ITG's Sparkes: Driving competitive advantage through FX TCA
Michael Sparkes (pictured), director of ITG argues that Transaction Cost Analysis (TCA)enables firms to reduce costs and hone trading strategies.
Michael Sparkes (pictured), director of ITG argues that Transaction Cost Analysis (TCA)enables firms to reduce costs and hone trading strategies.
“The most valuable commodity I know of is information” – to quote Gordon Gekko from the 1987 movie classic Wall Street. This line has never been more significant than in today’s data-fuelled financial markets, where detailed analysis of information can provide that all important competitive edge – both now and in the future. To achieve this, firms are looking towards Transaction Cost Analysis (TCA), which enables them to reduce costs and hone trading strategies.
This isn’t new. TCA has been established in equities for some time and while compliance was initially the main driver, it has proven to add alpha to the execution process. As a result, it’s not surprising that the TCA focus is now shifting beyond equities, with currency trading firmly in the spotlight following George Osborne’s plans to set out tougher measures to regulate FX markets.
However, it is not simply a case of applying the equities model to FX. The idiosyncrasies and inherently complex structure of currency markets have slowed TCA’s progress in FX. Added to this is the fact that FX has often been outsourced to third parties, or may be a secondary or subsidiary trade linked to another asset. So not only has TCA in FX proved more challenging than in equities, but the impetus has not been there to the same extent.
However, times are changing, and recent events emphasise the need for smarter use of TCA in FX. According to our recent report on tradable data between London and New York before and after the 4pm fix, the costs from the order arrival time until trade execution are on average 17 basis points, 20 per cent of the time. This is crucial as 17 basis points of implementation shortfall for up to 20 per cent of all days can potentially cost asset managers millions of dollars of un-invested funds. Not an insignificant amount for any investor.
This shows that in a post 4pm world, the time has come for the asset management community to take full advantage of the data available to advise strategy. Forward-thinking investors are already beginning to position FX TCA as a critical business function, enabling better trading outcomes and enhancing performance. Last month’s data can inform this month’s decisions on when and how to trade, maximising the benefit of their FX trading. This takes on even greater significance when you consider the percentage of the collective pension pots tied up in the currency markets. Even incremental improvements must be pursued.
To make these improvements, asset managers need to squeeze the very most out of all the information at their disposal. For this to happen, TCA providers need to anticipate what an asset manager might require from their data in the future. This includes pressure for higher returns triggering clients to demand even better execution. This, coupled with increasing pressure for higher returns, will see them asking more testing questions above and beyond the standard analysis.
These questions could be around the best algo to use for a specific trading scenario. As algorithmic trading continues grow in FX, there is still much confusion over what constitutes the best algo amongst the multitude deployed across the market. It is not just about algos, there could be a request for documenting data from a voice transaction that needs to be reported promptly.
The key to unlocking future success is for the TCA provider to work closely with the asset manager ahead of execution. This enables both the provider and the asset manager to get a better feel for market conditions before deciding on its trading strategy. As we move forward, asset managers who achieve competitive advantage will be the ones that adopt this approach in order to evolve their trading strategies in FX, using data to answer the testing questions for tomorrow, not just the ones for today
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