimated distributions.     

Factors Influencing Farmers' Crop Insurance Decisions

Farmers' decisions to purchase crop insurance and their choices among alternative products are analyzed using a two-stage estimation procedure. The influences of risk perceptions, competing risk management options, as well structural and demographic differences are evaluated. The likelihood for crop insurance usage is found to be higher for larger, older, less tenured, more highly leveraged farms, and by those with higher perceived yield risks. The marginal effects of size, age, perceived yield risk, perceived importance of risk management activities, and other structural and demographic variables are identified in terms of their influences on choices among alternative crop insurance products.     

Integration of VaR and expected utility under departures from normality

This article identifies the level of the expected utility (EU) risk aversion and Value-at-Risk (VaR) confidence level that yield the same choice from a given distribution of outcomes, and thus allow for consistent application of the two criteria. The result for a given distribution is an explicit mapping between risk aversion under EU and VaR, for both normal and nonnormal distributions. The Cornish–Fisher expansion is used to establish adjusted mean-deviates for nonnormal outcome distributions and the investor's preference function is expanded to include elements for variance, skewness, and excess kurtosis. A farm-level application with nonnormal revenue distribution illustrates these approaches.     

Factors Influencing Illinois Farmland Values

A hedonic model of Illinois farmland values is estimated using county-level cross-section time-series data. Explanatory variables include land productivity, parcel size, improvements, distances to Chicago and other large cities, an urban–rural index, livestock production through swine operation scale and farm density measures, population density, income, and inflation. The inclusion of spatial and serial correlation components substantially improves the model fit. Farmland values decline with parcel size, ruralness, distance to Chicago and large cities, and swine farm density, and increase with soil productivity, population density, and personal income.