Facing inconvenient truths about trade-cost trade-offs and execution performance: TCA must keep up

Transaction cost analysis (TCA) has come a long way in 30 years, but market structure innovations have obfuscated the true execution performance picture. As investment managers face inconvenient truths about trade costs, TCA solutions have a key role in the pursuit of best execution.

Addressing trade-cost trade-offs

Portfolio managers and buy-side traders are under tremendous pressure to consistently produce performance results for their clients. As low-fee passive investment alternatives proliferate and margins get squeezed, every cost is questioned.

Trade-cost trade-offs occur when traders balance opposing trade-cost dynamics to achieve the lowest overall cost of trading. Increasingly these trade-offs are under the microscope, as market structure innovations – from high-frequency market making, broker dark pools and systematic internalizers to maker-taker rebating – raise concerns about significantly higher hidden (implicit) costs compared with observable (explicit) trade costs.  

As data visualization, venue analysis and transaction cost attribution analysis (TCAA) techniques grow in sophistication, buy-side traders are becoming better equipped to understand the trade-cost trade-offs, and are using these analytics tools when deciding which brokers to select. Brokers that seek to gain a competitive edge by charging lower commission rates may find themselves falling behind in execution performance scorecards when deeper TCAA uncovers considerably higher implicit costs associated with their executions.

The need to disentangle all the complex implicit and explicit trading costs that affect investment performance is a real problem for buy-side firms. Anecdotal evidence indicates that for every one basis point saved from venue fee-sensitive routing or dark-pool preferences, execution performance is often lost because of significantly higher hidden trading costs.

Trade-offs: an inconvenient truth

Figure 1 illustrates a thought experiment in trade-cost trade-offs. Let us suppose that an investment manager trades through two brokers, broker A and broker B.

• Broker A is a high-cost broker but is fully venue-agnostic. TCA reports show that, on average, explicit trade costs are tilted higher, toward the upper quadrant, while hidden costs are tilted toward the lower quadrant (i.e., the costs are less). The combined effect is an overall execution performance that tilts toward the upper quadrant.
• Broker B, on the other hand, is a low-cost broker but is exceedingly sensitive to venue maker-taker fees, and needs to preference certain dark pools to help cut costs. TCA reports show that, on average, explicit trade costs are tilted toward the lower quadrant, while hidden (implicit) costs are tilted higher to the upper quadrant. The combined effects result in an overall execution performance for broker B that falls behind that of broker A.

Although this example is theoretical, it highlights how lower explicit trade costs can often lead to higher hidden (implicit) costs, resulting in reduced overall execution performance. It also helps to emphasize just how much of a problem disentangling the complex trade-cost trade-offs affecting investment performance is for buy-side firms when they provide best-execution reports to clients and regulators.

Figure 1: The inconvenient truth about trade-cost trade-offs and performance

Source: Chartis Research

TCA today: solutions must adapt

TCA has come a long way since the seminal work of André Perold* more than 30 years ago. But today’s TCA must keep up with the ever-changing liquidity landscape and convoluted trade-cost trade-offs, to provide traders with quick and easy access to all the key top-down strategy and bottom-up venue trade-cost statistics. To make them more transparent, implementation shortfall (IS), volume weighted average price (VWAP), and other performance benchmarks need to be broken down into parent order-level costs (spread capture, timing contribution, delay cost, opportunity cost, etc.), as well as venue-level statistics (impact cost, adverse selection, dark pool counterparty analysis, maker-taker rebates [if applicable], etc.) – while controlling for market-level variables such as volatility, liquidity, and market and sector betas.

As buy-side traders pursue optimum performance, and with MiFID II (RTS 27/28) and revised SEC Rule 606 demanding more disclosures around order handling and routing, data visualization and desktop trade-cost attribution will be essential tools for trade-cost measurement, prediction, and broker-selection decisions. Investment managers continue to seek not only transparency around transaction costs, but also a better understanding of how execution algorithm parameter settings and smart order-routing logic decisions play a role in execution performance and, ultimately, the performance of the fund.

Further reading

Future Chartis research on market structure will address the key technology trends that are of ongoing importance for buy-side investment managers. These include transaction cost analytics, execution algorithms, smart order routing, artificial intelligence and machine learning, order management systems, execution management systems, securities exchanges, alternative trading venues, bank capital and liquidity, and in-house vs. outsourced trading.

Chartis plans to publish an in-depth TCA market quadrant report in Q4 2020/Q1 2021.

• Hedge Fund Risk Management Technology, 2018

(Chartis, 2018)

• Risk as a Service for the Buy-Side, 2018

(Chartis, 2018)