Algorithmic Power Trading and Commodities

Algorithmic Power Trading and Commodities
Blog October 11, 2019

Commodity price movements are increasingly driven by algorithms, pushing traders to adapt and rethink the way they combine information with technology. In recent years, the interest in algorithmic trading has exploded in every sector of the financial market, from stocks to commodities. With the help of real-time data and automated trading, several use-cases listed below show how market participants can trade the spot market in a new fashion.

Spread trading: Trade between two different locations or contracts. For instance, changes in renewable energy feed-in can be anticipated in the day-ahead trade and used for strategic positioning in the intraday market (i.e.: buying Day-ahead and selling intraday). Figure 1 shows the difference between Day-ahead and intraday power prices in Germany for the same hours. For such a trade, a participant could sell the Day-ahead at 71.47 EUR/MWhr and wait until the next day to buy the same hour back at 65.19 EUR/MWhr.

Day-ahead and Intraday prices for baseload German power.
Figure 1: Day-ahead and intraday prices for baseload German power. Source: Genscape

Trading flexibility: Make asset-backed trades by comparing marginal cost to market price due to sudden change in wind and solar production within-day. Power stations use this strategy to optimize their production of flexible assets and a proprietary trading house can generate Profit and Loss. As shown in figure 2 below, Genscape’s PowerRT allows you to see the fuel stack of a country, intraday price, and demand in real-time. The crossing of the demand curve and the supply stack shows the marginal fuel in real time. Combined with intraday price, an asset owner can evaluate whether the marginal costs of production are higher or lower than market price and respectively buy back or sell more power.

Real-time fuel stack for Germany
Figure 2: Real-time fuel stack for Germany, including demand and price. Source: Genscape

Valuing storage: Allows optimization of storage facilities with time-spread trading. In a flexible power station with storage (e.g. pump storage or biogas), a trader can sell an expensive hour and buy back the same volume of another cheaper hour. The hydro plant would provide the expensive power that sold and pump cheap power that’s bought. Similarly, a pumped storage power plant can be used to offset imbalance exposure at the 15-minute level (i.e.: store power if the producer had a positive imbalance or produce power if the producer had a negative imbalance).

In the futures market, most players use unique data and algorithms to manage their hedging programs or mitigate their fuel price risk. There was so much noise that a small edge in fundamentals provided no edge at all. Now that volatility and liquidity are moving to the spot markets, new opportunities arise, as demonstrated by the increasing number of participants as well as the increasing number of initiatives. The Cross Border Intraday project (XBID) will soon face its second wave to include more countries and further integrate intraday markets together.

Algorithmic trading is reshaping the industry and creating new opportunities. The future is digital, and energy commodities are no exception. At Genscape, we use new technology and innovation to provide solutions in the field, and we assist our clients in the industry’s energy transition. To learn more about PowerRT or to request a demo, please click here.