Earlier versions of FIXatdlSM changed quite significantly from a structural standpoint, requiringmany iterations of the Parser. For instance, the placement of Strategy Parameters shifted between Top Level and Strategy Level, which required code changes. The more recent versions come with fewer structural shifts, and more often introduce new elements/tags/attributes, which makes it easier to update the parser. The parser is a good example of something the Working Group can provide as Open Source, as it will help manage version upgrades smoothly and maintain backwards compatibility.
Once the parser is upgraded to produce the appropriate Data Objects, the GUI Generator must, occasionally, also be upgraded. Here, two changes in FIXatdlSM are important to note. First, simple structural moves (i.e. shifting Strategy Parameter locations) should require no changes and produce the same screens; a good parser implementation will abstract this from the GUI Generator. Second, whenever new elements/tags/attributes are added, new code must be created to leverage the changes. This is another place where the Working Group can create Open Source software: a library that generates algo screens and has hooks to allow for proprietary layouts, so that every EMS can have its own look and feel. The layout and general look and feel is custom to each system, but the creation of the screens, their functionality, and the FIX values they produce is fairly generic.
As long as the FPL Algorithmic Trading Working Group grows FIXatdlSM and produces new versions, code must adjust to these changes. Many of the software updates necessary for each new version of FIXatdlSM are common, and Open Source software provided by the Working Group goes a long way to ease the development burden.
Where do you see algorithmic trading expanding: e.g. new trading arenas, asset classes, etc.?
I have seen an uptake in algos that trade multiple assets together, and I think this will continue to grow. There has been increased interest in Pairs Trading, with a number of new players entering the market. I think the execution quality and adaptiveness of these algos still has room to grow, as many are in their first generation. I can also see growth in Option algos, which can help facilitate spread trades and achieve floating delta exposures, as well as the development of Basket algos to facilitate portfolio rebalancing.
In terms of asset classes, I foresee growth in algos trading Commodity Futures, where the market is currently lagging. I think there will be more focus on ETFs and potentially automating the trading of Index Swaps. I suspect we will also see algos starting to trade across asset classes. There is an appetite for trading Equities against Futures, or ADRs with an FX component to keep constant currency exposures. I think the overall industry will move towards focusing on exposure over particular asset classes.
I think that the next generation of algos will become much more adaptive, stepping away from a single execution pattern (e.g., VWAP or IS). This generation will monitor the market as a whole and contain various modes, transitioning in response to volume, volatility, and price points. We have already seen, from a few vendors, the beginning of this evolution. This will be a differentiator since it allows traders a ’best of many worlds’ scenario and will model real trading more accurately. I also see automated feedback from algos coming into focus, where some of the analyses used by the algo to make decisions is kicked back up to the traders for enhanced market color at some manageable frequency. There is already nascent motion on this as well.
