The Impact of Situation and Outlook Information in Corn and Soybean Futures Markets: Evidence from WASDE Reports

The purpose of this study was to examine the impact of situation and outlook information from World Agricultural Supply and Demand Estimates (WASDE) in corn and soybean futures markets over the period 1985 to 2006. Results indicate that WASDE reports containing National Agricultural Statistics Service (NASS) crop production estimates and other domestic and international situation and outlook information have the largest impact; causing return variance on report sessions to be 7.38 times greater than normal return variance in corn futures and 6.87 times greater than normal return variance in soybean futures. WASDE reports limited to international situation information and domestic and international outlook information have a smaller impact. The results show that the impact of WASDE reports has increased over time.

[1]  M. F. Fuller,et al.  Practical Nonparametric Statistics; Nonparametric Statistical Inference , 1973 .

[2]  B. Dixon,et al.  The performance of event study approaches using daily commodity futures returns , 2004 .

[3]  R. A. Groeneveld,et al.  Practical Nonparametric Statistics (2nd ed). , 1981 .

[4]  Li Yang,et al.  The value of public information in commodity futures markets , 1997 .

[5]  D. Streeter Agricultural Futures and Options: Principles and Strategies , 1991 .

[6]  W. Spilka An overview of the USDA crop and livestock information system , 1983 .

[7]  D. Sumner,et al.  The effects of USDA reports in futures and options markets , 1993 .

[8]  D. Sumner,et al.  Are Harvest Forecasts News? USDA Announcements and Futures Market Reactions , 1989 .

[9]  S. Irwin,et al.  Market Efficiency and Marketing to Enhance Income of Crop Producers , 1998 .

[10]  R. Just The Impact of Less Data on the Agricultural Economy and Society , 1983 .

[11]  Chris Kirby,et al.  THE JOURNAL OF FINANCE • VOL. LXI, NO. 6 • DECEMBER 2006 Information, Trading, and Volatility: Evidence from Weather-Sensitive Markets , 2022 .

[12]  E. Fama,et al.  Efficient Capital Markets : II , 2007 .

[13]  Y. Tse,et al.  Holy mad cow! Facts or (mis)perceptions: A clinical study , 2006 .

[14]  W. J. Conover,et al.  Practical Nonparametric Statistics , 1972 .

[15]  W. Andrew,et al.  LO, and A. , 1988 .

[16]  D. Good,et al.  The Value of USDA Situation and Outlook Information in Hog and Cattle Markets , 2006 .

[17]  A. Lo,et al.  THE ECONOMETRICS OF FINANCIAL MARKETS , 1996, Macroeconomic Dynamics.

[18]  B. Brorsen,et al.  Daily futures price changes and non-linear dynamics , 1994 .

[19]  TRADING TIME EFFECTS IN FINANCIAL AND COMMODITY FUTURES MARKETS , 1987 .

[20]  S. Irwin,et al.  The Reaction of Live Hog Futures Prices to USDA Hogs and Pigs Reports , 1990 .

[21]  Jeffrey C. Williams Commodity futures and options , 2001 .

[22]  David Zilberman,et al.  Consumption of Economic Information in Agriculture , 2002 .

[23]  D. Whitefield,et al.  A review of: “Practical Nonpararnetric Statistics. By W. J. CONOVER. (New York: Wiley, 1971.) [Pl" x+462.] £5·25. , 1972 .

[24]  K. McNew,et al.  The informational content of USDA crop reports: Impacts on uncertainty and expectations in grain futures markets , 1994 .

[25]  A. McKenzie,et al.  The Effect of E. Coli O157:H7 on Beef Prices , 2001 .

[26]  E. Fama EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[27]  A. Thurow,et al.  Exploring the Market for Agricultural Economics Information: Views of Private Sector Analysts , 1998 .

[28]  Sanford J. Grossman On the Impossibility of Informationally Efficient Markets , 1980 .

[29]  G. W. Snedecor Statistical Methods , 1964 .