Quant strategies to weather volatile energy markets

Quant strategies to weather volatile energy markets

15 December 2021
by Markus Allard, Product Director

Find out how to build effective, quantitative energy hedging strategies during volatile market conditions.

European energy markets have seen almost two years of unprecedented volatility. Liquid natural gas (LNG) supply is constrained and demand is increasing as developing markets are rebounding from Covid restrictions. At the same time, intermittent drops in wind power generation have led to increased volatility in renewable energy pricing, while hydropower dams have slowed down power production in Northern Europe, to allow water in dams to freeze before ramping up production.

Moreover, discussions during COP26 have indicated that the future of gas and oil prices will be increasingly influenced by the volatile supply of renewable energy.

WTI and Brent Crude Price Series

Long or short energy

How you react to the increased volatility will depend on your role in the marketplace. The energy market can broadly be divided into producers, consumers and traders. Producers are producing energy commodities and are, by default, long the underlying commodity. This leads to volatility exposure and lower energy prices in the future. Producers typically run hedging programs to mitigate some of this risk.

Consumers include companies and households that consume energy. Consumers are naturally short energy as they need to satisfy their energy needs at future energy prices. This can lead to the inflation of energy costs for households and also impacts businesses. For instance, the United Kingdom has seen an increase of the number of bankruptcies of energy suppliers. It’s therefore critical for consumers to run cost-effective hedging programs to avoid exposure to rising energy prices in the future and to protect their businesses against future volatility.

In between consumers and producers are independent energy traders. These companies generally try to capture alpha in the markets and act as intermediaries between producers and consumers. Sometimes energy traders will own the infrastructure (refineries, oil and gas wells) and sometimes buy capacity where they see opportunities. Energy traders thrive on volatility because it presents opportunities for alpha creation. In order to capture these opportunities, it’s crucial that traders thoroughly analyze data to produce well researched quantitative strategies.

Traders need powerful tools to research and analyze the impact of volatility drivers such as unpredictable weather patterns, Brexit uncertainty and geopolitical tension, among others. In addition, vast amounts of new alternative data sources are coming to market frequently, creating a further need for quantitative analysis tools.

Producers and suppliers that are looking to hedge volatile prices via gas and energy futures are also presented with challenges. With the oil futures curve in backwardation, rolling the futures front month is becoming more costly.

Henry Hub Natural Gas Price Series

Incorporating transaction costs

When creating active hedging programs, it’s imperative to take into account transaction costs. If not executed correctly, gains designed to offset losses in the physical market can be erased by transaction costs, leaving hedging programs ineffective and missing opportunities in alpha generation. Portfolio managers need a granular and accurate view, down to individual orders of the transaction costs for each of their strategies.

The ability to incorporate key attributes of individual trades such as bid-ask spread, volatility, volume and the forecasted market impact into the backtest are critical to understand the projected cost of your strategy. Modelling for trading costs is also valuable for strategies in production to determine the slippage between the backtest model assumptions and the live production environment, as well as having a better understanding of its causes.

Here is an example backtest of a Brent crude oil rolling futures trading strategy using US PMI data as input signal:

Backtesting a quantitative energy hedging strategy


Previously, portfolio managers had to individually, and correctly, incorporate the relevant costs into their research and backtesting process. Now new technologies such as SigTech can provide the required level of detail and accuracy using calibrated transaction cost functionality that also integrates with proprietary TCA models and data.

Volatile energy markets are here to stay and those who have the tools and know-how to rapidly onboard vast, new data sources, effectively backtest their hedging strategies and deploy without delay, will have a clear advantage.

Interested to learn more? Watch the video below and discover how to build effective energy hedging strategies, using the SigTech platform.

Estèphe Corlin, Product Manager at SigTech, demonstrates how to build an options hedged Brent crude oil strategy.


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