Power to the Buy Side

Terry Flanagan

The buy side is experiencing an unprecedented wave of empowerment as it assumes control over functional areas that were formerly delegated to the sell side. These include the ongoing shift toward electronic market making in other asset classes besides equities, such as FX and futures, automated trading, algo developments, predictive analytics and visualization tools, and workflow optimization.

The goal within the buy side “is to actually take control of algo development, algo routing, algo decision making, algo enhancement,” said Alfred Eskandar, CEO of trading systems provider Portware. “There’s another set of in-housing which is venue analysis, algo selection, broker selection, etc. And of course the whole multi-asset capability, the ability to have analytics and multi-asset capabilities as sophisticated if not more sophisticated than some brokers actually are themselves.”

“FX, TCA, and fixed income have been very hot,” added Eskandar. “We can talk about the ‘electronification’ of these markets in the same vein as that of equities. The complex workflows on the equity side are all about automation.”

Buy-side demands for custom workflows, particularly control over order routing, has been a major theme in 2014. Buy-side conversations on custom, global multi-asset systems have turned into initiatives, with senior management recognizing that technology is not just the answer to cutting costs, but the path to gain a measurable advantage in today’s complex market structure.

One manifestation of buy-side empowerment is the move of the sales trader function away from the sell-side to the buy-side, resulting in more self-directed trading by buy-side firms and more control over the quality of execution. But that doesn’t necessarily imply a diminished role for the sell side, merely a changed one.

Alfred Eskandar, Portware

Alfred Eskandar, Portware

“Because we run our own algorithms, most of what we do is driven by ourselves, but the Street’s still very important to us,” said Nick Nielsen, head of trading for Marshall Wace, an equity long/short hedge fund that employs a process-driven and fundamental-driven trading strategy across multiple geographies and time horizons. “We use their dark pools quite a bit, we use them for advisory services, we use them for equity capital markets, so I think just the nature of the relationship is changing, not that it’s any better or worse. It’s just that there are value creations in different areas.”

Marshall Wace, with $18 billion in assets under management, has been fully automated for a number of years. “We’re incredibly automation focused,” said Nielsen. “The technology is maybe less important than it had been maybe five or six years ago. It seems that people that are automating now are pretty late to the game in the technology area that they focus on.”

Marshall Wace employs three models for TCA, according to Nielsen. The first, the so-called allocation approach, involves parceling out chunks of an order to different brokers and comparing their performance.

The second model for TCA is to compare performance against a specific benchmark, such as VWAP. “You might give someone a VWAP order and compare their performance against the actual benchmark,” said Nielsen.

The third model is for the firm to place the orders itself, and measure the results, looking at the fill rates from the different counterparties.

The objective is to generate alphas as “an alpha overlay on the execution process,” Nielsen said. “Quantitative research into how aggressively you trade, when you trade, etc., is probably more important. People are trying to automate the technology, but the important part, once you have that, is the actual research or strategy.”

Tapping into the past decisions of the portfolio manager and quantitatively applying the findings, a process known as alpha profiling, is part of a next frontier of ‘smarter’ trading that embeds business intelligence into trading, according to some practitioners.

Buy-side traders are more likely to draw fire by moving slowly on a trade order and having the price move in the wrong direction, rather than quickly filling an order which then goes bad. Thus traders tend to err on the side of front-loading trade executions, a systematic and unwarranted risk aversion that can be addressed by alpha profiling.

If traders can quantitatively identify situations where it makes sense to trade more slowly and the portfolio manager can be brought on board with adopting this strategy, then over time firms stand to save large amounts of money.

Featured image via Sergey Nivens/Dollar Photo Club

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