3 Common Mistakes in Layered Hedging: Why Your Hedging Strategy Fails

A hedging program can be a powerful tool for businesses seeking to maintain stable pricing in the face of fluctuating currency markets. By strategically layering hedges over time, companies can mitigate the impact of adverse FX movements on their bottom line.

However, to fully harness the potential of layered hedging, it's crucial to avoid common misconceptions and pitfalls that can hinder its effectiveness.

In the introductory blog of this series, we asked ourselves the question: What are the pricing characteristics of companies that need layered FX hedging programs? We saw that firms that require continuity in pricing are best suited for these types of hedging programs.

This is because layered hedging makes it possible for managers to keep prices as steady as possible, for as long as possible, without hurting budgeted profit margins—even in the face of adverse movements in currency markets. 

Before tackling the nuts and bolts of an effective FX layered hedging program in our next blog, we need to clarify some of the most common misconceptions and/or suboptimal practices that hinder the effectiveness of these programs. These include: 

• Confusing layered hedging and rolling hedging

• Disregarding constraints faced by treasurers

• Lacking the necessary flexibility to react to FX markets

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Layered hedging and rolling hedging

Companies that desire to keep prices steady for as long as possible will naturally use some form of continual or rolling budget. This allows them to project the FX-denominated budgeted revenues and/or expenditures that make up the firm’s exposure to currency risk.

At this point, a couple of clarifications are in order. As we will see in more detail in our next blog, layered hedging works by ‘building’ the FX rate in advance as successive layers of hedges are applied to forecasted exposures.

As layers of hedges are executed, different value dates mechanically share some trade dates (and spot rates) in common. This commonality allows treasurers to ‘smooth out’ the hedge rate over time, making it possible for the firm to keep prices as steady as possible.

Why do we emphasise this point? Because we are keen to make a distinction between this mechanical smoothing and what we call ‘fake smoothing’ and ‘statistical smoothing’. Fake smoothing describes the improbable situation of a treasury team that executes, right at the start of the program, an FX hedge with a very long maturity.

Quite apart from the fact that this ignores the weight of constraints —in particular, the degree of forecast accuracy and the possibility of executing forward contracts with a very long maturity—, the treasury team would find itself at the mercy of FX markets as soon as the hedge matures. In other words: there is no smoothing effect at all.

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‘Rolling hedging’ programs are more common. Here, several periods are hedged at different trade dates. Depending on how markets move, these trade dates may or may not share a similar spot rate. In other words: commonality between hedge rates can be obtained, but this would be on a statistical —as opposed to systematic— basis.  

Constraints

In real life, treasury teams have to face a number of practical constraints. Inevitably, these limitations contribute to the final shape of the FX hedging program that is adopted—and this can lead to discrepancies between desires and reality. The two major constraints include: 

• The degree of forecast accuracy

• The maximum trade length authorised by banks

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The degree of forecast accuracy depends, quite naturally, on each business model. German sportswear company adidas, for example, has long-term contracts with its manufacturing partners. Some of these contracts have a tenure of more than 20 years. This makes it relatively easy to project the firm’s long-term exposure to currency markets.

Changes in business models can affect forecasting accuracy. Take aquaculture. Citing an FAO study, the Financial Times notes that "the amount of fish farmed globally just surpassed the wild catch. In 2022, 94.4m tonnes of fish were farmed in pens and ponds, vs 91.0m tonnes in open water." Clearly, some of the companies involved will gain a lot in terms of forecast accuracy.

And that’s not all. In corporate forecasting, advances in AI and AI-generated ‘nowcasting’ techniques are making strides. While some of these are quite spectacular [see], the reality is forecast accuracy will inevitably constrain the capacity of the finance team to come up with perfectly reliable long-term projections for FX-denominated future cash flows. 

Finally, the implementation of a layered hedging program has to contend with the fact that a firm’s banking partners may set a maximum trading length, presumably per currency pair. This consideration may clash with the treasury team’s ability to set up its layered hedging program and must be taken into account. 

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Insufficient flexibility in the face of FX markets opportunities

As we will discuss in detail in our next blog, layered FX hedging programs are ‘time-driven’. The schedule of hedges is known in advance and has to be executed according to a predetermined calendar of trades. But ‘market-driven’ elements can be introduced to reduce costs and/or to profit from favourable moves in currency markets.

One example is the automatic monitoring of FX markets for individual layers, using conditional orders to reduce the financial impact of unfavourable forward points. We can go one step further. Technology makes it possible for finance teams to fine tune their layered hedging program to take advantage of favourable moves in exchange rates by altering the length of the program or the desired hedge ratio by currency pair:

This is accomplished by applying different ‘partitions’ to the hedging program, allowing the appropriate software solution to monitor FX Markets 24/7 to automatically increase hedge duration or hedge ratios whenever currency markets move in a favourable direction. 

While highly valued by corporate customers, this flexibility is lacking in most layered hedging programs. And here’s precisely where Currency Management Automation comes to the rescue. 

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