Algorithmic Trading and Market Abuse Regulation: Evolution or Revolution in EU Financial Markets Law

Abstract

This Student Voice article examines whether the European Union’s regulatory framework has evolved sufficiently to address the risks associated with algorithmic trading in modern financial markets. Automated trading systems have transformed the speed and complexity of trading activity, raising significant challenges for regulators tasked with protecting market integrity. This piece analyses the interaction between algorithmic trading and the European Union’s market abuse framework, focusing primarily on the Market Abuse Regulation and the Markets in Financial Instruments Directive II. It argues that while these instruments contain technology neutral provisions capable of capturing certain forms of algorithmic manipulation, they largely extend existing legal principles rather than fundamentally transforming the regulatory structure of financial markets. The article concludes that the European Union’s response to algorithmic trading reflects a process of regulatory evolution rather than revolutionary change.

Introduction

Article 15 of Regulation (EU) No 596/2014 on market abuse (“MAR”) provides that “a person shall not engage in or attempt to engage in market manipulation.”¹ This provision forms a central component of the European Union’s regulatory framework governing financial markets and reflects a broader objective of protecting market integrity and investor confidence. The prohibition is reinforced by Article 12 of MAR, which defines market manipulation broadly as conduct capable of giving false or misleading signals as to the supply, demand or price of a financial instrument.²

Despite the breadth of this framework, the structure of modern financial markets has evolved significantly. In particular, the rapid growth of algorithmic and high-frequency trading has transformed both the speed and scale at which trading activity occurs. Under Article 4(1)(39) of Directive 2014/65/EU on markets in financial instruments (“MiFID II”), algorithmic trading refers to trading where a computer algorithm automatically determines individual parameters of orders, including timing, price or quantity, with limited human intervention.³

Algorithmic trading technologies now account for a substantial proportion of trading activity across major European financial markets. While such systems may enhance liquidity and contribute to more efficient price discovery, they also create opportunities for manipulative trading strategies. Practices such as spoofing and layering involve the placement of orders that are intended to be cancelled before execution in order to distort market perceptions of supply and demand.⁴

Although the Market Abuse Regulation provides a broad and formally technology-neutral framework capable of capturing certain forms of algorithmic market manipulation, the speed, opacity and scale of automated trading expose significant enforcement challenges. These developments raise an important question for contemporary financial regulation: whether the European Union’s regulatory framework has evolved sufficiently to address the risks associated with increasingly automated financial markets.

This article argues that while recent legislative instruments including MAR, MiFID II and the Digital Operational Resilience Act (“DORA”) represent important regulatory developments, they largely extend pre-existing legal principles rather than fundamentally transforming the structure of financial market regulation. The development of European Union financial market law can therefore be understood primarily as a process of regulatory evolution rather than regulatory revolution.⁵

Algorithmic Trading and the Transformation of Financial Markets

Algorithmic trading has become one of the defining characteristics of modern financial markets. MiFID II recognises this development explicitly by providing a legal definition of algorithmic trading and imposing regulatory obligations on firms that engage in such activity.⁶ High-frequency trading represents a specialised subset of algorithmic trading characterised by extremely rapid order submission and cancellation using advanced technological infrastructure.⁷

Supporters of algorithmic trading frequently emphasise its potential benefits for financial markets. Automated trading systems may enhance liquidity by increasing the number of market participants and facilitating faster execution of trades. Empirical research also suggests that algorithmic trading may improve price discovery by enabling markets to incorporate new information more rapidly.⁸

However, the same technological capabilities that improve market efficiency may also facilitate new forms of market manipulation. One widely discussed example is spoofing, whereby traders place large orders with no intention of execution in order to influence the behaviour of other market participants.⁹ Once the market price moves in a favourable direction, the orders are cancelled and the trader executes genuine transactions at the manipulated price.

Layering represents a related strategy involving the placement of multiple non-genuine orders at different price levels in order to create a misleading impression of market demand. These strategies are particularly difficult to detect when implemented through automated trading systems capable of generating thousands of orders within milliseconds.

The increasing prevalence of such strategies illustrates the broader challenge facing financial regulators. Legal rules that were originally designed to regulate human trading behaviour must now operate within markets increasingly dominated by automated systems operating at speeds far beyond direct human supervision.

Market Abuse Regulation and Technological Neutrality

The Market Abuse Regulation represents the primary legislative instrument governing market manipulation within the European Union. Article 12 of MAR defines market manipulation broadly to include transactions or orders that give false or misleading signals regarding the supply, demand or price of financial instruments.¹⁰

Importantly, MAR adopts a technology-neutral regulatory approach. Article 12(2)(c) explicitly recognises that manipulative conduct may occur through algorithmic or high-frequency trading strategies where such behaviour disrupts trading systems or creates misleading market signals.¹¹

This drafting approach reflects a deliberate attempt by European Union legislators to ensure that market abuse rules remain applicable regardless of the technologies used to execute trades. By focusing on the effects of trading behaviour rather than the specific technological mechanism employed, the regulation seeks to maintain its relevance within rapidly evolving financial markets.

Nevertheless, the practical enforcement of these provisions remains complex. Algorithmic trading systems frequently operate simultaneously across multiple trading venues and generate extremely large volumes of trading data. Detecting patterns of manipulation within such environments requires sophisticated market surveillance technologies as well as specialised regulatory expertise.

