High Frequency Trading: A Threat To The Financial Markets Stability?

"Technological advances have outstripped our ability to regulate them. [...] It's like the Wild Wild West."

― Andrew Lo (MIT's Laboratory for Financial Engineering)

'Algorithm Trading' is a technique, which was created in the 1970s in the US in the context of the computerization of financial markets and took off in the 2000s. In the competitive world of finance, sophisticated operations carried out in a short space of time can make the difference. Algorithms allow financial institutions to take advantage of tiny differences in prices that can arise between the various stock exchanges, and thus multiply the profits by a large number of orders.

The term 'HFT' is pretty recent, and occurred for the first time in the mainstream language in the New York Times in 2009. On May 6th 2010, the public discovered HFT through what has been called the 'Flash Crash'. In a few minutes, nearly 800 billion euros (or nearly 50% of the French debt) were blown away. With no warning sign or apparent reason, the American Dow Jones index lost nearly 10%. The Flash Crash has been caused by HFT, since it permits an extreme reduction in the time required to complete an exchange on the financial markets. This is the opposite of the long-term investments for which stock exchanges were originally designed. The quality of the investment doesn't matter, it is the quantity and speed that counts. Therefore, it creates an extreme market's volatility, hence undermines its structure.

This doesn't prevent investment banks and finance professionals to make use of algorithms in the context of HFT. Around 50-60 per cent of all US equity market transactions are HFT related.

This has led regulators to take charge of the problem, as some feared a too high volatility and negative impact on their stock exchanges and financial markets. This paper aims to take a closer look at the issues created by HFT and at the regulations trying to solve them. Is HFT a threat to the financial markets stability?

The paper will first try to define HFT and explain in which way it can be problematic, after what it will expose the current legal framework in the EU.

Defining High Frequency Trading

HFT derives from AT. The latter has been defined as "the use of computer algorithms to automatically make trading decisions, submit orders, and manage those orders after submission." AT systems make it possible to have holding periods lasting for hours or days. If HFT also uses algorithmic decision making technology, it differs in its speed: it permits transactions in microseconds.

HFT has been defined as an algorithmic trading technique that implies that large volumes of orders are placed automatically at very high speeds. To understand the concept and how it has an influence on the analog economy, it is interesting to picture it through a concrete example.

A pension fund wants to buy 600,000 shares at $9.50 per share. Its purchase order is sent to different stock exchanges. In the first financial place where the order arrives, the HFTer records it and activates the transaction order. It sends its purchase orders to all stock exchanges, and does so faster than the pension fund. Thanks to its ultra-fast connection, it manages to buy all the shares at the price of $9.50, and then offers them to the pension fund at the price of $9.51. By selling its shares this way, the HFT manages to make a profit of $6,000 in a few milliseconds without taking any risk. On the other hand, the pension fund (actor of the 'real' analog economy) is victim of increasing prices. In the financial world, a few cents per share can lead to a disastrous inflation.

Issues Raised By The Use Of High Frequency Trading

Markets Volatility - HFT can act in a detrimental way against the diversity and fluidity of the market. It's about the impact of the actors' investment. If they want to buy a lot of shares, they will be dealing with a very fragile market that will offer little return on their investment. The HFTer isn't running 24 hours a day, but is activated when the financial markets experience strong fluctuations (volatility) as a result of crises, wars, or political decisions. In essence, HFT takes advantage of crises and awaits the next one to happen.

Furthermore and in the same vein, HFT competes with analog actors of the real economy. Let's think of the situation in which a great crisis is occurring, due to political and/or diplomatic conflicts. It is predictable for everyone that the prices of some specific shares in a given economic sector will drastically fall under a new record. Actors of the real economy will resell their shares before they loose to much value, and investors believing in the future uptrend of the market will invest. The selling of the shares for them will last a few days, whereas it takes milliseconds for the HFTer. In this sense, the robot can take advantage of the situation and resell every share in a few seconds before the prices drop too low. This mass resell has a bomb effect on the real actors shares which will massively loose value. The return of investment for the real actors is therefore almost nonexistent. This example shows how strong the impact on the real economy can be.

