As equity algorithms have become a commoditized standard for buy-side trading organizations, technology innovation once again is helping the trading desk evolve to keep up with the changing needs of traders. The past few years have seen multi-asset trading systems proliferate on the Street as firms now routinely trade beyond equities and across country lines.

With this trend comes the burgeoning demand from the buy side for cross-asset algorithms, and sell-side providers are stepping up with packaged strategies for trading multiple asset classes simultaneously. Instinet, for instance, has been focusing on building out its multi-asset trading platform and now offers algorithms for trading across equities and options on its platform.

John Comerford, global head of trading research at Instinet, explains that while options traders traditionally have used simple trading styles for hedging the equity legs of their trades, the availability of multi-asset execution management systems (EMSs) and other cross-asset trading tools is allowing them to pursue more sophisticated trades. "A lot of our hedge fund clients are clearly the drivers for this, just as they were the big drivers in equity algorithms five years ago," he says. "As traders are putting on calls to hedge out the equity side, or as they're buying equity to cover calls to get some extra yield on a trade, they want the same tools they are used to on the equities side for the options side, and the underlying algorithms are key."

Adds Vijay Kedia, president and CEO of FlexTrade Systems, "Cross-asset algorithms and cross-asset trading are becoming more and more prevalent. A year or two ago the trend was multi-asset trading, but now customers have been doing that, and the next step was how to trade multiple asset classes simultaneously while looking at relationships [between the asset classes]."

According to Kedia, FlexTrade offers clients the ability to trade foreign exchange and futures in a cross-asset fashion, as well as equities, FX and derivatives, such as options, equity options and futures. He points out that in many cases buy-side users want to keep their strategies private, so FlexTrade offers a number of off-the-shelf algorithms that clients can then customize. Liquidity and connectivity, Kedia adds, are key to the value of these cross-asset algorithms, as is extensive research between the asset classes. "In these cases the quants definitely bring the extra edge," he notes.

Weighing Options

Brian Fagen, cohead of liquid market sales for the Americas at Barclays Capital, says the majority of the focus and development of cross-asset algorithms has been on the options space because many options traders also trade equities. "The algorithms help options traders trade both the option itself and the underlying hedge for the option or trade based upon a relationship between the two, such as volatility or delta," he explains. "These are mostly utilized at hedge funds where typically they tend to traffic more in options products and they tend to be doing the types of trades that require both the option and the underlying [hedge]."

According to Fagen, cross-asset algorithms originated on sell-side options trading desks that were trading these types of products internally to hedge their books more efficiently. "From there it's a relatively easy step to package that up and deliver it to an external client," he says.

Going forward, Fagen adds, he expects more cross-asset algorithm work in the foreign exchange space, particularly as algorithms across geographies become more popular. "The ability to hedge an FX exposure as a trade is happening in an algorithmic fashion is important," he insists.

Fagen also sees potential for these types of algos in program trading, in which firms trade a list of stocks across multiple countries and currencies. "To have algorithmic functionality that would automatically hedge that currency exposure as the trade was executing to minimize slippage would be key," he says.

FlexTrade's Kedia also sees interest in fixed-income cross-asset algorithms. "There is a lot to be done with interest rate products and cross-currency products," he asserts. "Now that the liquidity and electronic trading has picked up, it's bound to become a big component in cross-asset trading."

Not Yet Ready for Prime Time

While Barclays' Fagen sees the potential in these advanced cross-asset algorithms and acknowledges that a subset of sophisticated clients already are interested, he says these types of algos aren't mainstream quite yet. For one thing, front-end customization is needed to drive adoption of cross-asset algorithm offerings. "They need parameters that can be set around areas such as how much drift you'll allow or what minimum increments of size you want to trade at," Fagen comments.

In general, however, the industry is starting to see accelerating convergence of electronic products across asset classes, Fagen adds. He points to equities, FX, futures and the fixed income space as key areas in the trend. "We're starting to see more and more cross-pollination [of asset classes] where related products that will give clients the ability to trade those instruments more in tandem makes sense," Fagen explains. He cautions, however, that cross-asset algos likely would be effective only for instruments for which the trading relationship is inherent, not necessarily for products such as equities and commodities.

"Much of the development of [algorithms] has been done in isolation, so bringing them back across assets requires work on the technology side," Fagen notes. "That is less so when you talk about, say, equities, options and futures; [it is] more so with equities, FX and fixed income, for example."