Algo trading innovations stoke fear despite increased popularity

By Emma Olsson | 11 October 2019

Once feared by traders and regulators alike, attitudes towards algorithmic trading have changed. The development of more sophisticated algorithms, advances in artificial intelligence (AI), and an increasingly regulated market have shifted perspectives on the strategy. But tension lingers, as fear of the unknown has been replaced by anxieties around predictability and control.

Here are just some of the trends and insights shaping the impact of algorithmic trading in 2019.

AI developments to drive algo trading

AI is finally leaving its nascency. Once considered a risk to the already precarious nature of trading – especially under tightened rules such as Europe’s second Markets in financial instruments directive (Mifid II) – more and more firms are starting to embrace AI in their trading. As the technology’s reputation shifts from risky to responsible, its incorporation into the market seems a natural progression. Fintechs such as Binatix, Kavout, and Auquan have been leading the way in incorporating AI into their algorithms to recognise complex trading patterns and adapt to the market.

Reinforcement learning (RL) algorithms are increasing in popularity

RL algorithms work by penalising algo strategies for making the wrong decision while rewarding them for making the right one. They were championed by JPMorgan in 2018 and play a large role in the future development of algo trading. RL is part of a broader family of AI referred to as deep learning, which fintechs such as Sentient have been developing in recent years.

Algorithms must have a dynamic approach to fluctuating market conditions, and RL algos provide a robust quality to algo trading that has become integral to its success, according to JPMorgan. RL’s impressive self-teaching capabilities take further control from an organisation’s human hands – an impact which has both cynics, wary of too much responsibility being placed on the machine, as well as advocates, who celebrate the lack of emotion with which the systems learn to better enter and exit positions.

Hedge funds embrace algos

As markets have been hit with a swath of new rules in recent years, firms are still facing fines for compliance breaches. The UK’s Financial Conduct Authority (FCA) investigated 48 firms for potential breaches in February, with Goldman Sachs fined £34.3m for insufficient transaction reporting in March. As a result, hedge funds and banks alike are cracking down on accuracy in their trading, which increasingly reliable algorithms may be able to provide.

In the search for arbitrage, hedge funds have long utilised algorithms. Yet still today, there are traders and analysts who blame algo trading for the market crash of 2015. Criticisms aside, ignoring the changing market landscape seems a fruitless fight: recent reports such as the 2019 Algorithmic Trading Survey suggest that hesitations towards algo are dissipating as companies adapt to changes, with hedge funds “doubling down” on algo trading.

Increased investment in surveillance tech may be leading firms to embrace algo trading

The Mifid II world is one in which surveillance is key to the market. As the directive requires constant reporting on each transaction, firms must maintain flawless surveillance in order to avert transgressions. According to a 2019 report by Coherent Market Insights,  firms obliged to report under Mifid II have significantly increased their investments in surveillance tech. Many market participants have embraced algo trading as a means to minimise transaction costs and market risk, a by-product of prioritising surveillance.

These findings contrast initial beliefs that algo trading is too rooted in short-term solutions to be effective in the long-run. As we move further from Mifid II’s implementation date, the industry seems to be drifting away from initial compliance concerns, according to the 2019 Algorithmic Trading Survey. These developments place algo trading in a tricky position. On one hand, algo trading has been useful throughout the early Mifid II period, as its quick solutions have allowed space for a greater focus on surveillance and meeting regulatory requirements. On the other hand, as technology advances, algo trading could be configured to meet these re-prioritised, long term strategies. The true impact of Mifid II on algo trading remains to be seen.

Asia Pacific catching up with North America

Algo trading is most prominent in North American markets, with Coherent Market Insights reporting that 60-73 percent of all US equity trading utilise algorithms. The area with the most projected growth, though, is Asia Pacific (APAC), where trade is growing rapidly in developing economies. APAC markets have been slow to adopt algo trading due to a slew of legal and regulatory obstacles, but these regulations show signs of being lifted. For example, India’s Security and Exchange Board (SEBI) announced new measures for making algo trading more accessible for its investors last year. Coherant Market Insights report that 37 percent of financial institutions in India invested in AI in 2018, with around 68 percent planning to adopt it into their algorithms in the future.

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