In an era of increasing volatility in global energy markets and declining margins, how do you stay on top of fast-changing market information to manage your risks and make the right trading and strategic decisions? In October, we wrote about how algorithms increasingly drive commodity price movements. Traders must adapt and rethink the way they combine information with technology. In this blog, we will dive a bit deeper to describe why real-time data plays a significant role in automated trading.
Shifting Market Dynamics
The Western European energy markets have experienced significant structural changes over recent years, with this pace of change set to accelerate even further. Significant investments were made in renewable energy generation and capacity management, largely driven by governments recognising the need to alter the dependency on fossil and nuclear fuels. This change in the generation mix has also led to a change in how markets define short-term trading. It used to mean trading months ahead, but now short-term is defined as intraday, leading to the growth of new automated tools to support and keep pace with the demands of this new paradigm.
For example, we are now getting closer and closer to the actual physical delivery of electricity. We often saw a disconnect between the two markets, but nowadays they are increasingly merging together, and the futures price has an even greater impact on the actual physical price of the power. This has caused volumes to grow exponentially in the intraday market in the last few years.
The Power of Real-Time Data
The key to smarter algorithms is data. Today, almost every large company is working on data analytics, and to stand out you need access to unique data. What if you could know in real-time when other companies’ power plants are ramping up or down, or how much power flows from one country to another?
For instance, your forecast may tell you that the wind will blow, keeping power prices low, but frequent congestion may mean that this cheap power can’t flow, resulting in a price increase. Real-time knowledge of the load on transmission lines could allow you to make a better prediction earlier than others in the market.
Another problem is the delay in outage messages. According to our analysis, 92 percent of outage messages are sent late. Let’s say a nuclear plant has an unplanned maintenance outage but doesn’t send a notification until several hours later. If you were aware of their ramp-down in real-time, you would have hours of advanced notice and be able to predict a rise in prices, giving you a huge advantage in the intraday market.
Algorithmic trading is reshaping the industry and creating new opportunities. Smarter algorithms need smarter data, and energy commodities are no exception. It is possible now to get this and more valuable data in real-time. Unique data gathered from infrared cameras, electronic magnetic field monitors, drones, planes, and more enables unprecedented transparency into the current state of energy supply, transmission, storage and demand.
Traded Volumes are Moving Closer to Real-Time
In the futures market, most players use unique data and algorithms to manage their hedging programs or mitigate their fuel price risk. 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 Single Intraday Coupling project (SIDC, formerly known as XBID) is planning a third wave to include more countries and further integrate intraday markets together.
Algorithmic trading is reshaping the industry and creating new opportunities. At Genscape, we continue to use new technology to assist our clients in the industry’s energy transition. To learn more about our offerings or to request a demo, please click here.