Solution

A common hedging strategy when targeting a level of revenue is simple swaps, where the hedge converts a floating price to a fixed price. However, if a company tries to be 100% certain by hedging all its revenue exposure, the result is usually hedging too much. Why? Because this approach assumes that unhedged volumes would receive zero dollars in revenue, and this is usually too conservative. 

The challenge: finding the precise amount of volume needed to make goal achievement sufficiently likely, rather than certain. 

Often, companies use a credit approach for hedging percentages (even if they don’t want to do so), often created by their lender, where hedge volumes are designed to make interest-payment default a very remote possibility. But this wasn’t consistent with our customer’s goal metric. 

Other companies hedge based on “rules of thumb” that are too often mislabeled as “best practices.” Yet, each company’s assets and risk are unique; peer benchmarking is often misleading. They can be so liberal to be dangerous, or so conservative to be costly. Our customer instead wanted to optimize. 

Our customer used AEGIS risk systems to estimate how much cash flow was at risk for every month in the forecast period to determine if there was a correct amount to hedge. 

With this approach, the customer could set two types of goals. The first was their “must-have” level of revenue that barely satisfied investors’ expectations. The second goal was a more aspirational goal as prices fluctuated (higher) and the stretch goal was achievable.