Why is liquidity such an important factor to consider in the use of FX algorithms – even superseding execution logic at times as the most important determinant of performance?
During volatile periods, access to reliable liquidity is paramount. We put significant effort into maintaining strong relationships with a diverse panel of external liquidity partners to ensure continuous access, even under stress. Without reliable liquidity, even the most sophisticated execution logic would struggle to achieve optimal outcomes.
Why is offering access to clean liquidity with depth something that relatively few providers of FX algo trading services are currently able to offer?
Offering access to clean liquidity not only requires a curated panel of external partners it also is dependent on a diverse and deep client franchise which few banks have the resources to achieve. Deutsche Bank’s ability to tap into our franchise flow provides an edge.
How important is it that clients understand the liquidity their FX algo orders are interacting with and what benefits can this transparency deliver?
Clients are no longer satisfied with simply using algos; they want to understand how they work and prove their effectiveness. This understanding is crucial for minimizing market impact and achieving optimal performance. This knowledge empowers clients to make informed decisions about algo usage and settings, ultimately leading to better outcomes.
In what ways can internalisation sometimes help to improve FX algo execution performance and how much of a differentiator amongst providers is this capability?
Internalisation can potentially lead to better pricing by reducing reliance on external liquidity sources and reduce signalling risk. The prominence of internalization stats within our TCA reporting is testament to how critically we treat this requirement in our product set. The ability to customize liquidity pools, including the level of internalisation, is a differentiator, as it caters to clients’ specific preferences and allows for fine-tuning of execution strategies.
We also offer a secondary internalisation model, whereby we leverage liquidity from other, carefully selected, internalising LPs to supplement our offering, which clients find very valuable.
In what ways are some providers leveraging their own quantitative research to make more effective use of liquidity for FX algo trading?
We leverage our own quantitative research through proprietary modelling and short-term forecasting which allows our Algos to optimise their execution path and timing of the underlying fills to the benefit of our clients.
This quantitative research helps to intelligently navigate and utilize available liquidity, adapting to market conditions for more effective execution.
How difficult is it for providers to effectively manage and benchmark various liquidity pools and is being able to take a more data-driven approach to this process seen as another differentiator and strength amongst some of them?
Managing and benchmarking liquidity pools is challenging as you require statistically significant samples from similar market regimes. Our use of automated A/B testing, which customises the liquidity sources and settings based on their usage demonstrates our data-driven approach and ultimately allows for clients to make more informed decisions. This capability is seen as a differentiator and strength, particularly for our extensive quantitative hedge fund client base.
Some providers are more resilient in volatile markets than others so how are they managing liquidity to maintain better FX algo execution quality during times of stress?
Our algos automatically adjust their order placement strategies to optimize for liquidity in certain market conditions. The market conditions are also modelled within our Quick Pre Trade tool, so clients have on demand visibility as well as the real time TCA and execution advisory support.
Other providers also offer access to more diverse liquidity pools than competitors. What benefits does this bring and how does it facilitate more adaptive and effective execution strategies?
Access to more diverse liquidity pools brings the benefit of continuous pricing, even under stress. This diversity facilitates more adaptive and effective execution strategies by providing a wider range of options for order placement and fill. For example, Stark taps into Deutsche Bank’s broad client franchise flow and select liquidity sources to execute faster than average. A broader and more diverse set of liquidity sources allows algos to find optimal execution opportunities across various market conditions and order types.
More customised liquidity pools are also starting to appear based on client preferences. In what ways is this flexibility helping clients to fine-tune execution to their particular trading style as well as improve outcomes?
Customized liquidity pools allow clients to adapt their setup, including the ability to increase or decrease the level of internalized fills by currency pair and by algo type. This flexibility helps clients fine-tune execution by enabling them to align the algo’s liquidity interaction with their specific trading style, risk appetite, and objectives. For example, some clients might prefer higher internalization for certain currency pairs, while others might prioritize external liquidity for speed.
There continues to be tremendous innovation in the algorithmic FX trading space. As part of these endeavours how are some providers taking liquidity management to the next level and looking to move ahead of the pack in order to help achieve even better execution performance and trading outcomes for their clients?
Algo innovation is a bit like a premier league team, if you do not continually reinvest then you will drop down the rankings. In an increasingly data driven world, that performance matters more than ever when looking to create positive feedback loops. Innovation for innovation’s sake however is a red herring, it has to be led by client feedback and help improve their user experience. Our innovation is pretty broad, across quantitative research, A/B testing, real time analytics but our core driver is always client-led enhancements.
