Volatility is back in the European energy market as natural gas prices spike higher, driven by supply constraints, pipeline capacity, and drawn-down reserves, among other factors. Temporary drops in renewable energy generation (for example, caused by a lack of wind), have exacerbated the situation, causing ripple effects into other energy markets. If you have been using a naive model that only tracks the last two years of data, you may have been slow to realize how much is at risk.

Generated using Beacon Plot

Dangers of Extreme Volatility

Big changes in commodity prices can be difficult to manage, triggering strong market movements and knock-on effects in other industries. When these price changes are caused by relative scarcity, strange things can happen. Energy, especially natural gas and electricity can be even more affected due to the complexities of transportation, transmission, and storage in the supply chain. Electricity especially is very difficult to store. The shift away from coal and towards using natural gas turbines to handle surges in electricity demand are compounding the effects.

Energy consumers are essentially short in the market and often have limited options to change their consumption patterns or find arbitrage opportunities in the face of a temporary price spike. Steel plants need to keep the ovens hot, factories need to keep production running, and homes and offices need to keep the heat and lights on. The marginal cost of not doing these things is very high, so those with short-term contracts are forced to pay the spot price, sustaining the demand pressure and fueling higher peaks. Markets at the end of pipelines, like the UK, can be at even greater risk.

Evaluating Portfolio Risk

Stress-testing scenarios, such as Value at Risk (VaR), are useful tools for evaluating portfolio risk, but can miss the potential for a big price hike if the data range is too short or lacks sufficient volatility. Many organizations manage their VaR based on a 1-2 year window, which can diminish the effects of initial price spikes. When testing portfolios that include commodities, it is important to consider longer time periods or additional dimensions. For example, feed in data from a previous time of weather impacts, transportation disruptions, or other price shocks. You can then bring in supplementary market data to get better insight into what can happen to the broader portfolio. Analytics can be modified to include things like natural gas storage, which can be a leading indicator of potential problems if they are low or can mitigate the short-term pain if they are nearly full. Correlations between front month and deferred, between one commodity and another, or across asset classes can change rapidly. Can your risk management system adapt in response to market paradigm shifts?

Hedging Your Exposure

There are a variety of hedging options and short-term opportunities during periods of high volatility in commodity prices, if you have the data and analytics capacity to identify the early warning signs and act quickly. As a corporate energy consumer, supply contracts are an essential tool, enabling you to lock-in forward prices before the rest of the market. As a portfolio manager, you can often find interesting relationships between various commodities, or other energy sources that will react later, creating opportunities for arbitrage or short-term plays. The majority of the market cannot digest all of the information available very quickly, opening windows for those who can explore more data, faster. Similar to concerns about inflation, price volatility and data availability are putting pressure on firms to be more innovative in their use of analytics.

Looking Forward

Some of the price hikes and volatility that we are experiencing in European energy markets right now are due to the transformation of these markets to greater sources of renewable energy generation and a more carbon neutral economy. The decline in coal-fired electricity generation, fewer investments in natural gas storage, and the learning-curve of managing solar and wind power are just a few examples. As we gain experience and capacity in renewables, these big swings in carbon-based energy prices may happen less often. But in the meantime, everybody wants carbons to keep the factories humming and the lights on. Having a broad range of data sources, flexible analytics, and quick access to computing capacity can substantially reduce the energy price exposure in your portfolio or corporate operating plan.