By Amol Dhargalkar, Chatham Financial
With FX and IR risk-management programs in place, treasurers are now turning their attention to managing commodity risk.
After many years of investing in tools, processes and technology, many multinationals have become increasingly confident in their hedging programs to manage currency or interest rate risk. The recent extreme volatility experienced by the financial markets has underscored the importance of implementing such programs, which many firms are using to weather the seemingly endless crises across the globe. But financial risk does not stop at just currency or interest rate risk, and some of the more sophisticated treasurers are now turning their attention to the management of a different risk: commodity risk.
The best-in-class treasuries are using sophisticated Monte Carlo methodology to incorporate commodity risk in their hedging programs, thus allowing them to maximize hedging efficiency. But it’s not easy, and requires an ongoing organizational commitment to risk measurement and management. The benefits of evaluating a portfolio of currency and commodity risks can be significant—it can save a firm from hedging the wrong exposures and thereby increasing risk.
Risk Management Framework
A common framework for risk management involves firms following the steps
listed below. And while each step will look different for each firm, the broad objective is the same—to effectively measure and manage financial risks across the entire business. The framework is general enough for firms focused purely on currency risk alone, but for MNC manufacturers or others with significant input costs tied to commodities, the functional differences lie in steps 1, 2 and 4.
1) Identify exposures. This is often the most challenging task when creating a hedging program especially for large organizations with multiple risk exposures.
As with currency exposure, commodity exposure can sometimes be very clear. But mostly it is far from obvious. Many firms have exposure embedded within components. Alternatively, what may seem like a commodity exposure may not truly be linked to any financial market, such as fuel surcharges, which rarely go down when the price of oil drops. Finally, you may think you have exposure to a commodity input when in reality your purchasing managers may have already negotiated long-term, fixed-price supply contracts.
We recommend putting together a multi-functional team to identify these exposures. This can help treasury better understand and translate exposures into a model that can convert underlying currency and commodity price volatility to changes in earnings or EBITDA.
2) Quantify risks. The next step is to assess the impact of movements in the market on key metrics such as EBITDA, earnings, or operating margin. There are a number of ways to do this, from a simple static shock of some percent to a single variable to Monte Carlo simulations.
Using Monte Carlo simulations is similar to observing a million possible combinations of underlying variables. Included in the combinations are scenarios that most would never even envision, such as the price of gold going to either $500 or $3,000 in the next year. These extreme events are properly weighted based on the current market expectations and volatility. In addition, all of the variables must be correlated to one another based on either historical or future expectations of how the variables move in relationship to one another.
3) Compare to risk tolerance. Next, compare the results from Step 2 to a risk tolerance level. Embedded within this step is a need for firms to clearly state their hedging objective: which metrics matter most? Does EPS matter more than cash flow? Are you in an industry where margin percentage is scrutinized far more than any other metric? Firms will often try to reduce volatility across multiple metrics rather than just a single metric. Understanding what matters and how much risk to take on is critical in developing a robust risk management program.
4) Determine optimal risk reduction strategy. This can provide the most “bang for the buck.” Certainly, hedging all of a firm’s exposures would reduce volatility the most, but for many firms, the cost of doing so can outweigh the benefits. To determine an optimal risk reduction strategy, consider the most significant exposures to the firm—should it hedge diesel first, or EUR exposure first?—and make clear risk reduction decisions based on a hierarchy of risk contributors. The goal is maximizing the amount of risk reduction while minimizing the cost of hedging.
Once the order of risks is identified, decide on the best approach for each individual risk. For example, when hedging in certain less-liquid commodity markets, hedging with suppliers may be preferable to hedging with financial derivatives because there may not be a financial derivative that matches the underlying risk. In some cases, however, a supplier may not be able to provide efficient pricing and a firm may be willing to take some “basis” risk on its financial hedge in order to lock in better pricing through derivatives.
5) Evaluate and repeat. Risk management is not a one-time event. Smart firms continuously evaluate their risks and adjust hedging programs to take into account new information. Without consistently evaluating and repeating a risk management process, firms can fall victim to timing the market instead of consistently applying a trusted methodology.
A Simple Case Study
Figure 1 to the right is a sample output for Global US Firm (GUS). GUS faces significant fuel and currency exposures shown in Figure 1. GUS wants to understand what level of hedging it should employ to reduce the risk around their USD operating income. The company currently doesn’t hedge any of its risks under the belief that its risks are “naturally hedged” against one another. This is a large firm that faces significant overall risks and at first glance, one would assume that the currency exposure is as significant as the fuel risk based on the Operating Income total.
The outputs of the Monte Carlo analysis are provided in the three-dimensional graph in Figure 2 below. The independent variables are the percent of fuel exposure and percent of currency exposure hedged. The dependent variable (z axis, going straight up) is the Cash Flow at Risk for a given level of hedging. Specifically, this is the difference in USD operating income between the average and the worst case scenario (a 2-standard deviation move). The graph tells GUS how wide the distribution of outcomes could be between what they expect (the mean) and what could happen (the 2 standard deviation move)—the lower the number, the lower the risk. The point of least risk is at the intersection of the two axes. When both risks are hedged 100 percent, there is no Cash Flow at Risk. The color gradients on the chart indicate “buckets” of risk. For example, blue indicates that the Cash Flow at Risk is between $0 and $100mn, while red indicates the Cash Flow at Risk is between $100mn and $200mn. The edges of the plane represent extremes in the hedging scenarios—either 100 percent of currency or 100 percent of fuel hedged.
What are the key conclusions from all of this analysis for GUS?
1) GUS is not “naturally” hedged as it still faces significant risk that operating income could be materially lower than expected due simply to fuel and currency movements. Without adding any additional hedges, at the 0% Fuel Hedged and the 0% FX Hedged, GUS has almost $500,000 of Cash Flow at Risk.
2) The easiest way for GUS to reduce its risk is to implement a fuel-hedging program. Hedging currency exposure alone may increase their overall exposure.
3) At certain fuel hedging levels, the most effective way to reduce risk is to hedge currency and fuel simultaneously.
4) There is such a thing as “too much” hedging, at least when looking at only hedging fuel exposure.
While it may be difficult to execute, bringing in commodity risk to an existing currency risk management program can lead to new insights and significantly improve the manner in which firms are able to manage their financial risks. For some firms, focusing on currency risk alone may lead to sub-optimal risk management decisions.
Ultimately, as commodity risk management increases across an organization, the treasury team must be ready to implement robust processes to incorporate this risk into its existing programs.