Category: Crop Marketing

The USDA Risk Management Agency (RMA) published final 2023 county yields for upland cotton on July 3, 2024.  Upland cotton producers who purchased 2023 crop year Stacked Income Protection Plan (STAX) policies are now receiving final indemnity payments, thus contributing to current cash flow.  Based on RMA’s Summary of Business reporting as of July 15, total STAX indemnities across all states for 2023 will slightly exceed $352.7 million dollars.

STAX is a crop insurance product for upland cotton that provides coverage for a portion of the expected revenue in an area. Most often, the “area” will be a specific county, but may include other counties or production practices as necessary to obtain a credible amount of data to establish an expected yield and premium rate. STAX coverage is available in all counties where crop insurance for upland cotton is currently offered.

According to USDA-RMA data, 4.87 million acres of upland cotton were insured under STAX in 2023 (Figure 1).  This was 48 percent of nearly 10.1 million planted acres.  In the majority of cotton producing states, STAX participation is much lower than 48 percent.  The high concentration of U.S. cotton acreage in Texas inflates the level of total participation in the STAX program.  On a regional basis, the Southwest (Kansas, Oklahoma, and Texas) accounted for 70 percent of the total acres enrolled in STAX last year.  This region also has the largest concentration of upland cotton acreage in the U.S at almost 6.1 million acres.  Texas alone planted over one-half or 5.55 million acres of the U.S. upland cotton total in 2023. Furthermore, Texas accounted for 66 percent, or 3.2 million of the 4.87 million total acres insured under STAX. 

Figure 1. State-Level Percentage of Upland Cotton Planted Acres Enrolled in STAX (2023)

STAX pays a loss on an area-wide basis, and an indemnity is triggered when there is an area loss in gross revenue. Gross revenue is a function of both yield and price.  Common to many crop insurance products, STAX utilizes a futures price (i.e. December cotton futures) to determine the Projected and Harvest prices used to calculate indemnity payments.  For most states in 2023, revenue losses resulted solely from below-average yields, which means that Projected and Harvest prices in those states were either the same or Harvest prices were higher than Projected prices.  

The state level price discovery periods and the 2023 Projected and Harvest prices for cotton are summarized in Table 1.  Only Kansas, New Mexico and Oklahoma had a lower Harvest Price that may have contributed to revenue losses. Thus, for fourteen (14) of the seventeen (17) cotton producing states, any STAX payments were the result of actual yields being at least 10 percent less than the expected county/area yield (assuming the 90 percent area loss trigger was selected).

Table 1. State Level Crop Insurance Price Discovery Periods for Cotton.

State(s)	Projected Price Discovery Period	Harvest Price Discovery Period	2023 Projected Price/lb	2023 Harvest Price/lb
Southern TX	12/15 – 1/14	9/1 – 9/31	$0.81	$0.87
AL, AZ, AR, CA, FL, GA, LA, MS, NC, SC, central TX	1/15 – 2/14	10/1 – 10/31	$0.85	$0.85
MO, northern TX, TN, VA	2/1 – 2/28	10/1 – 10/31	$0.84	$0.85
KS, NM, OK	2/1 – 2/28	11/1 – 11/30	$0.84	$0.78

Since the inception of the STAX program ten years ago, in response to the provisions in the 2014 Farm Bill, some consideration can be given to how effective the product is as a price risk management tool.  Although coverage levels can vary, the majority of STAX policies in the U.S. would see indemnities begin when area revenue falls below 90% of its expected level.  In selecting a crop insurance product, growers may consider the likelihood of a STAX revenue loss being generated solely by declining prices.  Figure 2 illustrates that over the past decade Harvest Prices relative to Projected Prices have experienced a 10 percent or greater decline in three crop years in the period 2014 to 2023, with an average change of -1.2%. Thus, similar to 2023, STAX most often protects against either only yield effects or a combined yield and price effect.  

Figure 2. Percent Price Change from Projected to Harvest Price*, December Cotton Futures (2014 – 2023)

References

USDA-RMA (2024, July). USDA Risk Management Agency Summary of Business. 

URL: https://www.rma.usda.gov/SummaryOfBusiness.

USDA-RMA (2024, July). USDA National Agricultural Statistics Service QuickStats. 

URL: https://quickstats.nass.usda.gov/.

