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Featured researches published by David E. Kenyon.


American Journal of Agricultural Economics | 1993

Forecasting Performance of Corn and Soybean Harvest Futures Contracts

David E. Kenyon; Eluned Jones; M. Anya McGuirk

In contrast to earlier periods, post 1973 spring prices of December corn and November soybean futures contracts have not been good forecasts of harvest price. Regression analysis of price forecast variance before and after 1973 indicates that the decline in forecasting accuracy is related to increased yield forecast errors and to reduced interference of government loan rates on market price determination. Since these futures are poor forecasts, producers should not rely on futures prices alone to allocate resources at planting time unless they simultaneously forward price.


Applied Economic Perspectives and Policy | 2001

Producer Ability to Forecast Harvest Corn and Soybean Prices

David E. Kenyon

Harvest-price expectations for corn and soybeans were obtained in January and February each year from 1991–1998. Producer expectations on average missed actualcorn and soybean prices by


American Journal of Agricultural Economics | 1987

Toward an Appropriate Measure of Uncertainty in a Risk Programming Model

William T. McSweeny; David E. Kenyon; Randall A. Kramer

0.41 and


Journal of Agricultural and Applied Economics | 1973

An Analysis of Anticipatory Short Hedging Using Predicted Harvest Basis

David E. Kenyon; Steven E. Kingsley

0.67 per bushel, respectively. Producer price expectations each year had a range of over


Journal of Futures Markets | 1987

Factors affecting agricultural futures price variance

David E. Kenyon; Kenneth Kling; James V. Jordan; William E. Seale; Nancy McCabe

1.00 per bushelfor both crops. Producer price distributions were skewed toward higher prices, and they consistently underestimated the probability of large price changes from January until harvest.


Journal of Futures Markets | 1987

Analysis of profit margin hedging strategies for hog producers

David E. Kenyon; John Clay

The measure of uncertainty in a risk-programming problem has long posed a dilemma. The use of the variance of realized returns assumes that the distribution of realized returns is the same as the distribution anticipated by the decision maker prior to the start of production. Rejection of this maintained hypothesis requires either direct elicitation of these distributions or construction of another measure from realized data. A mean-squared forecast error is considered an appropriate measure. Optimal solutions to a quadratic risk-programming problem are obtained using this measure and compared to those obtained using traditional measures. (This abstract was borrowed from another version of this item.)


Journal of Futures Markets | 1987

Transactions data tests of the black model for soybean futures options

James V. Jordan; William E. Seale; Nancy McCabe; David E. Kenyon

The use of the futures market as an aid in The producers net price (


Archive | 1988

THE INTRADAY VARIABILITY OF SOYBEAN FUTURES PRICES: INFORMATION AND TRADING EFFECTS

James V. Jordan; William E. Seale; Steve Dinehart; David E. Kenyon

1.20) is the harvest cash marketing farm commodities has been gaining in price (


Journal of Futures Markets | 1997

Multiple‐year pricing strategies for corn and soybeans

David E. Kenyon; Charles V. Beckman

1.15) plus the gain or loss on the futures popularity among producers. Current hedging contract(s) (


Staff Papers | 1999

Price Discovery and Risk Management in an Industrialized Pork Sector

David E. Kenyon; Wayne D. Purcell

.05). Equivalently, net price is the short practices are largely based on average basis or basis futures price (

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William E. Seale

United States Commodity Futures Trading Commission

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Nancy McCabe

United States Commodity Futures Trading Commission

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William T. McSweeny

Pennsylvania State University

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