As standards in transparency and technology have evolved over the past few years, today’s markets are undergoing changes that are both behavioral and technological in nature. One of the most notable observed changes is that securities are becoming hard to borrow (HTB) and more expensive at a faster pace.
As managers try to adapt to the changes, it is important to understand the underlying drivers so they are better equipped to optimize their strategies. Technology, as in everything, is bringing new efficiencies and transparency to the securities lending market. The reliance on data from multiple sources has now become commonplace and is embedded in trading desk algorithms and trading systems.
An increasing number of lenders are utilizing technology platforms with analytics and machine-learning capabilities to determine the opportunity costs of lending. Further, bots and other forms of AI are being used to scan news articles and social media for mentions of a security to gauge its demand.
The use of big data and AI is driving transparency and speed, helping with price discovery and providing insights into the depth of the market. Yet, not all participants are applying data in a uniform way, leading to inconsistencies and distortions in rates, which are hitting the tape at a faster-than-ever pace, with ever-wider visibility.
It is important for managers to note that these rates are not always set and things can shift overnight in the securities lending market. That’s why it is critical to partner with a prime broker who can provide a bird’s-eye view of the market and let them know whether the rates are market-set or a short blip.
Another factor exacerbating the situation is when securities experience both lowered supply and heightened demand, a typical issue faced in bearish markets, and one we have experienced recently in the wake of the pandemic sell off. Generally speaking, bearish sentiment causes investors to pull back on lending, as they seek to offload their holdings or refrain from supporting short sellers. We witnessed this first-hand in late March and early April when a bearish sentiment in the market led to increased strain on securities lending.
Maintaining open and frequent communications with prime brokers, particularly in such markets, can help hedge funds get a better handle on the market, as prime brokers can provide the much-needed visibility into the HTB supply based on their broad read of the market and internal supply.
Lastly, managers should be aware that automatic settlement is going to become more prevalent – due to the impending implementation of mandatory buy-in frameworks in Europe – and thus failing on a settlement without repercussions will soon become a thing of the past. The impact of this is that market participants will have to be extra careful when providing locates on less-liquid securities for short sales.
Further, broker-dealers will likely pay higher fees to avoid failing to deliver these securities and incurring the associated penalties. This will likely lead to more participants “buffering” their loanable supply because they don’t want to create unnecessary fails, considering that in such an event there are charges to incur on top of potential settlement risk. With penalties increasing, higher risk may demand higher cost, like any other market. Ultimately, all these drivers will create new trends in the evolving securities lending landscape.
In the age of big data and AI, the trend of rapid rate changes and securities becoming HTB shows that this will likely continue to be a phenomenon for the foreseeable future. Managers will remain under pressure in the short term to find opportunities in a supply challenged market.
Choosing a prime broker with a strong internal supply and a large visibility into the retail market can help managers to demystify the inconsistencies in the market and offer better pricing power.
Published in HFMTechnology, August 4, 2020.
Mark Aldoroty is a Managing Director for BNY Mellon | Pershing. He leads Pershing’s Prime Services and Collateral Funding and Trading teams. Prior to this role, Mark led the Prime Services Sales and Relationship Management teams.