Statistical Models Provide a Better Approach to Energy Hedging

When it comes to implementing a hedging strategy to manage energy risk remember that it shouldn’t be looked at as a source of revenue. An effective energy hedging program should provide clear benefits like revenue certainty, cost certainty, forecastable profit margins, and an insurance against both increasing and decreasing prices. These benefits are true for consumers, marketers, producers, and refiners.

Most of the energy hedging mistakes are due to the poor or nonexistent energy hedging policies or absence of a good hedging strategy. Such mistakes are avoidable if you take time and effort to formulate a good hedging policy and implement an energy risk management strategy that will enable you to meet your hedging goals, objectives, and risk appetite.

Relying on a Statistical Model Is Better Approach to Energy Hedging

Any good hedging strategy becomes more effective if it is based on the statistical model. This approach gives you access to scientifically analyzed data, which allow a better understanding of the energy market’s price risks. By using the statistical approach, you will make sure the hedging decisions you make are spot on.

Creating an Effective Energy Risk Management Strategy

You have to have a strategy or a set of strategies i.e., forward contracts, futures, swaps, and options that can address all of the relevant risks. That strategy/s should establish your risk management goals and objectives, along with your risk tolerance, and risk appetite. Your energy risk management strategy which is also called an energy hedging strategy should be developed to give your goals, objectives, risk tolerance and risk appetite a formal look.

While most companies have different exposures to price risk, companies involved in commodity transactions like natural gas and crude oil can manage their risks in an efficient way if they have a good hedging strategy that accounts for their goals, objectives, and risk appetite. Here a statistically based hedging product can deliver the goods for you. Such a product will identify when to hedge, which maturity to use, how to scale in, and when to restructure and will be very useful for investors and traders, involved in buying and selling of energy commodities. It will in fact help in mitigating their risk exposure.

Analyzing and Tracking Hedges

For most energy commodities traders and investors the execution and management of hedges have to be a dynamic process, instead of a static process. In that capacity, existing and potential hedges have to be continually analyzed (i.e. week by week or month to month) to guarantee your positions are within the set rules of your hedging strategy. Also, you must make sure that hedges will fulfill our goals and objectives. A statistically based hedging strategy provides an easy way for on-going analysis of your hedges.

Conclusion

Creating and implementing an effective energy hedging strategy demands the use of a statistical model. Most importantly it makes you confident about your hedging decisions.