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Stiles, H. Scott, and Hunter D.Biram. “Review of 2023 STAX Payments and Implications for Price Risk Management in Cotton.” Southern Ag Today 4(31.1). July 29, 2024. Permalink

The USDA Quarterly Stocks Report, representative of stocks held on June 1, indicated that both corn and soybean stocks (Figures 1 and 2) are higher than in recent years. High stocks are a bearish factor for the market as they increase the supply side of the balance sheet going into the new marketing year and have been one of many contributing factors to the price decline experienced this summer in corn and soybean markets. A significant insight from the report is how much stock is still stored on-farm versus off-farm.  On-farm corn stocks are at the highest level since 1988 and up 37 percent from last year. On-farm soybean stocks are up 44 percent from a year ago. Given the high level of stocks still being held by producers, it is appropriate to discuss the importance of having an exit strategy that allows producers to exit old crop positions in preparation for new crops. While the exit strategy ideally should be decided before grain goes into storage, some pieces of the discussion below could still be implemented this late in the marketing year. 

An exit strategy marks the official end of marketing activities for a particular crop year. No matter what type of marketing tool is used, a basic exit strategy utilizes price-driven or time-driven methods. Specific price targets guide a price-driven exit strategy. An example would be selling stored grain at X cents over the harvest price. In this case, the harvest price would be what the grain could have been sold for at harvest. Ideally, a price-driven exit strategy would divide sales up across a range of prices; an example for corn would be selling 10,000 bushels at $4.25 per bushel, 10,000 bushels at $4.40 per bushel, and the last 10,000 bushels at $4.50 per bushel. As each price level is attained, grain is sold. This strategy diversifies price targets to ensure you are not stuck with mostly unpriced grains when transitioning into the lower price environments we are currently experiencing. Another example would be selling stored grain at X cents under the harvest price. At some point, exit strategies need to be used to cut losses. Price targets serve as bookends that guarantee the producer will not be left holding grain indefinitely, speculating on a marketing situation that never occurs.

Another exit strategy is to set predetermined sale dates. This could be as simple as “I will sell all stored grain by July 31” or “I will sell 10,000 bushels the first of each month, with my final sale occurring July 31.” Setting a predetermined date forces the producer to take a marketing action. An exit strategy can have both price-driven and time-driven components, for example, selling all stored grain at $4.25 per bushel or higher before July 31^st. Being late in the marketing year, a producer can still sell their grain and maintain a position in the market by buying a call option. If it is decided to hold on to the physical grain, producers will likely need to plan to store until after harvest, as harvest pressure will decrease the likelihood of a better pricing environment.     

While the exit strategies discussed above may seem straightforward, they do a good job of curbing emotional hesitancy in marketing decisions. One of the most challenging emotions for producers to control is regret. A producer might feel regret if they sell right before a rally begins or decide not to sell before a market downturn. Dwelling on regret about past sales can make producers hesitant to book future sales.  A well-developed exit strategy can assist producers in coping with emotional bias in marketing decisions. A successful grain sale is based on sound reasoning, with each component of the exit strategy being grounded in price targets derived from production costs and time targets based on local market seasonality. This exit-strategy approach ensures that each marketing decision is reasonable and not regretted in hindsight. An exit strategy gives producers a way out of the old crop and allows them to focus on new crop positions. 

Figure 1. On-Farm and Off-Farm June 1 Corn Stocks 

Figure 2. On-Farm and Off-Farm June 1 Soybean Stocks 

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Maples, William E. “Having a Way Out.” Southern Ag Today 4(30.1). July 22, 2024. Permalink

Hedge funds or “managed money” refers to financial client money that is invested in commodity futures, stocks, bonds, and other investments. Figure 1 shows varying levels of hedge fund investment in ICE cotton futures over the last ten years, either positioned as bullish net longs (i.e., upward pointing green areas) or bearish net shorts (i.e., downward pointing green areas).  In contrast, the blue colored graphed area of Figure 1 reflects the more stable, long-only positioning of index funds. The latter tend to buy and hold nearby futures contracts, and then roll forward as those contracts mature.

Statistically, net long/short positioning of hedge funds is directly associated with higher/lower ICE cotton futures. Past statistical modeling indicates that a 1.9-cent decline in the most active cotton futures price was expected for every 10,000-contract decrease (or increase) in the hedge fund net long (net short) position (https://www.farmprogress.com/cotton/cotton-spin-hedge-funds-revisited ).  Looking at the most recent price decline, the hedge fund net long position peaked at 73,230 contracts on February 27, 2024, when nearby ICE cotton futures settled at 98.80 cents per pound.  This net long position changed to a 51,442 net short position, a total change of 124,672 contracts and associated with a 72.76-cent settlement on June 18 in nearby ICE cotton futures.  The previous statistical relationship implies that 23.56 cents of the total 26.04 cent decline in nearby ICE cotton futures is associated with bearish hedge fund adjustment, all other things being equal. 