Piracy - HFT can be dangerous since it is possible to hack the robot. As an example, a HFTer has programmed a robot to trade automatically and stop trading as soon as it loses connection with the mother firm. He came back the next day and realized that a parameter was inactive. He ended up with a robot that was running wild and wouldn't stop trading. In the end he could've lost up to 300 million euros. Beside the loss for the trader, this also results in a strong fluctuation on the market, depending on the size of the trading structure using the algorithm. This incident was the result of a piracy action in which the hacker had disabled the defense parameter. Because no system is immune to piracy, HFT therefore also undermines trading structures.

Quote Stuffing And Dark Pools - 'Quote Stuffing' is a technique consisting in the saturating and slowing down of IT-services by sending several thousand orders that are immediately cancelled, in order to prevent a competitor from placing its orders. This makes it possible in particular to conceal certain strategies and can be considered as manipulation strategies by the authorities.

This technique has been made possible by HFT, and permits market manipulation. Indeed, other traders are slowed down by it, which allows the HFTer (being the stuffer) to trade in his advantage on the same or on another venue.

The lack of traceability of HFT's operations is also criticized. So-called 'Dark Pools' are private electronic platforms allowing an asset to be traded anonymously and thus escape the control of the authorities. Regulators are aware of these practices, but find it impossible to legislate in view of the complexity of the systems in place.

The European Regulatory Package

As HFT is raising new challenges, regulators have taken the problem seriously and tried to interfere. The regulatory approach differs between the different markets and geographical/cultural areas due to the lack of a clear-cut definition and agreed characteristics to identify HFT.

The European regulator legislated by laying down the so-called 'MiFID', which has been replaced by 'MiFID II' and 'MiFIR'. These regulations, along with the consultation paper issued by the ESMA, build up the new regulatory package on AT/HFT.

According to it, investors must be authorized by the financial market authorities (if they don't fall within the exemption cases). Also, they need to keep track of their transactions by storing time-sequenced records of their AT/HFT systems for a minimum of five years. This specific provision should prevent from widespread market abuse practices like quote stuffing.

Also, the regulatory package gives a clear identification of HFT practices, by setting two characterization options. The first one is to determine quantitative thresholds such as the message rates. A second option is to compare between the median order lifetime and the median lifetime of all the orders in the trading venue; in particular, if the former is lower, then there is evidence of use of high frequency trading practices.

So the EU increased transparency requirements. This doesn't prevent the use of HFT, but it's a step forward.

Conclusion

The most important factor is nowadays the speed of the transaction, rather than its quality. This weakens security and fundamentals don't play any role for most HFTers. Human are removed from the direct decision‐making process of security transactions and substituted by computer software. This has to be discussed. Indeed, is it in anyone's interest to let robots take control over our economies and financial places, as they're the pillars on which capitalism is based on?

Additional literature:

Brogaard, Jonathan. "High Frequency Trading And Its Impact On Market Quality." Northwestern University School of Law, 2010.

Kolb, Robert. "The SAGE Encyclopedia of Business Ethics and Society." Second Edition, 2018.

Lehmann, Matthias ; Kumpan, Christoph. "European Financial Services Law". International and European Business Law, 2019.

Moser, Friedrich ; Wunderer, Daniel. "Die Geldroboter." RBB, 2020.

Henderschott, Terrence ; Riordan, Ryan. "Algorithmic trading and information," 2009.

Weller, Benedict ; Bruno, Michelangelo. "Is EU regulation of high frequency trading stringent enough?" The London School Of Economics Review, 2018.

Legal sources:

Directive on Markets in Financial Instruments repealing Directive 2004/39/EC and the Regulation on Markets in Financial Instruments, commonly referred to as MiFID II and MiFIR.