Grain Price Risk Management: Using A Hedge Ratio

By: Craig Haymaker, Chief Operating Officer

This is the second article in a series entitled ‘Grain Price Risk Management.’ Please visit HedgeStar University for other articles in this series. In this article, we posit the application of a hedge ratio and address how to apply it in a risk management framework. In our previous article – Price Risk Perspective in the Grain Supply Chain – we explored the price risk orientation of different types of organizations within the grain supply chain – producers, consumers and suppliers/traders. We noted their price direction bias and how risk is mitigated by locking-in prices. In that vein, we also acknowledged that the market is unpredictable and that price risk management warrants consideration of historical price levels as a data point for hedging decisions. Ultimately, we were left with questions on how grain market participants can mitigate their price risk given the prevailing market outlook on grain prices. When considering a hedge program, organizations should always begin by establishing risk appetite. This exercise is a coordinated effort between senior management and the board of directors. Risk appetite is often represented by a risk policy that places ‘guard rails’ around an organization’s hedging activities. A good risk policy will outline clearly the role of governance and leadership functions, risk reporting (e.g. scorecards), the responsibilities of risk groups, key processes and internal controls. Risk reporting is critical here, as it conveys key risk metrics and risk limits that serve as guidelines within which hedgers will operate – this is the true expression of an organization’s risk appetite. Examples of risk limits may include maintaining a hedge ratio quantity between 30%-80%, keeping value at-risk below $X million, hedged exposure between 80-100%, and so on. Concepts such as risk appetite and risk reporting will be explored further in our grains article entitled Monitoring Grain Hedges. As risk managers, we do not speculate where prices will go. We conduct analyses by evaluating a number of factors – current price levels, crop yields, acreage, weather patterns and other supply and demand data points to name a few – and then benchmark these factors against similar historical conditions (a “grains analysis” or “price risk analysis”) to formulate a thesis on price outlook. Price risk analyses don’t tell us whether or not to hedge – our risk management framework and approval from senior leadership dictate this decision. Instead, they inform us about when and how much to hedge, while also minimizing cash flow volatility and losses from adverse market conditions. Focusing now on grain consumers and how they think about price risk, managing grain purchases and production input costs is paramount. Budget requirements dictate the preferred margin for the organization between grain price purchased per unit (e.g. bushel, short ton) and selling price per unit of the finished good. While this margin objective is relatively clear, systematic risk in the commodities market makes it far more challenging to achieve. With this objective in mind, let’s now presume that the grains consumer intends only to lock-in prices at a certain level and assure price certainty for a specified timeline. With prices at historically low levels, this seems like a prudent and favorable action considering the current outlook is that prices are likely to increase. But what if the opposite happens and grain prices go down? Did the consumer fail in its ability to effectively manage price risk? It was able to mitigate the cash flow variability inherent in commodities, yet the prices went in a direction not expected – a common outcome in volatile market conditions. Creating a price risk analysis can help us navigate this uncertainty. Example With this example, assume it’s mid-August 2020 and we intend to hedge corn prices for delivery in October 2020. With consideration given to two-months’ (August to October) worth of corn price risk, a risk manager might begin by adjusting his/her analysis to show corn prices over the last ten years using prices observed for mid-October. Applying only these two factors – historical price and seasonality – a simplified grains analysis output might look like the chart below:

First, let’s assume current corn prices for October are 340₵/bushel. Using our grains analysis, there is a 20% probability prices could drop below current levels and an 80% probability they will not. Thus, the consumer’s risk management team sets out to lock-in grain prices at or near 80% of its forecasted needs for October. This is a common starting point for organizations that, as a practical matter, want to avoid hedging too much quantity and desire some flexibility to adjust forecasted grain purchases with changing demand for finished goods. With that, consider 80% the upper band of the desired hedge ratio. This 80% hedge ratio also implies that 20% of the forecasted grain needs will be purchased at prevailing market price or “spot” levels, instead of being hedged. Now, let’s go the other way and assume that grain prices are at higher levels (historically speaking) around 500₵/bushel, for example. Suddenly, fixed pricing at or near 80% of forecasted needs is less attractive. Instead, the analysis tells us that locking-in prices around 40-50% is more pragmatic, leaving the other 50-60% of our purchases to float with the market. As you would imagine, adjusting the hedge ratio down can be a slippery slope for risk managers because the lower the ratio, the greater the market price risk to the organization. As such, a judicious hedge ratio “floor” might be between 35-50% for organizations actively managing grain price risk. Again, the hedge ratio percentages employed by the organization are an expression of its risk appetite and should be subject to review and approval by the Board of Directors. This is a simplified view into one facet of a comprehensive price risk analysis. As mentioned before, most risk managers will want to use factors beyond historical price and seasonality, giving more consideration present-day factors such as crop yields, acreage and recent weather patterns to get a better understanding of the current growing environment. The monthly World Agricultural Supply and Demand Estimates (“WASDE”) reports published by the US Department of Agricultural can be terrific resources for informing organizations about these types of analysis factors. Ultimately, price risk analyses should be living, breathing assessments that evolve over time to reflect an organization’s own experience and orientation with factors influencing grain prices. As a counterpoint, some organizations may suggest that conducting price risk analyses on a frequent basis and tinkering constantly with a hedge ratio is excessive and tedious. There is some truth to this perspective. Active risk management has a cost, and suitability of this exercise may differ from organization to organization. Simpler analyses that consider fewer factors – much like the one above – can be conducted, but are at risk of failing to incorporate critical data points that might otherwise alter decision making about when and how much to hedge. One angle unexplored in this article is using financial instruments such as derivatives to avoid constantly changing hedge ratios while optimizing risk management. Derivatives – both exchange-traded and over the counter – offer organizations greater latitude to manage price risk given volatile and/or adverse market conditions. There are different types of derivatives that afford users greater flexibility for selecting the instrument best suited to their risk appetite and risk management strategy. The different types of derivative instruments and their profiles will be covered in a separate article entitled Instruments for Hedging Grain Price Risk.

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