In mid-2020, Securities and Exchange Commission (SEC) Rule 606(b)(3) came into full implementation. Rule 606(b)(3) (aka “Institutional 606”) adds an impressive data source for the buy side to help them navigate the increasingly complex world of order-routing analysis, execution quality review, conflict of interest management, and information leakage minimization. However, the information contained in the Institutional 606 reports is only delivered upon request by the buy side, so the question has to be asked – will the buy side be looking to the sell side to provide these reports?
Two years ago, we wrote a blog post, M-ELO Shows Signs of Better Quote Stability Than Other Nasdaq Passive Order Types, concluding M-ELO was a viable option for midpoint liquidity because of its lasting quote stability post-execution compared to other Nasdaq midpoint order types.
A critical component that determines an algorithm’s success in sourcing liquidity is how it rebalances—or decides which venues to route to based on where it already sent orders and received fills. Many algorithms claim to "intelligently" source liquidity but still rely on static previous-fills heatmap data. However, if you use a genuinely dynamic Liquidity Awareness Signal, it's possible to achieve a nearly 500% improvement in hit rates for midpoint orders*.
Concerns about conflicts of interest have long been top of mind for players in the equity trading space. There's been no shortage of discussion around protecting the interests of end-investors and rooting out conflicts in broker routing. Much of the industry's regulation aims to address those conflicts, including the SEC's proposed Transaction Fee Pilot. Had the pilot received approval, it would have studied how exchanges' pricing may create conflicts of interest for broker-dealers, which in turn may harm investors.
For the first time in 20 years, we witnessed a Level 1 cross-market trading halt on March 9, 2020. It was followed by three more days where the Level 1 market-wide circuit breakers (MWCB) were triggered and the markets halted due to significant market declines with the potential of exhausting market liquidity.
The title of a recent blog post, “How Fast Should You Trade”, brought me back to the early ’90s and one of my favorite rap songs, “Sometimes I Rhyme Slow Sometimes I Rhyme Quick”, by Nice and Smooth.
The massive amount of market data available in the current day is both a boon and a burden. More information can lead to making smarter decisions, but does the glut of data lead somewhat to paralysis by analysis?
As we enter the season of market structure conferences, we are sharing Clearpool's annual Market Structure Viewpoints—our view of some of the most pressing equities market microstructure matters that support transparency and fair and equitable access to our markets.
By definition, rebalancing—also known as reloading—is an algorithm's ability to dynamically respond to source additional liquidity based on its assessment of the liquidity landscape after its baseline route to the “Street”.