Calmer FX markets, liquidity fragmentation and the legacy of the pandemic are among the factors fuelling a new wave of algo usage.
As FX spreads continue to compress and liquidity fragments, algos are increasing in popularity among institutional clients seeking to get the best price.
Nomura has seen average client FX algo volumes quadruple since January 2023 led by real money clients like pension funds and asset managers. A survey last year by Coalition Greenwich revealed that 69% of respondents believe that algo use in FX will increase in the future.
The trend is being driven by relatively calmer FX markets over the past year – which negates the need to call a broker for market colour - and a compression in spreads due to competition among banks and market-makers, as well as fragmentation in liquidity as dozens of electronic platforms host currency trading, according to Antony Foster, Head of G-10 Spot Trading for EMEA at Nomura in London.
“As markets have become more electronic and fragmented, clients want execution options and analysis to measure their flow rather than charging into the market,” says Foster.
Algos, which trace back their origins to equities in the 1970s, have become a dominant force in financial markets. They are characterized by the use of computer algorithms to automate trading decisions and have significantly reshaped how FX is traded, driven by advancements in computing power, the pursuit of efficiency and the need for a competitive edge.
In FX, the largest and most liquid financial market in the world with daily trading volumes exceeding $6trn, algo trading started gaining prominence in the mid-2000s. As FX is traded 24 hours a day, it’s well suited for automated algo strategies.
Today, the spot FX market is comprised of dozens of banks transacting across more than 15 venues for euro dollar, the most commonly traded currency pair. On top of that, each bank typically operates several different algos including ‘aggressive,’ ‘passive’ and ‘dynamic’ versions, offering an enormous menu of choices for clients.
“Client conversation around algo usage has evolved over the last decade” says Ben Robson, EMEA Head of e-FX Sales at Nomura in London. “It’s no longer seen as a tool to replace traders on the desk but instead augment the set of options around execution and currently it is far more focused on data and the decisions being driven by pre, intra and post trade transaction costs”.
There are multiple drivers for the increased usage of algos:
1. TCA – Transaction Cost Analysis
Algo trading reduces transaction costs by minimizing the bid ask spread and lowering the market impact of large trades. This cost efficiency is particularly attractive in the FX market where even small cost savings can translate into substantial profits due to high trading volumes. Banks can also provide data to show that using an algo beats a risk transfer equivalent – such as calling a broker or manually using a platform – over a period of time on average, according to Foster.
2. Speed and precision
Human traders cannot match the speed and precision of algorithms. Algo trading systems can execute trades in milliseconds, capitalizing on short lived market inefficiencies and arbitrage opportunities that would be impossible for humans to exploit.
3. Risk management
Advanced algorithms can monitor and manage risk more effectively than human traders. They can dynamically adjust trading strategies based on real time market data ensuring positions are hedged appropriately and risk exposure is minimized.
4. Covid-19
The Covid-19 pandemic broadened the use of algos in FX as market participants working from home found it easier to automate their trading.
Algo trading has increased liquidity by providing continuous bid and offer quotes, making it easier for traders to enter and exit positions. However, this liquidity can be quite fleeting as algorithms can quickly withdraw from the market during periods of volatility.
The fragmentation of liquidity across electronic platforms such as EBS means a greater need for algos, which smooth out the effects of larger sized orders.
Foster explains that the biggest segment of Nomura’s users are asset manager and pension funds with large spot flow to transact who want to limit market impact while opportunistically taking advantage of market-moving events.
At times they deploy aggressive algos as these strategies seek out deep liquidity across venues while exploring the likelihood of rejection before intelligently sourcing the right liquidity.
With spreads continuing to compress even in very large size and banks streaming in bigger notional, there’s a huge value in having a conversation with an expert around FX execution, says Robson.
Some banks offer a pre-trade TCA tool but others including Nomura prefer to offer a more bespoke service depending on the particular trade.
“Our USP is to offer a tailored response rather than just provide data and leave the client to make decisions without speaking to experts. If volatility kicks off and markets become more complex, clients should utilize the skill of traders using these products daily to inform their decisions,” says Robson.
The challenge for banks is to take the data that algos are generating and display it to traders on the desk who are deciding what strategies to use.
By rapidly incorporating new information into prices, algo trading has contributed to more efficient markets, narrowing bid-ask spreads and increasing the speed of price discovery.
The rise of algo trading has intensified competition among market participants, driving innovation. Firms invest heavily in developing cutting edge algorithms and technology to gain a competitive edge, leading to continuous improvements in trading strategies and market infrastructure.
An area of challenge for algos concerns regulatory scrutiny as authorities increase focus on ensuring automated trading systems operate fairly. But in the long run, it benefits the development and maturity of the market.
Overall, the outlook for algo trading couldn’t be brighter as technology such as AI looks set to usher in a new leg of growth. The integration of AI into algos promises to revolutionize the FX market by enabling the development of more adaptive and predictive models, capable of learning from past data sets.
“The growth in algo trading across FX markets represents a significant shift in how currency trading is conducted, and it will only get more sophisticated in future,” says Foster.
To gain further insights into algo trading in FX markets please contact Antony Foster or Ben Robson.
Head of G-10 spot trading for EMEA at Nomura
EMEA Head of e-FX sales at Nomura
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