Aggressive rate hikes by the US Federal Reserve this year have triggered the worst bond market decline since the collapse of Lehman Brothers in 2008. But as market participants navigate a sell-off that ranks among the most painful in history, they are doing so with powerful new tools that are helping them avoid dangerous disruptions and potentially mitigating some of the losses experienced in past sell-offs.
One of the main hazards for bond market investors during any pronounced downturn is a breakdown in market liquidity. Over the past few years, however, modern electronic bond trading platforms have provided traders and dealers with more tools that can better cope with the stresses associated with volatile markets.
Increasingly, electronic platforms rely on artificial intelligence to do the heavy lifting. Although the AI often runs in the background and might not be detectable to the user, applications powered by this technology can empower users through enhanced information and reach that can lead to vastly improved outcomes — especially in times of heightened volatility.
AI-driven applications enable market participants to peer into the traditionally opaque OTC marketplace to anonymously find potential trade partners, assess accurate pricing and execute trades by accumulating liquidity across multiple counterparties.
When bond markets are falling fast, it can be a struggle to determine the proper value of a security and find interested counterparties for a trade. This is especially true in today’s post-Dodd-Frank market structure, in which dealers carry much smaller bond inventories with which to facilitate trades. New software can help both dealers and investors identify supply and demand for bonds by combing through historic trade data to identify natural buyers and sellers of securities, as well as by anonymously searching for real-world interest based on current trades being considered by dealers’ clients . This transparency allows dealers and their clients to find natural contra liquidity and then directly engage with it.
In addition to identifying potential partners and facilitating price improvement on bilateral trades, these platforms integrate algorithms that can help trades get executed by splitting them up and aggregating supply or demand from multiple market sources. That capability is proving its worth in this year’s tumultuous markets, when dealers might not be able to find a single counterparty for, say, a $50 million bond trade, but an effective algorithm might well be able to identify a series of counterparties willing to buy $5 million to $10 million chunks.