The structure and make-up of the foreign exchange (FX) market has been transformed over the past 20 years. Once a voice-traded, bank-dominated market, the industry has evolved almost beyond recognition as a result of new technology, greater diversity of counterparties, and innovation in areas such as electronic and algorithmic trading.
The role of the treasurer has also evolved in this period. Treasurers have become increasingly strategic, with a greater focus on solving wider business challenges beyond their traditional remit.
Technology and automation are also having a profound effect. Nearly 75% of treasurers say that their organisations are automating treasury functions in one form or another, and two-thirds expect automation to have some impact on their working lives.
The benefits of automated technology and artificial intelligence (AI) are most prominent when there is a need to process vast amounts of data. Put simply, machines are far superior than humans at high-volume processing. Not only does that improve efficiency and risk management, making a lot of treasury functions easier to manage, but it frees up corporate treasurers to focus on other tasks where they can value.
The view that machines are superior to humans at high-volume processing is certainly true when it comes to managing volatility and hedging foreign exchange exposures. This has always been a complex and challenging task, with all but the largest global corporations either outsourcing this function to banks or relying heavily on them for access to liquidity, execution and market intelligence.
Automating currency trading – the role of algorithms
The challenge of managing FX exposures has been exacerbated in recent years by the increased complexity of the market’s structure. There is greater fragmentation of liquidity, as the number of venues and execution models increase and the sheer level of information that needs to be processed almost instantaneously in order to execute a trade, is significantly higher than a few years ago.
Corporate treasurers need the necessary tools to master the trading process and stay on top of all the data that is generated. That’s why many are turning to algorithmic trading, or urging their banks to do so, ensuring they achieve and can demonstrate best execution, while reducing the risks associated with their currency trades.
According to Greenwich Associates, there has been a meaningful increase in both penetration and the proportion of flow that is executed by corporates through algorithms as they seek to optimize their FX trading performance.
A human cannot react as quickly to changing bids and offers across multiple venues as quickly as a computer can. Additionally, since algorithms automate trading, they can process multiple orders simultaneously. This is another important benefit, especially at a time when traders are being asked to do more with less.
58% of FX traders found that algorithms materially reduced overall trading costs, while over a quarter of traders believed algorithms enabled them to spend more time on complex orders.
Achieving best execution
With the changing face of regulation within FX, it is important for all participants to realize the importance of best execution practices and ensure that their business model and products correlate firmly with this.
Last year’s introduction of MiFID II significantly upped the stakes for best execution, because firms must now take “sufficient steps” to ensure favorable execution of client orders as opposed to “reasonable steps”.
This change in language may sound subtle but it has significant consequences for banks trading on behalf of their corporate clients. Each firm must now have a clearly-worded best execution policy that has sufficient detail for their clients. In addition, the effectiveness of this policy must be analyzed no less than annually.
At the same time, greater attention has been placed on complying with the principles of the FX Global Code. One of the Code’s six principals is Execution, which outlines a set of principles clarifying what traders should expect from their service providers. As well as the processes and policies, they should have internally around trading in order to promote fair and orderly markets.
It is therefore unsurprising that there are stronger demands from corporates for tools that measure and evaluate execution quality. One way of achieving this is through the use of transaction cost analysis (TCA) tools.
Utilising TCA to measure execution quality
By its nature, algorithmic trading lends itself well to TCA, as the market data needed to power the algorithm can be recorded on a database, along with the execution data. This enables corporate treasurers to measure and understand if they are achieving high-quality execution, and to improve their trading process.
An algorithm requires real-time market data and knowledge of how it is tracking against an order. This information can be logged and easily stored in databases and later utilized for TCA purposes by algorithmic providers.
Historical trading data can be reviewed against a number of metrics and factors, such as price benchmark, trade duration, venue traded, currency pair and trade side. This enables corporates to measure and understand if they are achieving high-quality execution on trades and where they can improve their trading processes to drive better trading performance and save money.
Greater sophistication to drive algorithmic growth
Today, the largest and most advanced trading firms in the world are amongst the heaviest users of algorithms because they recognise the benefits they provide. With corporate treasury divisions growing in influence and becoming more sophisticated, continued adoption and use of algorithms is an inevitable endpoint.
As electronic trading evolves and becomes more mature, and regulation continues to push for greater transparency, algorithmic trading will become an indispensable tool for corporate treasurers.
Curtis Pfeiffer is Chief Business Officer at Pragma.