Can you please share more details about the new algo functionality you recently introduced?
We have recently rolled out two enhancements within our most popular FX algo strategy – FLOAT. Clients can now run a Float algo with State Street and access Aim to Complete (ATC) and Implementation Shortfall (IS) functionality through both their EMS and VectorFX algo hub.
The ATC parameter within Float monitors the progress of the order against an underlying TWAP (default) or VWAP/IS curve to ensure completion by desired end time. ATC will only come in to play if the Float algo notional fill speed is falling behind the underlying curve schedule due to parameter settings /liquidity market conditions and/or limit price.
The IS parameter allows Float to operate with a dynamic implementation shortfall curve which aims to minimize the mean-variance of implementation shortfall cost of the order (i.e. reduce slippage from the arrival price). We leverage the efficient frontier concept when we construct the IS curves – a concept first pioneered in our portfolio algo released last year. Efficient frontier establishes tradeoffs between average expected cost of slippage and standard deviation. This is based on different risk aversion profiles which can be expressed by the client by selecting different execution styles on our Float algo. The IS curve adaptively recalculates when order parameters are amended or when the algo strategy falls behind IS curve projection (i.e. limit price impedes algo fill speed).
What needs do the new ATC and IS parameters fill for your client base?
Our client base continues to look for ways to minimize information leakage and reduce trading costs. At the same time, resource constraints have led execution traders to take on more responsibilities in the “multi-asset” execution space. Within this context our clients are asking for an algo strategy that has the benefits of the State Street Float strategy but also assures completion in busy markets. This is where Aim to Complete becomes a helpful tool. Traders may access the opportunistic and passive nature within Float but also have the assurance that on a busy trading day where they can become distracted, their risk will still be covered. They can take comfort knowing the Float-ATC will attempt to finish the execution based on their desired end time.
One of the challenges when using a passive algo strategy is how to engage with liquidity when markets are fast moving or trending away from you. If you are too passive and miss out on 5-6 bps of price action it impacts your slippage from arrival, and risk transfer benchmarks. Our Implementation Shortfall parameter was designed to be more proactive and engage with liquidity through an IS curve derived from an efficient frontier which varies from our standard FLOAT algo interaction. The IS parameter targets the arrival price and has the ability to engage with liquidity a bit quicker than the normal Float algo based on the underlying IS curves. In fast moving or trending markets this should aid execution performance and clients should see better slippage against “arrival price” benchmarks.
As opposed to other providers where IS or POV (Percentage of Volume) are separate algos strategies we chose to include IS as a parameter on Float. With this set-up clients receive all the benefits of Float with the added ability to overlay IS and POV constraints on the strategy. This helps us keep our list of strategies succinct while allowing flexibility to switch between FLOAT/IS/POV easily. This has been key feedback from our clients.
Has there been any changes in demand for data or analytics and what can you do to meet this demand?
Yes, clients have been particularly interested in volume metrics this year. In a fractured FX market where liquidity is decentralized liquidity profiles, liquidity regimes and liquidity forecasts can help lay a framework for clients to know when, where, and how to clear FX risk. These metrics can also be used to evaluate liquidity conditions through comparison of different timeframes or events. We have been generating these metrics in our internal “Liquidity Dashboard” since 2022 and it is something we often discuss with clients while they are evaluating how and when to execute a trade. These volume metrics can be particularly informative during market events, or in EM pairs where liquidity may track closely with local market hours or in low liquidity hours for G-10 pairs. Due to the demand for these metrics, we are working to integrate our liquidity dashboard into our VectorFX SDP algo hub where clients can access it directly at their fingertips.
Have you seen any change in demand for internalisation?
Internalisation is always at the forefront of our clients’ minds, and it is something we constantly look to improve in order to minimize market footprint by harnessing the value of our franchise liquidity. Our peer-to-peer algo matching engine, Interest Match, was enhanced in Q1 2024 with the introduction of Skew Match. A Skew Match will occur when State Street fills all or a portion of an open algorithm order with liquidity from an opposite direction skewed streaming price at, or better than the mid-price.
With the addition of Skew Match, our peer-to-peer Interest Match feature within the algo suite is now composed of four distinct ways to increase internalisation. The fills in each of these internalization categories are shown as separate venues in our TCA for full transparency to our clients. Results of Skew Match have been excellent. It allows us to clear algo risk in lower liquidity regimes at a faster pace, lowers signalling and market impact, increases internalisation and thus improves overall algo performance.
