Insight into this activity was provided by explanatory market survey (the ACM Study) conducted by the Netherlands Authority for Consumer and Markets (ACM).
In broad terms, an algorithm (or algo) is a series of mathematically rigorous instructions in a computer program, typically used to solve a class of specific problems or to perform a computation.
At a high level, algorithmic or algo trading involves the use of computer algorithms either to execute trades or generate trading 'signals' indicating which trades to execute based on predefined criteria, such as timing, price and volume. These algorithms may process vast amounts of data in real time, allowing traders to capitalise on market opportunities that might be missed through manual trading. Some participants use purely algo strategies, while others use algos in conjunction with human trading.
The ACM Study identifies three types of algorithms used in power and gas trading:
The results of the ACM Study indicated that in the natural gas market, execution algorithms are more frequently used than signal generators and trading algorithms. However, all three types of algos are used to a similar extent in the power market.
The use of algorithmic trading in the power and gas markets has been growing and is expected to develop further with an increasing number of market participants using algos. The ACM Study indicates algo trading is particularly prevalent in the short-term power markets.
Why is the use of algo trading growing in power and gas markets?
There are several underlying reasons for the growth of algo trading, set out below:
Uses of algos
The increasing complexity of inputs into price formation and the need to execute trades more quickly both favour the use of algo trading.
Although algo trading in the power and gas markets offers a range of benefits for participants, there are significant risks and challenges. These include:
Regulatory responses to algo trading: The EU and UK
MiFID II
Algo trading first developed in financial markets and the first regulatory responses to the activity occurred in the regulations governing those markets, especially MiFID II. MiFID II is a comprehensive regulatory framework for investment services and activities when performed in relation to financial instruments.
Article 17 of MiFID II sets requirements on investment firms engaging in 'algorithmic trading' to have in place effective systems and risk controls suitable to their business and are subject to appropriate trading thresholds and limits. In addition, firms engaging in algorithmic trading must notify their national competent authority (e.g., the FCA in the UK) and provide detailed information about the trading strategies and the types of instruments traded. Finally, MiFID II requires that a firm's trading systems are resilient and have sufficient capacity in accordance with chapter II of the EU's regulation on digital operational resilience for the financial sector (DORA). The requirements of Article 17 are supported by more detailed requirements set out in regulatory technical standards (RTS) on the requirements of investment firms engaged in algorithmic trading (2017589/EU) (RTS 6).
RTS 6 sets detailed requirements relating to the governance and control of algorithmic trading, the testing and deployment of trading algorithms, systems and strategies, as well as their management, monitoring and control after they have been deployed.
MiFID II and RTS 6 will be directly relevant to trading in power and gas futures but not to short-term physical trading. That said, as the ACM Study notes, many physical market participants have established compliance frameworks aligned with these standards.
Furthermore, those engaging in 'high-frequency algorithmic trading' (HFT) in financial instruments cannot rely on the exemptions from MiFID II that may be relied on by commodity or energy traders (e.g., the ancillary activities exemption). MiFID II defines HFT as an algorithmic trading technique characterised by:
a) infrastructure intended to minimise network and types of latencies, which must include at least one of the following facilities for algo order entry: co-location, proximity hosting or 'high-speed direct electronic access';
b) determination by the system (without human intervention) of order initiation, generation, routing or execution; and
c) high message intraday rates (for orders, quotes or cancellations).
REMIT and REMIT II
The EU's Regulation on Energy Market Integrity and Transparency (REMIT) sets requirements relating to the disclosure of inside information, prohibition of insider trading and market manipulation, and the reporting of orders and transactions in gas and power markets. In its original 2011 guise, REMIT did not set any specific requirements relating to algorithmic trading.
Recently, REMIT was extensively amended by REMIT II, which introduces for the first time requirements relating to algorithmic trading that are specific to power and gas markets, among other things.
Article 5a of REMIT II sets very similar requirements for market participants as apply to investment firms under Article 17 of MiFID II. However, there is no mandate under REMIT II for delegated legislation to be issued to supplement Article 5a in the same way that RTS 6 supplements Article 17. As the Article 5a standards are drafted at a high level, there is the potential for this to introduce some uncertainty into the concrete steps that must be taken to meet these standards. While this may be addressed by guidance from ACER, we can expect that market participants will use RTS 6 as a benchmark for designing their systems and controls relating to algo trading.
The AI Act
The EU's AI Act seeks to regulate the use of AI across different uses, including its application in algorithmic trading within power and gas markets. The provisions most relevant to algo trading are summarised below:
United States - Regulation
The United States does not have the same type of prescriptive rules related to the types of algorithmic trading typically used in the power and gas markets. For example, neither the Commodity Futures Trading Commission (CFTC) or the Federal Energy Regulatory Commission (FERC) have licensing requirements related to the use of algorithmic trading strategies in their markets.
The CFTC does impose requirements on futures exchanges related to the prevention of market anomalies and disruptions caused by algorithmic trading, but this is generally seen as codifying risk control requirements that futures exchanges already had in place. Specifically, the CFTC requires U.S. futures exchanges to: (1) implement rules designed to prevent, detect, and mitigate market disruptions and system anomalies associated with electronic trading; (2) implement pre-trade risk controls for all electronic orders; and (3) promptly notify the CFTC of any significant market disruptions on their electronic trading platforms.
However, market participants using such strategies are responsible for the trading activity conducted by such programs, and many CFTC and FERC enforcement actions relate to automated trading programs that violate regulatory requirements (e.g., spoofing). Additionally, respondents in such enforcement actions (and disciplinary actions from futures exchanges) are often charged with a failure to supervise.
Separately, certain U.S. futures exchanges have certain technical requirements related to algorithmic trading, which are important to understand. For example, certain futures exchanges require automated trades to be reported with specific identifiers, or tags, indicating that they were executed via an algorithm rather than manually. Other rules may require traders executing manual and automated trading strategies to use different tags identifying the trader and whether the trade was executed manually or via an algorithm.
Final Thoughts
The use of algorithmic trading in power and gas markets is likely to continue to increase, as it can bring significant benefits to market participants. However, it can also carry significant risks. Regulators have responded to these issues in a variety of ways, and we expect further regulatory and legislative change, especially as AI and machine learning are deployed in connection with algorithms.