Last year a series of events brought the issue of execution quality into focus.
Toxicity – the term used to assess how bad a trading venue is for executing orders at an optimal price or returning high numbers of bad fills – is a major factor.
The release of Flash Boys (one of the mostly hotly discussed issues at last year’s TradeTech) brought issues around the presence of high frequency trading (HFT) in venues to the attention of end investors and the wider public.
This was quickly followed by legal action in the US against some dark pool operators, accused of misrepresenting the amount of HFT in their dark pools. Lastly, in the summer of 2014 the UK’s Financial Conduct Authority (FCA) launched a review of best execution, and found that many firms were falling short of its expectations.
Michael Richter, director of trading analytics, EMEA at Markit, says: “This has led to a huge trend in our client base, who are all keen to start analysing and building up their data as a way to better manage the way brokers route and execute their orders.”
Taking the measure
So there is a demand for increased information on where orders execute and whether or not they are likely to be gamed by HFT, but is it possible to measure toxicity? Richter thinks so.
“Measuring toxicity is similar to measuring liquidity in that we can’t see it directly but we can identify and demonstrate its presence using data.”
Markit looks at some key metrics to help its transaction cost analysis customers spot toxicity in dark pools, asking questions of the data, such as “was there a run up in the stock before execution?” and “did the stock move away from you as you executed?”
Rob Boardman, chief executive officer of ITG, says his firm also examines a variety of key metrics, including market movements, timing of liquidity spikes and reversion.
“When we analyse toxicity for clients we need to look at what is the right measure of toxicity for them, because different clients have different priorities in terms of speed or size of execution, price and market impact,” he explains.
Of course, simply identifying the metrics and measuring them is not enough to understand the extent of toxicity. Markit has opted to adopt its own method for helping clients understand how toxic a dark pool is.
“We have developed an intuitive concept of ‘Adverse Ticks’,” says Richter. “An Adverse tick is, say in the case of a “buy” order, an execution which occurs on an uptick. Vice versa for a Sell order.
“All venues should be subject to the same macro-economic momentum factors and have more or less the same tick structure in terms of percentages of upticks, downticks and ticks that were the same as the prior tick. If you are getting a much higher percentage of adverse tickets than other market participants executing the same stock at the same order interval there is an indication of toxic activity”
For ITG, toxicity forms one of the core issues discussed as part of its execution consulting service that it launched in 2011, and is intended to help inform clients of how to act on the insights gained from execution data.
“Toxicity correlates with liquidity and you need to balance the needs of your client,” says Boardman. “Dark pools tend to be less toxic and lit markets tend to be most toxic but individual clients will have different experiences in different venues.
ITG performs toxicity measurements for both its client base as a whole and for individuals, though the latter will often require time to build up a sufficient data set to perform a meaningful analysis. Once this data is collected, consultants can then sit with clients and discuss what toxicity means for them and how they can refine their routing in order to improve execution quality and avoid being gamed.
With the growing regulatory focus on best execution and increased scrutiny of trading from end investors, it seems likely the buy-side will continue to demand more and more data and analysis to help them understand the effects of toxicity on their orders, not just in equities but across FX, fixed income and virtually any other asset class which has a sufficient data set to analyse. The key will be effectively combining data, technology and the advice of specialist experts to be exposed to toxicity only when necessary and to achieve best execution objectives.
• This article is taken from the TradeTech Newspaper, published at the TradeTech 2015 Conference by The TRADE.