The Value of USDA Announcements in the Electronically Traded Corn Futures Market: A Modified Sufficient Test with Risk Adjustments

Abstract

The paper assesses the value of USDA information in the electronic corn futures markets. While recent research has documented large price volatility spikes after USDA announcements, increased volatility does not directly translate into value. Using multiple newly developed risk-premium measures and intraday data, we extend the Carter and Galopin approach based on estimating the risk-adjusted profits that accrue to advanced USDA information. Using the 2010-2020 period, the analysis demonstrates that USDA announcement surprises have economic value, with WASDE surprises from NASS-WASDE joint events being always valuable under all risk preferences. While the value is sensitive to these preferences, risk is relatively small because prices usually move in the direction of the market surprise which minimises losses. NASS surprises also contain value, though less than WASDE and only for the less risk averse traders. While overall risk is generally small, the intensified volatility right after the announcement points to the presence of noise and to the inadequacy of inferring the value of public information through price variability alone.

The Agricultural Economic Value of Weather Forecasting in China

“…Before adding the control variables, the regression coefficient of the weather forecasting was 0.832, which passed the 1% significance test; from the regression results, adding the control variables one by one, the meteorological forecasting still retained a significant positive impact on the agricultural economic efficiency. From the regression results of column (7), it can be seen that for every one percentage point increase in the accuracy of the weather forecasting, the economic efficiency of agriculture increased by 0.500 percentage points. Therefore, the empirical results verified the promotion effect of accurate weather forecasting on the agricultural economic benefits.…”

“…Few scholars have used econometric methods to discuss and verify the relationship between meteorological forecasting and economic benefits. Huang (2009) et al [7] pointed out that a regular weather forecast can directly affect the change in certain in the financial market by predicting the change in a certain crop yield at a certain time in the future. Wang (2019) [8] found that weather forecasting plays an important role in agricultural production, which is specifically reflected in helping to establish an early warning mechanism for agricultural production, reducing meteorological disaster losses and improving the scientific level of agricultural production management.…”

A systematic review on price volatility in agriculture

“…In comparison, the quantity theory of money (Zhang et al., 2014) was the only dominant theory that appeared in the post‐crisis period in spot market studies. These studies have gone into great transition in terms of theory starting from price stabilization (Yang et al., 2001) in both market types towards more sophisticated theories for addressing various issues, that is, arbitrage pricing for asymmetric price adjustments (Mao et al., 2021), cobweb for sustainable food value chain (Muflikh et al., 2021) and expected utility theory for asymmetric information (Huang et al., 2021). The researchers tried a wide range of theories as agriculture markets do not provide a “natural correction process” for price volatility and require distinguishing between endogenous and exogenous price volatility (Huffaker et al., 2018).…”

Grain Futures Market Response to the Black Sea Grain Initiative

“…Previous studies have examined internal drivers, such as market participants and traders (Williams and Wright, 1991;Gorton, Hayashi and Rouwenhorst, 2013;Fama and French, 2016), and external influences, which include economic and geopolitical factors (Bailey and Chan, 1993;Hess, Huang and Niessen, 2008). Additionally, studies have explored the relationship between commodity futures prices and investment portfolios (Erb and Harvey, 2006;Gorton and Rouwenhorst, 2006), USDA reports (Huang, Serra and Garcia, 2021;Massa, Karali and Irwin, 2023), market patterns (Decoster, Labys and Mitchell, 1992;Chinn and Coibion, 2014), and market efficiency (Kellard et al, 1999;Kristoufek and Vosvrda, 2014;Kuruppuarachchi, Lin and Premachandra, 2019). Some researchers have focused explicitly on grain futures prices, mainly studying the implications of market speculation and its determinants (e.g., Sanders, Irwin and Merrin, 2010;Karali and Thurman, 2010;Etienne, Irwin and Garcia, 2015).…”