Write-up by Rupert Walker, Managing Editor, GlobalTrading
Automation throughout the trading process is increasing rapidly, but there are roles for human agency, according to participants at a roundtable discussion in New York City.
Trade automation continues to be driven by regulatory requirements for best execution and stimulated by the rapid development of new technologies. It can help remove human bias, enhance surveillance, and explain trade execution in a systematic way and benchmark its performance.
Eventually artificial intelligence and machine learning will likely further reduce the role of human agency in the trade process, but now there is still demand for staff with quantitative skills, managerial expertise and even personal networks and market knowledge built on experience.
At its best, automation is about solving problems for clients, increasing trade execution efficiency and achieving scalability, agreed panellists at an Itiviti-sponsored roundtable discussion hosted by IEX at its office in the World Trade Center, Manhattan on 27 June.
One panellist recounted an anecdote from an electronic trading conference a few years ago when a speaker, with tongue in cheek (perhaps) predicted that soon dealing desks would be fully automated – and protected from meddlesome humans by a guard dog.
However, if automation goes wrong, problems can grow exponentially without human monitoring and override capability. In fact, financial firms have learned from experiences a decade ago and put in controls concurrent with technology installation since 2008, and the industry is now generally a safer place.
Third parties can be a better, more cost-efficient option for trade surveillance functions, such as identifying spoofing and front running, and making control adjustments. A lot of trading surveillance is already automated, but patterns are changing and bad behaviour is becoming more heinous and difficult to identify. In some markets, often the best that can be done is merely to flag a signal that a trader might be being spoofed or layered.
Automation is well-established in developed equities markets, and is increasingly deployed in the operational processes of passive funds to match indexes and reduce tracking errors.
Algorithms are sufficiently different and can execute diverse strategies, which ensures trading is not homogenous and one-directional – at least in normal market conditions. For instance, smaller fund management firms often tend to be very active with distinctive strategies implemented by their own homegrown algorithms.
Dealing desks, especially at large asset managers, can tailor their trading strategies to match the diverse styles, such as momentum or value-driven, of their portfolio managers and automate the processes. Regulation increasingly requires buy- and sell-side firms to explain and justify execution, especially outlier trades, in a systematic fashion. One consequence of greater compliance costs in illiquid transactions might be to force some firms out of business.
Banks, fund managers and vendors are applying similar technologies to other asset classes, including fixed income and foreign exchange, but the transfer is far from easy. Markets have their own idiosyncrasies, levels of liquidity and dealing practices; fixed income, in particular, suffers from sparse data.