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Innovate to Differentiate: Advanced Simulation, The Next Frontier in The Execution Arms-Race
Traders Magazine Online News, March 6, 2019
Trading technology has always been at the cutting edge of financial markets. As technology has evolved from carrier pigeons, to telegraphs, to microwave communications and beyond, traders have always been pioneers. Over the course of the last 100 years or so it is not an exaggeration to say we have progressed from the speed of flight to the speed of light as financial firms have continued to push the envelope of innovation.
The same is true on the execution desk, where sell-side firms have had to innovate to differentiate in a highly competitive market. In addition to competing with peers for order flow, sell-side brokers have seen their customers grow in sophistication over the last decade; asset managers and hedge funds have increasingly deployed advanced analytics, often recruiting expertise from the banks themselves. Where speed of execution had once been the battlefield for so long, advanced analytics is where the arms race has shifted.
Development has progressed at an ever increasing pace as sell-side desks look to win increased order flow by offering more advanced tools than their competitors or, indeed, what institutional customers can deliver for themselves. Perhaps the most important development in the last 15 years has been algorithmic execution. Together with the fragmentation of liquidity across a multitude of new lit and dark trading venues, this innovation has led to an explosion in the number of execution options available to the buy-side. But the question remains: has all this led to better performance in trade execution?
Algo selection remains a thorny issue and has proved to be surprisingly hard to grapple with, even when using technological or statistical solutions. Measuring and reporting best execution continues to be loosely defined by regulators and is open to interpretation. This, coupled with a bewilderingly wide range of alternative algos to select from and the fact that the majority of total cost analysis (TCA) tools are provided either by the brokers or trading platform providers, has made algo-selection challenging for the buy-side. It has also left sell-side firms struggling to differentiate themselves from their peers.
New algorithms are launched into the market with great fanfare but data supporting the veracity of their performance has sometimes lagged behind. Third party vendors have tried to provide technology-based solutions to fill this gap. Independent ‘best execution’ benchmarks have been created ranging from TCA tools to ranking the execution quality of brokerage firms on a “broker wheel”. Many Order Execution Management Systems (OEMS) vendors now provide these analyses directly to the buy-side trading desk through their execution platforms.
However, like all algorithmic approaches, these have several inherent flaws and while buy-side institutions are obliged to repeat the disclaimer that “past performance is no guarantee of future success”, this is just as apparent when benchmarking algos as it is when back-testing portfolios.
Ultimately, traditional tools and methodologies fail to address two fundamental questions:
- How can we determine what future performance will look like using only historical data?
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