Energy Risk Management: Five Steps to Improve Your Process

Choose the right risk metric.

Energy portfolios vary greatly from company to company and location to location.  No two energy portfolios are the same, and risk management strategies must be tailored to the unique risk factors of each portfolio.

Many companies use a traditional Value-at-Risk (VaR) metric to report risk to their Board and to highlight risk to the portfolio in quarterly financial reports.   But what action does your organization actually take if your VaR goes up by 25% in one week?  If you don’t have a great answer, VaR may not be right for your portfolio.  At cQuant.io, we use both VaR and Cash Flow at Risk (CFaR) methodologies to assess and report portfolio risk, depending on the type of portfolio and the goal of the risk reporting.  Here is a simple comparison of the two:

Which is more appropriate, VaR or CFaR?

• VaR is a risk metric that provides not only the value the portfolio could lose over a given time interval in a “worst case scenario”, but also a measure of the statistical confidence around that estimate. For example, computing the VaR for a large portfolio of financial contracts may suggest there is a 95% chance that portfolio will not lose more than $1M over the next 5-day period.  VaR is most appropriate for assessing risk over short time periods (less than one month), particularly for positions that can be unwound in a few days.
• CFaR is a more appropriate risk metric for companies with physical assets, customer load or complex structured transactions.  These types of portfolio elements cannot typically be sold or significantly modified in response to short-term market moves. CFaR provides a detailed analysis of cash flows through time based on many simulations of possible future states (more on simulations in item #3). The result is a distribution of future value and costs for any time bucket (day, week, month or year) on any portfolio item (gen asset, storage, customer, deal, commodity, counter-party), or for the portfolio as a whole.  The results can be proactively used to reduce risk, lower cost and improve portfolio performance.
• Why use both?  Many energy portfolios contain both long-term and short-term assets.  Using both CFaR and VaR can provide advantages for more diverse portfolios.  Additionally, more sophisticated VaR models allow users to slice through portfolio dimensionality to report net position by commodity, value at risk by trader or counter-party, and other useful metrics that can be used to surgically target and mitigate risk from specific portfolio components.  Taken together, combined VaR and CFaR analysis can enhance active risk and portfolio management.

Choose the right risk factors.

What is driving the risk to your particular portfolio?  Price volatility, weather uncertainty, basis risk, customer migration, congestion, government policy or regulation?  Understanding the underlying “risk factors” in your portfolio is crucial to modeling your risk appropriately.  As your portfolio responds to changes in energy markets and supply/demand dynamics, even the sharpest intuition can mis-identify the riskiest portfolio elements.  A good risk management process can help keep the focus on what poses the greatest threat to your company financials.

Choose a Great Simulation Model.

It seems that everyone has a simulation model these days.  At the simplest level, these are Excel plug-ins, closed form models or a bunch of legacy code from some analyst that used to work at your company.  Here is the danger – a poor simulation engine can be much worse than having nothing at all.  At least when you have nothing, you know it.  A poor model may add uncertainty in a way that is not market-consistent, may misrepresent important relationships between related commodities (e.g., correlation between power and gas prices), or may simply drift out of calibration as market conditions evolve.  Inaccurate simulations can result in actions that are completely inappropriate for your real risks.  Its important to validate any simulation model against actual market data regularly to ensure it’s doing its job.

Include everything in your model. 

Too many companies get lazy with this.  “My model includes about 90% of our portfolio, but the more complex transactions we value in a separate process.”  It may be the case that those exotic transactions are driving an outsized portion of your risk!  Recognize that big risks can come in small packages and allocate staff (or vendor) time to include all transactions into your model to get a comprehensive and accurate risk analysis.

Turn results into actions. 

Surprisingly, this is the most common gap.  Perhaps you have done all the hard work to set up a comprehensive risk management system, but the results still aren’t affecting real portfolio decisions.  Try holding monthly risk committee meetings that include your financial, trade and asset managers along with at least one C-suite sponsor.  The volatility in energy markets is the risk manager’s best friend.  The next Polar Vortex or Bomb Cyclone is lurking just around the corner.  Eventually, you’ll be able to say, “I told you so”, and win the day.

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This article was written by David Leevan. David is the Managing Director of cQuant.io, a SaaS platform for energy analytics.