Blogs

With everyone seeking up-to-the minute data, analysts and investment managers utilized foot traffic from geolocation data to quantify retail sales and disruptions to the global supply chain. The rise of new marketplaces should remove some of the onerous work of sourcing, collecting, and normalizing data feeds from multiple vendors.

The rise in off-exchange market share fueled by retail trading, liquidity aggregation on fixed-income trading desks, and how options traders adjusted to all-electronic trading during the pandemic were among the most popular topics. On the technology front, readers were drawn to the adoption of AI and machine learning by algo trading desks, ATSs and Algo Wheels.

Another trend has been the mergers and acquisitions of exchanges and bond trading platforms, and joint ventures between fintech companies and fixed-income venues. Exchanges have been acquiring fixed-income venues over the past few years, which is also driving the consolidation of liquidity pools and e-trading protocols.

Equity market participants are learning about new exchanges, order types, and periodic auctions bringing innovation and competition to the equity trading landscape. Citing the concept of “inaccessible liquidity,” asset managers pointed to the surge of retail trading by mom and pop investors whose orders are executed off-exchange on private platforms.  

While adhering to the CAT reporting timeline, sell-side firms are responsible for monitoring the CAT Reporter Portal and for fixing errors and rejects that come back from FINRA. So far, experts say the industry is doing very well with their data submissions. But error rates could escalate as the industry tackles more thorny order events and submits higher volumes of data.

It is conceivable that US equity market structure could be tested again, and brokerage firms will be counting on the resiliency of their trading systems, which is why firms need a strong order-management system with integrated equity and options analytics, including connectivity to  a breadth of other broker/dealers, exchanges, and ATSs.

Aggregation tools that pull in direct pricing streams and RFQs into an execution management system (EMS) or order management system (OMS) are becoming a critical part of creating a composite view of the fixed-income market.

The current workflow with so many “jumps” between platforms adds unnecessary complexity to an asset class which is already fragmented. We’re seeing more and more buy-side firms looking for solutions to consolidate available liquidity in one screen and to boost capacity to automate.

With the hiring of data scientists, advances in cloud computing, and access to open source frameworks for training machine learning models, AI is transforming the trading desk. Already the largest banks have rolled out self-learning algorithms for equities trading.  

Banks and asset managers relied on global teams to backup and transfer workloads during the pandemic. But, in moments of crisis, exposure to operational risks, model risks, cybersecurity attacks, and fraud can increase exponentially.