With Carl James, Global Head of Fixed Income Trading, Pictet Asset Management
The methodology of equity TCA appears to be being supplanted straight into fixed income – yet we know this way of thinking simply doesn’t work. MiFID definition of best execution, describes the process whereby price is an important component, but it’s not the sole component. In terms of terminology, it would be better to use best execution ‘methodology’ or best execution ‘benchmarking’ instead of TCA.
What many in the industry don’t realise is the extent to which fixed income is a completely different asset class (with a number of different instruments) compared to equities. In addition, the reason that instruments are bought and sold is different for fixed income as compared with other asset classes.
The question of best execution methodology begins with the choice of execution strategy. Is it agency or principal? If agency, is it in a synthetic central limit order book or is it a dark pool? While decision-making, firms need to use the underlying data to support their reasoning. Traders need to improve how they use the data that they have already at their disposal. If a trade in a similar name worked well in a dark pool, it could be worth trying the same again. Similarly, if it worked well through an RFQ using a particular set of brokers, then they could try those brokers again to see if the liquidity is still there.
If a firm examines the active inventories and the hit ratios of winning bids and non-winning bids, there is suddenly a huge amount of data available that will lead to a defensible position of why the firm used Broker X and Broker Y; this should then lead to a better informed strategy and a chance at a better overall outcome. It is a layering process which becomes a more dynamic set of inputs and outputs, rather than simply a tick-box exercise to reach whatever benchmark is being targeted. Traders are therefore actually able to demonstrate that sensible decisions are being made all the way down the decision-making process.
There is a vast amount of data that asset managers can buy, but this would clearly have a budgetary impact. There is also a considerable amount of free data that buy-side firms have access to because they have already been given it. The first set is their own hit ratio. Firms can examine a broker’s profile to see how well they perform, whether they are the best broker for example, and then they can examine how they fare in terms of other brokers etc – this all gives additional colour.
In terms of other data, the axes and the inventories that are being sent to the desk, if the firm is able to systematically capture this data, then actual flows and fills can be used to detect and recognise patterns in quotes and spreads. If it is possible to detect changes in what is being traded, then we can work out where a broker is in terms of their positions.
Firms do need to be a little more autonomous to pull the data together in order to analyse it. This is part of the ongoing behavioural development of the buy-side, and it is time that these changes were fully embraced. The responsibility of the buy-side to take ownership of this area, not just from the viewpoint of collecting the data, but analysing that data and taking action resulting from those results, means that more proactive steps will surely follow.
Attitude versus technology
As more and more CEOs, CIOs, compliance officers and finance officers realise how important it is to trade correctly, then there will be an uptake in the numbers of firms taking ownership of that on the buy-side.
This is partly a reflection of the maturity of the industry. There is more automation, lower margins, fewer people and generally a more efficient product. As regulation continues to tighten and the technology continues to improve, the industry needs to keep re-evaluating itself and driving further forwards. What the industry needs to do is to start capturing the brains that are heading towards Silicon Valley for their careers rather than towards finance. A more holistic approach to best execution methodology is just one of the areas where firms can make wholesale improvements in their approach to technology and data, and better use the data that they already have access to.
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