RiskTech Forum

Out Of The Dark: Technology And The Future Of Trading

Posted: 23 January 2013  |  Author: Nigel Woodward

Ken Yeadon, managing partner of Thematic Capital, has suggested – based on his experience as a trader for a Tier 1 firm, an algo hedge fund, and an industry investor in technology innovation – that the future of trading will move from response to signals in market data towards reaction to multi-faceted information, with a very real and conscious eye on global financial environment impact.

Information influences trading decisions, while considering regulation can help to spot and contain risk issues. Ken painted a picture using the automobile industry and our everyday experiences to show that the trading function needs to learn some lessons from the way it has matured and operates today. They say a picture paints a thousand words and never has it been so true as today.

Fast-moving traffic assumes that it is all moving in the same direction. Basic information controls as to what the overall safety considerations are mean that we are able to coexist together and allow us to modify our behavior accordingly.

In trading, the information and controls are economic indicators and immediate market behavior, but the nature of trading to date has led to this self control and behavior moderation has been questioned.

Therefore, much recent regulation has been a heavy blunt instrument, against a political backdrop in which the pendulum has swung towards much stricter supervision. The industry therefore needs to come up with an operating model that satisfies societal needs but also preserves the functions and role of the markets

We need to be able to perceive looming hazards in the market and build “situational awareness”. The trading function needs to anticipate, manage, and pre-empt hazard by modifying the rules of the market in play at any one time to reflect the state of the operating environment.

Oversight by the regulator allows supervision with identification of both pattern and practitioner behavior and specific intervention against rogue operators, if necessary, when they practice in known high risk patterns. In its ultimate form, information must be assembled such that responsible practitioners can heed its input and supervisors can impose controls where they see impending dislocation or failure in the market.

If the trading environment is unclear, then the prudent response is to back-off. Information on market activity needs to become more transparent (lit as opposed to dark) and, if necessary, cut off-switches should be implemented to avoid the pile up. This all implies an extra cost of surveillance and technology at a time of lower market volumes and reduced revenue in the current business model.

Pressures indeed, but the onus is on the market to respond. Technology can reduce costs; it can enable and disrupt and we are now in search of the viable equation. The aim must be to at least intercept the issue and, if it does happen, containing it so that unrestrained contagion does not occur.

This is where the crossover with technology innovation exists. Analytics are optimized for big data, so that information can map the interaction patterns of latency data, trade data, risk, and order flow. The punch line is that latency will continue, but it might be different – from interpretation and response to signals in market data to analysis of situational and environmental (big) data, such that operation can proceed uninterrupted, but within the guidelines coming from informed responsible supervision.

Risk management remains a high priority, as is the need for more information – echoing the views of Ken Yeadon’s keynote address.