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The Future of Trading

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Calculating Cost First, Trading Second

November 4, 2010
By Chris Kentouris

As real-time analytics gains particular popularity one particular tack known as predictive analytics may become the wave of the future, according to Celent’s Habbal. Pipeline, for one, has already developed what it calls an Algorithmic Switching Engine that predicts the performance of algorithms under real-time conditions based on information from the post-trade analysis. “It takes a trader's instructions about how hard the trader would like to drive an order into the market and translates that minute-by-minute into a choice of an algorithm style, price limit for an algo, the control parameters on that algo and the size of the orders sent to that algorithm, and then the algorithms execute it," says Waelbroeck. Currently, Pipeline's switching engine can accommodate more than 100 algorithms and is adding about 10 more each month.


Just how effective is such switching? From January 2009 to May 2009, AllianceBernstein conducted a joint study with Pipeline Trading to define "adverse selection" and measure the effectiveness of predictive switching on adverse selection costs. Alliance Bernstein used a dark aggregator – a program that aggregated orders in dark pools that would match a given set of orders at a given price from a different sell-side provider while Pipeline ran its Algorithmic Switching Engine. The study showed that Pipeline's predictive switching strategy -- as compared to a common dark aggregator strategy -- saved as much as 70 percent of the costs attributed to adverse selection. The engine switched strategies, on the fly, when it saw that the original algorithm was wrong.

While stocks remain the dominant asset class for transaction cost analysis, there has been a growing push for TCA in other products which have to date been limited in large part because of the lack of sufficient market data and interest from fund managers.

As fund managers now understand the importance of including other financial instruments as asset classes in their analysis of best execution they are demanding the same sort of TCA.

Nowhere is the need for TCA more pressing than in foreign exchange transactions as was evidenced by a lawsuit filed last year by California's largest pension plans – the California Public Employees Retirement Plan and California State Teachers Retirement System -- against Boston-headquartered custodian bank State Street. They allege that State Street fraudulently priced foreign exchange trades which resulted in extraneous costs of over $56 million since 2001.

But performing TCA on FX trades is no easy task. While the market for foreign exchange trades is highly liquid, it is also highly fragmented across dozens of over-the-counter platforms. Making matters more complicated is the fact that not all custodian banks timestamp their trade executions, which would permit the fund manager to use benchmarks traditionally adopted for the equities market to determine values at any given point.

"For fund managers which have time-stamped trades we can offer traditional equity metrics and for those which do not we can perform analysis that is analogous to volume-weighted average price measurement ," says James McGeehan, chief executive officer for FX Transparency, a Boston-based firm specializing in transaction cost analysis for foreign exchange transactions.

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