Over the past few years, we have seen the price of crude oil drop from over $100 per barrel to less than $30 per barrel and natural gas fall from over $6.00 per MMBtu to less than $2.00 per MMBtu. Crude prices are on the rise again, and natural gas sits on the edge of a knife ahead of this winter. The constant upward and downward price movements expose both producers and consumers to risk. How would you know if the prices of crude or natural gas have bottomed or peaked in the near future? There is always an element of risk, and in worst case scenarios, those risks can serve as a cruel blow to your operational profitability. This is where energy hedging is seen as a viable way to mitigate risk in highly volatile markets.
More and more businesses in the energy sector are looking at hedging as the best way of shielding themselves against the risks of these highly volatile commodities. With the help of statistical modeling and well thought out risk management plans, producers and consumers have taken to hedging to protect against violent swings in the cost of energy. Given the fact that every business has different goals and risk appetites, an accurate advisory from an energy hedging consultant can help in determining whether their energy hedging goals are achieved.
Statistical Modelling and Hedging
Effective hedging programs used to mitigate the risk of a company’s underlying energy costs aim to lock in energy prices over the course of months or even years when attractive pricing opportunities present themselves. Most think that a long-term energy forecast is a solution. However, they are wrong. In chaotic data series, like those generated by energy prices that have so many moving parts and factors that drive prices up and down, short-term forecasts work but long-term forecasts do not. In this case, long-term is defined as more than three months (so not too long by many standards). The challenge is there is too much that can change over the course of time that could or will drastically change the course of prices. Therefore, the longer the forecast, the more inaccurate it will be.
At best, we can make educated guesses about the long-term price of energy. Therefore, the best solution in this type of chaotic data series is the use of statistical models that identify and take advantage of long-term price cycles. A model like this can then be used to identify periods of high, neutral, and low prices. Strategies for producers and consumers can then be built around a company’s risk appetite that uses these cycles to time hedges.
Hedging Strategies Using Statistical Models
A successful hedging program built around a statistical model must be well planned and address a company’s unique goals and risk appetite when it comes to energy prices. Every company will approach hedging in a different manner, but the plan to hedge using the statistical model can be adapted to mitigate risk in different manners. For instance, a company that is hedging to protect a budgeted energy price has a much different set of goal than a company that is looking to lock in the best energy price possible.
Therefore, it is important to work with an energy consultant to identify your company’s goals and risk appetite so that they can help you to design a program that will best suit your needs.