How long will the current net short position last?  Figure 1 highlights that net short positioning is less frequent than net long positioning.  Over the ten years graphed in Figure 1, only 156 weekly observations involved net short positioning while 370 weekly observations involved net long positioning.  Practically speaking, speculating on the size of an establishing, growing crop during the summer is a bit of a risky gamble.  This dynamic may encourage caution on the part of short speculators during the growing season.  Such behavior could also be the basis of a short covering rally in the event of reduced acreage expectations, bad weather, or negative production scenarios.  Short covering is where hedge fund managers buy back their outright short speculative positions as a result of changing (i.e., more bullish) expectations and/or pre-set buy stop orders.  The liquidation of a large net short position can thus lead to a cascade of buying, referred to as a short covering rally.

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Robinson, John. “The Net Short Hedge Fund Position in ICE Cotton Futures.” Southern Ag Today 4(29.1). July 15, 2024. Permalink

Producers make several important marketing and risk management decisions throughout the year. One of the most important decisions is the choice of coverage levels when purchasing crop insurance. Revenue Protection (RP) – by far the most popular plan of insurance – provides an indemnity if realized revenue (combination of yield and price) drops below the guarantee (or a percent of expected revenue) for the insured unit. RP coverage levels range from 50% to 85% of expected revenue, increasing in 5% increments. Producers must weigh the choice of varying RP coverage levels against the changes in premium costs. Premium costs vary and consider factors such as the risk of loss for the insured crop in the specific county, coverage level, insurance product purchased, and production practices. This article examines the weighted average coverage level (WACL) by county and crop from 2011-2022 for corn, cotton, soybean, wheat, and peanut RP insurance plans. RP insurance plans from 2011 to 2022 covered 88% of all insured acres for corn, cotton, peanuts, soybeans, and wheat (USDA Summary of Business). The WACL is calculated as RP coverage level multiplied by acres insured for the coverage level divided by total RP acres insured for each county crop and year.

Corn

The Corn Belt states of Indiana, Illinois, and Iowa show most counties have a WACL of 81% to 85%, indicating higher insurance coverage purchases. Most counties in North Dakota, South Dakota, Nebraska, and Kansas exhibit a WACL of 71% or greater. However, there is more variability in the southern and eastern states, with coverage levels generally lower than in the Midwest.

Figure 1. Corn Acre-Weighted Average Coverage Level Revenue Protection 2011-2022

Cotton

Southern Arizona has a concentration of 76% to 80% WACLs for cotton, while the majority of Western Oklahoma and Texas counties have a WACL for cotton of 66%-70%. The rest of the south’s cotton production is concentrated along the Mississippi River, the east coast, South Georgia, and South Alabama with a 71-75% WACL being the most prominent coverage level. Nationally, there are very few counties with a WACL above 80% for cotton.

Figure 2. Upland Cotton Acre-Weighted Average Coverage Level Revenue Protection 2011-2022

Peanuts

The southern regions of Alabama, Georgia, and the eastern Carolinas show a WACL between 66% and 75%. About half of the counties in Northeast Arkansas and Northwest Mississippi have a WACL of 76% or higher. The counties along the border of Western Oklahoma and Texas have lower WACLs, while those along the border of West Texas and Eastern New Mexico mainly have WACLs of 71% or higher. Like cotton, peanuts have few counties with WACLs that exceed 80% – fewer than twenty counties have WACLs greater than 76%. 

Figure 3. Peanuts Acre-Weighted Average Coverage Level Revenue Protection 2011-2022

Soybeans

Trends for soybeans mirror those for corn, with counties in Ohio, Indiana, Illinois, Iowa, and Kentucky showing WACLs of 76% or higher, with many reaching 81% or higher. From North Dakota to Kansas, counties have WACLs of 71% or better. In the southern states, the WACL varies significantly.

Figure 4. Soybeans Acre-Weighted Average Coverage Level Revenue Protection 2011-2022

Wheat

Northwestern states and parts of the Midwest exhibit WACLs of 76% or greater. In Texas, many counties show lower WACLs, ranging from 50% to 70%. Wheat production varies by season (spring or winter) and type (hard, soft, and durum). Wheat production in the northwestern states is typically soft spring wheat, whereas Texas wheat is mostly hard red winter wheat that produces lower yields than soft wheat. 

