At Brady, our commitment to advancing algorithmic trading technology for short-term power markets is evident through the development of our pioneering solution, PowerDesk Edge. We have recently partnered with Reactive Technologies, a leading provider of grid measurement tools, on a research initiative to explore how traders achieve high ‘alpha’ returns in continuously changing market conditions through the integration of our solutions.
PowerDesk Edge underwent extensive testing, employing Reactive Technologies’ sophisticated grid signal detection technology to simulate trading strategies. Strategies were measured against market average returns to measure the effectiveness of Reactive/Brady automation.
We are delighted to announce a rigorous academic review of this work has been published in Risk.Net’s prestigious publication, Journal of Energy Markets.
The context
When supply (generation or interconnection) does not meet demand (customers usage), the frequency of the transmission system changes. Similarly, when there is a sudden change to planned generation or consumption, market prices typically move as the marginal cost of generation shifts. We have used this correlation (whereby a single event impacts a physically measured characteristic, i.e. frequency as well as traders prices) to employ an automated trading strategy.
Trading on Grid events using PowerDesk Edge
PowerDesk Edge stands out for its ability to integrate a diverse range of external data into its decision-making process, from weather-related information to advanced machine learning models. Our study focused on utilising signals related to grid events (provided by Reactive), to determine PowerDesk Edge’s potential for profit maximisation. PowerDesk Edge is based on pythonic libraries whereby algos are coded at the command line and not through a GUI. This means that Brady’s data scientists had far greater influence on the exact characteristics of the algos created, hence could create more exotic trading strategies.
Study results
Our analysis showed that PowerDesk Edge, combined with a grid event input signal, significantly outperformed the market. Even after accounting for real-life latencies and technological constraints, we calculated the ‘haircut’ and found that PowerDesk Edge exceeded the market by statistically significant margins.
Implications of the study
This study underscores PowerDesk Edge’s capability to enable energy traders to realise their profit potential. By incorporating new data sources and having the flexibility of our python approach with an in-built back testing engine, PowerDesk Edge equips traders to maintain a competitive edge in the fast paced short-term power trading arena.
