This week, 27 of our buy side members came together at one of our Digital Cafés to share their advice, challenges, and experiences on how they are accessing Fixed Income liquidity in 2023.
Our discussion centred around the infrastructure needed, platforms that are currently being used, decision tree frameworks to establish the best path to trade, and improving the reliability and accuracy of axes.
Infrastructure to Maximise Liquidity Access
It’s clear that different asset managers have different approaches to using an EMS (Execution Management System). An EMS is considered an important component of the trading process for its ability to provide an aggregated view of liquidity and full functionality to merge, split, or execute orders. Most of our members currently use an EMS to supplement their existing OMS (Order Management System), most commonly from one of Charles River, Bloomberg AIM or Aladdin. Several EMS platforms continue to be evaluated amongst other members who do not currently have one, most notably T.S. Imagine, Flextrade and Adroit. However, EMS alone is not sufficient to address all market challenges. Therefore, there is a need for an interoperability layer that can integrate internal and external data sources seamlessly.
Moreover, the use of industry utility solutions, such as Neptune, is crucial to aggregating dealer inventory and ensuring quality access from dealers. Neptune is considered an efficient way for the buy side to receive quality axes from dealers as it provides the same feed for dealers who send out data via 3rd party platforms and aggregates this view.
Beyond the Big 3 – Which Other Platforms Are Being Considered by Our Members?
Improving Pricing and Reliability
While the big three platforms (Tradeweb, MarketAxess, and Bloomberg) are popular choices for Fixed Income trading, it’s worth exploring other platforms that may offer more specialised services or better liquidity in specific regions. Most notably, other platforms being used or now considered by our members include Liquidnet, LedgerEdge, TransFICC, Fenics and Trumid, who are all offering a more specialist approach to liquidity and have been shown to offer significant liquidity benefits, specifically with certain products or regions.
Different portfolios will have different needs when it comes to Fixed Income trading. Some portfolios may have high volumes of low nominal value bonds and may benefit from using a platform like MarketAxess or Tradeweb, while others may need to trade larger ticket sizes and may prefer to go directly to counterparties, or use a more specialised platform.
Platform Evaluation – Key Considerations
Cost vs. return: Trading costs can vary significantly between platforms, and it’s important to consider these costs when evaluating options. Bloomberg may be more expensive, but it may offer better liquidity for certain types of bonds or in certain regions, whereas MarketAxess may be more cost-effective for trading certain types of Fixed Income securities, such as credit default swaps.
Connectivity and flexibility: When evaluating Fixed Income trading platforms, it’s important to consider the connectivity and flexibility they offer. Adroit Trading Technologies, for example, has designed its platform to be as close as possible to the APIs within the EMS’ themselves, which provides flexibility in architecture and design. Similarly, TransFICC has focused on creating a highly flexible and customisable platform that can integrate with a variety of EMSs and other trading tools.
Speed and efficiency: In today’s fast-paced trading environment, speed and efficiency are critical. Look for platforms that offer fast and reliable execution, as well as tools for developing and executing algorithmic trading strategies. Liquidnet, for example, has a suite of tools for algorithmic trading, including a smart order router and an execution algorithm engine.
Transparency and compliance: With increasing regulatory scrutiny on Fixed Income trading, it’s important to prioritise transparency and compliance when evaluating platforms. Look for platforms that offer robust reporting and compliance tools, as well as features for managing pre- and post-trade risk. Tradeweb, for example, offers a range of compliance tools, including pre-trade credit checks, regulatory reporting, and transaction cost analysis.
Improving pricing requires a multi-faceted approach that considers differences in Fixed Income products, the importance of automation, the development of better pricing models, and the need to build a strong buy side consensus which can influence the quality of pricing data and axes you receive. By focusing on these areas, buy side firms can improve pricing accuracy, respond more quickly to market changes, and build stronger relationships with their clients.
In the US market, leaving a request for quote (RFQ) out for 10-15 minutes might be sufficient, but in Europe, the time frame is much shorter, typically 2-3 minutes. This means that buy side traders need to be able to act quickly, which puts pressure on sell-side firms to provide timely and accurate pricing. Solutions could include improving automation, utilising data sources that provide real-time information, and developing algorithms that can respond quickly to incoming RFQs. Our members have suggested 4 areas which can help improve axe dissemination and pricing reliability:
Focus on automation: Automation is key to providing better prices and reacting more quickly to market changes. Buy side desks are investing in technology that streamlines pricing processes, including automating data collection and analysis, as well as utilising artificial intelligence and machine learning algorithms to improve pricing accuracy.
Develop better pricing models: To provide accurate pricing, firms need to develop better pricing models that take into account market data as well as internal valuation information. This can be especially challenging in markets where there is little trading activity or limited information available, such as emerging markets or high-yield bonds. One solution could be to use a combination of different data sources and develop customised models that are specific to each market and build this up over time to create a better picture of markets.
Focus on building a strong all-to-all buy side community: The success of all-to-all platforms depends on having a strong buy side community that is engaged and actively using the platform. Firms should focus on building relationships with buy-side clients and providing them with the tools and resources they need to effectively trade on the platform.
Use confidence intervals to manage pricing risk: It’s important to recognise that pricing models will never be perfect and that there will always be some level of risk involved. One solution is to use confidence intervals to manage pricing risk, allowing traders to make more informed decisions based on the level of confidence they have in the pricing data.
Building a Decision Tree Framework to Decide Your Route to Trade:
It seems that there is a recognition of the need for a more structured approach to trade execution in Fixed Income trading, particularly as new trading protocols and market conditions emerge. Developing a framework for making trade execution decisions, based on data and analytics, as well as a clear understanding of market conditions and liquidity, may be an effective way to navigate these challenges.
Part of our discussion centred around the need for a framework or set of guidelines to help traders make decisions about how to execute trades in various market conditions. It was noted that while there may not be hard and fast rules that apply in all situations, having a basic framework can be helpful in determining the best approach for executing trades.
One potential way to develop this framework is with execution data and analytics, such as TCA (Transaction Cost Analysis), which can help traders refine their execution methodologies and determine which approaches work best in different scenarios.