In our initial observation of the Tick Size Pilot*, we found a shift in liquidity from off-exchange venues to exchanges in G3 and a shift from maker/taker to inverted exchanges across all test groups. However, we did not observe the same increase in impact costs that other studies found. We concluded that the pilot may be showing signs of improved liquidity capture for institutional investors and we committed to measure and report the results of the pilot in the future.
After a year of collecting and analyzing data, we have compiled our findings in a whitepaper, Tick Size Pilot: Year in Review. Our assessment is that the pilot has not completely achieved its overall intended objective, but it has highlighted some interesting dynamics that affect market microstructure.
The pilot was successful in transferring flow from maker/taker to inverted exchanges as competition in maker/taker exchanges increased. Relative to the Control Group, we observed:
- 2x more inverted exchange volume across all test groups
- 25% decrease in off-exchange volume in G3
- An increase in midpoint exchange and off-exchange volume across all test groups
- No significant change in block volume or average trade size in any test group
As passive liquidity became more competitive, Clearpool’s algorithms were able to effectively balance the shift in volume. While there were fewer opportunities to add liquidity at the full spread, we captured more liquidity at the midpoint compared to the Control Group, and we improved impact costs and trading fees overall. Once it became less efficient to add liquidity passively, our algorithms adapted and shifted their behavior to opportunistically remove liquidity from inverted venues where the rebate would offset trading fees.
Essentially, because our algorithms are programed to dynamically adapt to market structure changes, we were able to counterbalance the microstructure effect on impact costs and trading fees, leading to overall improved impact costs and trading fees for the pilot compared to the Control Group. Here’s how Clearpool’s algorithms responded across all test groups:
- 76% increase in opportunistic liquidity removal
- 42% decrease in high-impact liquidity removal
- 35% increase in midpoint liquidity capture
Some other algo providers cited a decrease in their performance, which could have been exacerbated by those algos that were hardwired to capture the rebate and not capable of adjusting to market microstructure changes in real time. It will be interesting to see how brokers who prioritize rebates in their routing protocols will respond to the proposed Access Fee Pilot.
I invite you to view the full results of our Tick Size Pilot: Year in Review and encourage clients to contact their Clearpool relationship manager to discuss the findings. Not yet a client? Learn more about the Clearpool Algorithmic Management System and Venue Analysis or request a demo to learn how we can help.