Figure 5. Wheat Acre-Weighted Average Coverage Level Revenue Protection 2011-2022

Since the early 1990s, buyup coverage levels for crop insurance have trended higher (Smith, 2015). From 2011 to 2022, across commodities there is greater variability in WACLs in the South than the Midwest and Northern Plains. Variability in WACLs by crop and region highlights differences in risk levels, risk preferences, insurance premiums, and production costs. Regions with higher WACLs often have more consistent yields; regions with lower WACLs typically face higher premium costs due to greater production variability. Understanding trade-offs in risk and premium cost can help producers determine the correct RP insurance coverage level to meet their specific risk management needs.

References and Resources:

Biram, H.D. 2024. The Fundamentals of Federal Crop Insurance, University of Arkansas. Link

Smith, S.A., J. Outlaw, and R. Tufts. 2015. Surviving the Farm Economy Downturn. Chapter 10. Crop Insurance: Basic Producer Considerations. https://afpc.tamu.edu/extension/resources/downturn-book/.

USDA Risk Management Agency. Summary of Business. https://www.rma.usda.gov/SummaryOfBusiness

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Duncan, Hence, and Aaron Smith. “Revenue Protection Weighted Average Coverage Levels by County and Crop.” Southern Ag Today 4(28.1). July 8, 2024. Permalink

On Friday June 28^th the USDA released its annual Acreage report. The report estimates planted acreage of principal crops based on producer surveys conducted in the first two weeks of June. Nationally, principal acres planted were estimated at 315.177 million acres, up 1.866 million acres compared to the March Prospective Plantings report and 4.424 million acres lower than last year (Table 1). Southern states accounted for 22.8% of principal crop acreage. The largest negative and positive percent change (highlighted in Red and Black in the tables below) in principal crop acreage compared to the March Prospective Plantings report, in the southern states, were Oklahoma -5% and South Carolina +8%. Tables 2-7 show acreage changes, by state, compared to last year and the March Prospective Plantings report for corn, wheat, rice, soybean, peanuts, and cotton. 

Corn acres planted were estimated at 91.475 million acres nationally, with the southern states accounting for 10.1% of planted acres. National corn acres were higher than most pre-report predictions and 1.4 million acres greater than the March Prospective Plantings report. Corn futures prices declined 13 to 16 ½ cents for the day. In the southern states, South Carolina had the largest increase, compared to the March report, adding 80,000 acres (+27%), while Louisiana and Tennessee had 9% decreases in planted acres. Nationally, the report indicated that corn left to be planted was 3.36 million acres.

All wheat planted acres were estimated at 47.24 million, down 258,000 acres compared to the March estimate. Revisions in acres were made for Alabama (-15,000 acres), Arkansas (+5,000), Georgia (-25,000 acres), South Carolina (-5,000 acres), Texas (-200,000 acres), and Virginia (-5,000 acres). Chicago wheat futures were down 4 ½ to 6 ¼ cents for the day, and Hard Red Wheat futures were down 4 ½ to 10 ½ cents.

Southern states account for 75% of rice production nationally, with Arkansas the largest producer. Rice acres planted were unchanged in Texas and Mississippi, declined 30,000 acres in Arkansas and increased 30,000 acres in Louisiana.  

Soybean acres were estimated at 86.1 million, down 410,000 acres compared to the March estimate – slightly lower than pre-report estimates. Soybean futures closed down ¾ to 2 ¾ cents for the day. In the southern states, planted acreage was reduced 10,000 acres compared to March, with reductions for Arkansas, North Carolina, and Oklahoma and increases for Alabama, Kentucky, Louisiana, South Carolina, and Tennessee. The report indicated that soybeans left to be planted were 12.8 million acres.

Peanut acreage increased 7% (106,000 acres) compared to the March report. Increased planted acres in Texas, North Carolina, Georgia, and Mississippi were only partially offset by a small reduction in Alabama.

Upland cotton acres were estimated at 11.488 million, nearly 1 million acres higher than the March estimate and pre-report forecasts. Cotton futures closed 1.63 to 2.21 cents per pound lower for the day. Texas planted acreage increased 890,000 acres compared to the March report, contributing by far the most to the change in national acreage. Arkansas had the largest percentage increase at +24%.

Overall, the report provided bearish news for several markets that had already experienced substantial price declines this growing season. Moving forward, prices will continue to react to weather and revisions to planted/harvested acreage estimates.

References and Resources

Barchart.com. Daily futures prices. Accessed at: https://www.barchart.com/futures/grains?viewName=main

USDA National Agricultural Statistics Service (NASS). June 28, 2024. Acreage Report. Accessed at https://usda.library.cornell.edu/concern/publications/j098zb09z

USDA National Agricultural Statistics Service (NASS). March 28, 2024. Prospective Plantings Report. Accessed at https://usda.library.cornell.edu/concern/publications/x633f100h