This week our question is for the Head of Electronic Trading at a recognized algorithmic trading firm.
Q: Where do you think trading execution is heading over the next five years?
A: The evolution and transformation of Wall Street trading desks over the next several years will continue to move further away from the traditional trading desks that we are all accustomed to. The “quant’ has taken us from a high touch sales trader environment to a low touch computer driven world in a very short period of time. Algorithms have reshaped how we trade and will continue to capture market share and dominate trading due to their ability to process large volumes of order flow in a very cost efficient manner.
Over the last several years the equity markets are not the only market centers that have become automated and started using algos. The options markets now trade on an automated platform and one of the areas where we will see a change in trading is algorithms becoming more efficient at trading across multiple asset classes simultaneously. Algorithms will identify and capitalize on any arbitrage opportunities that take place within any investment vehicle deemed to be correlated.
Some market structure analysts have referred to market fragmentation and the costs associated with it as, “the race to the bottom.” Market fragmentation has dramatically driven down trading costs, but has also transferred liquidity from a handful of destinations to dozens. What I foresee happening, is the marketplace will become more consolidated-as only the strong will survive. The dark pools and ATS’s with the most volumes will drive the lower volume destinations out of the game. Not only is it a volume dilemma for some of the lower volume destinations, it is the processing of quote traffic and trade data that has become cost prohibitive. Servers only a few short years ago would process somewhere around 40 quote updates a second and now that number could conceivably be 400 quotes a second.
Another area of change, is firms will need to do a better job deciding which algos best suit that firm’s business model; one stop algo shopping will not work going forward. The better suited the algo, the better cost analysis that can be done, resulting in bringing down trading costs even further. Because a destination is the cheapest does not mean that they will be best suited to a firms bottom line. If an algo has a lower hit rate than other algos, the result is latency and in a world where we are trading in microseconds a delay of any sort could be costly.