Recognising these challenges, the European Securities and Markets Authority (“ESMA”) has emphasised the importance of strengthening supervisory capabilities among national competent authorities and developing technological tools capable of analysing high-volume trading data.¹²

Preventative Regulation Under MiFID II

Alongside the prohibition of market manipulation under MAR, MiFID II introduced a range of preventative regulatory safeguards designed to address the operational risks associated with algorithmic trading.

Article 17 of MiFID II requires investment firms engaging in algorithmic trading to implement effective risk controls designed to ensure that their trading activities do not contribute to disorderly markets.¹³ Firms must conduct testing of trading algorithms prior to deployment and maintain systems capable of monitoring trading activity for abnormal behaviour.

Trading venues themselves are also subject to regulatory obligations. Article 48 of MiFID II requires regulated markets to implement mechanisms such as circuit breakers designed to temporarily suspend trading during periods of extreme price volatility.¹⁴ These safeguards aim to reduce the risk that automated trading systems could trigger destabilising market movements.

The increasing reliance on digital infrastructure within financial markets has also prompted the development of broader operational resilience frameworks. The Digital Operational Resilience Act (“DORA”) introduces regulatory requirements intended to strengthen the technological resilience of financial institutions and ensure the reliability and security of financial market infrastructure.¹⁵

Taken together, these measures illustrate an increasing emphasis on preventative supervision within European financial regulation.

Comparative Enforcement and Algorithmic Manipulation

Comparative enforcement experience also demonstrates how algorithmic manipulation can be addressed through existing legal frameworks. In the United States, spoofing was explicitly criminalised under the Dodd-Frank Wall Street Reform and Consumer Protection Act following concerns that automated trading strategies were being used to manipulate derivatives markets.¹⁶

One of the most widely discussed cases involved the trader Navinder Singh Sarao, whose automated spoofing strategies were linked to manipulation of E-mini S&P 500 futures contracts.¹⁷ By placing and rapidly cancelling large volumes of orders, Sarao was able to create misleading signals regarding market demand and influence market prices.

Although European legislation does not specifically use the term “spoofing”, similar conduct would likely fall within the definition of market manipulation under Article 12 of MAR. The comparison illustrates that while regulatory terminology may differ across jurisdictions, the underlying legal principles governing market manipulation remain broadly consistent.

Artificial Intelligence and the Future of Financial Regulation

Recent developments in financial technology suggest that algorithmic trading systems may become increasingly sophisticated through the integration of artificial intelligence and machine learning technologies. These systems are capable of analysing vast quantities of market data and adjusting trading strategies dynamically in response to changing market conditions.

Artificial intelligence therefore introduces additional regulatory challenges. Unlike traditional algorithms that follow predetermined instructions, machine learning systems may evolve their behaviour autonomously over time.¹⁸ This raises complex questions regarding accountability and regulatory oversight where automated trading systems operate with minimal human supervision.

Nevertheless, the technology-neutral structure of MAR provides some flexibility in addressing these developments. Because the regulation focuses on the effects of trading behaviour rather than the specific technologies employed, manipulative outcomes generated by AI-driven systems may still fall within the scope of existing market abuse rules.

Conclusion

Algorithmic trading has transformed financial markets by introducing unprecedented levels of speed, automation and technological sophistication into trading activity. While these developments have improved market efficiency and liquidity, they have also created new risks of manipulation and market instability.

The European Union has responded through a series of legislative reforms designed to adapt financial regulation to these technological developments. Instruments such as the Market Abuse Regulation, MiFID II and the Digital Operational Resilience Act collectively demonstrate a regulatory strategy focused on strengthening oversight of automated trading systems.

In this respect, the development of European Union financial market law can best be understood as a process of regulatory evolution rather than revolution. Existing legal principles relating to market integrity continue to form the foundation of the regulatory framework, even as supervisory tools and technological safeguards evolve.

However, the continued advancement of artificial intelligence and increasingly complex trading technologies suggests that financial regulation must remain responsive to ongoing technological change. Ensuring that legal frameworks evolve alongside financial innovation will therefore remain a central challenge for European financial regulation in the years ahead.

Bibliography

1 Regulation (EU) No 596/2014 on market abuse [2014] OJ L173/1 art 15.
2 ibid art 12.
3 Directive 2014/65/EU on markets in financial instruments [2014] OJ L173/349 art 4(1)(39).
4 International Organization of Securities Commissions, Technological Change and Market Structure (IOSCO 2011).
5 Regulation (EU) 2022/2554 on digital operational resilience for the financial sector [2022] OJ L333/1.
6 Directive 2014/65/EU art 4(1)(39).
7 European Securities and Markets Authority, Algorithmic Trading and Market Structure (ESMA 2014).
8 Jonathan Brogaard, Terrence Hendershott and Ryan Riordan, ‘High Frequency Trading and Price Discovery’ (2014) 27 Review of Financial Studies 2267.
9 International Organization of Securities Commissions, Algorithmic Trading and Market Integrity (IOSCO 2017).
10 Regulation (EU) No 596/2014 art 12.
11 ibid art 12(2)(c).
12 European Securities and Markets Authority, Supervisory Briefing on Algorithmic Trading (ESMA 2022).
13 Directive 2014/65/EU art 17.
14 Directive 2014/65/EU art 48.
15 Regulation (EU) 2022/2554 on digital operational resilience for the financial sector.
16 Dodd-Frank Wall Street Reform and Consumer Protection Act 2010.
17 United States v Navinder Singh Sarao (2016) US Department of Justice enforcement action.
18 Lin Lin, ‘Artificial Intelligence, Finance and the Law’ (2019) European Business Organization Law Review.