06.20.2014
By Terry Flanagan

Pre-Trade Analytics In Focus

Traders are taking advantage of pre-trade analytics tools to determine which trades to enter into and their expected profitability.

“With respect to forecasting available liquidity, traders can use statistical regularities in venue selection for block activity to help determine liquidity,” Henry Yegerman, trading services product specialist at Markit, told Markets Media. “Additionally, robust statistical analysis of IOI activity gives traders better insight into establishing actionable liquidity.”

Complex Event Processing (CEP) that combines real-time surveillance analysis with historical performance correlations is at the forefront of quantitative analysis of trading and trading technology, Yegerman added.

The Markit Pre-Trade tool estimates how market impact is created from the cumulative costs of crossing the spread and setting new price levels to obtain liquidity by calculating the “tick risk profile” of each stock. This allows for the forecasting of the market impact of the trade.

Real-time alerts help traders to better control market impact intra-trade. “Taking action on these alerts lets the trader cut out orders from the negative tail of market impact performance which contribute the most to trading under performance,” Yegerman said. “This may involve changing strategies, speeding up or slowing down trading, modifying limits or any number of remedial actions.”

The value of real-time TCA in achieving best execution is to a large extent a function of the information quality of the real-time metric. “Merely producing a relatively uninformative metric in real-time still does not result in useful or actionable information,” Yegerman said. “It is critical that real-time alerts signal to the trader what is happening in the market.”

Through a partnership between Markit and Eze Software Group, Eze Software clients can leverage Markit’s TCA product to view pre trade forecasts alongside their open orders in the Eze OMS trading blotter. Following the trade, the customer’s data is automatically processed by Markit’s TCA service to provide actionable trading insights that help reduce trading costs and identify liquidity.

Typically, TCA products rely on order allocation records, which are aggregations of individual executions. Markit calculates implementation shortfall by looking at each individual execution, according to Yegerman, thereby improving execution and reducing trading costs by breaking out the impact of the trader’s own activity from the wider movements of the market.

Another factor influencing the take-up of pre-trade analytics is the preponderance of low-touch trading platforms.

Buy-side trading desks are resource constrained, averaging just under four traders according to Greenwich Associates Trading-Desk Optimization Study. Fewer traders handling more flow means increased interest in trading electronically. Due to similar resource constraints and shifting business models, top-tier brokers are encouraging the e-trading behavior investors are asking for.

Feature image via iStock

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