Bullish corn yield projections in the United States confounded many analysts, but were no surprise to those who follow Thomson Reuters Agriculture.
The 2017/18 corn season in the United States has been one of surprise, denial, and finally, acceptance.
Month after month, high yields reported by the U.S. Department of Agriculture (USDA) shocked the market upon release.
Initial reactions featured skepticism and doubt, and then gradual acceptance as analysts’ own estimates eventually caught up with our own research.
Going well beyond notoriously fickle condition scores, Thomson Reuters Agriculture Research (Lanworth) was one of the very few groups to first catch the upside in United States corn yields.
Watch video — Thomson Reuters Agriculture Research (Lanworth) – US crop tour August 2017
Ahead of the release of the USDA reports, Reuters exclusively polled analysts’ expectations.
These insights keep customers on the pulse of market sentiment and allow them to capitalize quickly on price fluctuations ahead of, and after, the market moving data.
In addition, our agriculture research analysts provide further insight and commentary into the data inputs driving their views.
Their methodology combines weather modeling, satellite imagery and extensive field data collection to provide early and accurate supply intelligence.
— Grains Guru (@GrainsGuru) October 5, 2017
Tracking the upside
Thomson Reuters customers truly benefited in September and October.
The market, which was focusing largely on comparing notoriously fickle condition scores from one season to another, was convinced the USDA had its yield too high and that it would surely come down in the 12 September report.
In fact, the USDA shocked the market when it increased corn yield to 169.9 bushels per acre (bpa).
Thomson Reuters had yield at 170.8 bpa, citing beneficial weather and near record vegetation density, as shown by satellite imagery.
However, models based purely on condition scores were pointing to national yields lower than those expected based on weather and satellite imagery.
In September, according to Reuters polls, a corn yield above 170 bpa was considered extreme — the highest analyst estimate in the market. A month later 169.8 bpa was the average estimate of the analysts surveyed. By November, 169.7 bpa was the lowest.
Thomson Reuters customers were informed of the upside of this year’s crop well ahead of government reports. They were also well informed as to the reasons why the corn yield would exceed market expectations before nearly everyone else.
The USDA subsequently upped corn yield to 171.8 bpa in October before raising the yield once again in November.
Securing market advantage
Tracking the fundamental shift in weather is where our experienced analysts and scientific approach has given customers the edge.
For all crops and geographies for which we forecast, we rely on rigorous, systematic, and comprehensive analysis of several independent sources of information: climate indicators set our initial expectations, which is followed by actual weather and satellite data that tests and updates these expectations.
We then collect field observations and survey elevators as a further check on climate, weather and image-based estimates.
Customers were well positioned on soybean yields as well.Weather and satellite imagery models, coupled with field work, implied soybean yield at 49.3 bpa, lower than the USDA’s estimate in early October of 49.9 bpa.
The average of analysts’ own estimates from the Reuters poll expected yield to be unchanged. Only three out of 14 analysts contributing an independent estimate held lower yields. Upon release, the USDA lowered soybean yield to 49.5 bushels per acre.
What happened in the U.S. in 2017 is an example of how and why Thomson Reuters Agriculture Research gives customers an edge in advance, but it has not been the only example.
It has happened many times before across the world.
Why is this the case? The answer is that our estimates come from a dedicated, experienced team that pays close, rigorous attention to the fundamentals that drive production and constantly tests their expectations.
The result is accuracy, and, more importantly, trust.