The Changing Fixed-Income Data Landscape
INSIDE MARKET DATA FIXED INCOME SPECIAL REPORT
The New York Stock Exchange's plan to launch corporate bond trading is an indication of how credit has evolved as a tradable asset class. Disparities still exist between the most liquid issues that trade like equities on quasi-exchange platforms, and those that barely trade at all. But the growing interest is fuelling demand for more data than ever before. IMD recently discussed several hot topics with leading figures in the industry and found a broad range of opinions
IMD:
What changes have you seen in the market data space over the last year with regard to fixed-income data?Ben Fortunato, director of market data, Thomson TradeWeb
: There continues to be an increasing demand for credit information, specifically corporate bond and CDS pricing. Also, the importance of low-latency feeds is increasing, which is driving more business to direct providers of market data.Ian Blance, vice president, Capital Markets, FT Interactive Data
: We have seen two main trends emerge within the fixed-income market data space over the past year. The first is a requirement for data on a broader set of instruments, with a significant increase in demand for prices and evaluations for asset-backed securities, structured products and derivative instruments. The second is the increase in firms requesting the underlying data in support of an exchange price or evaluation.Chris McGuigan, head of information services, MarketAxess
: Over the past year we have seen more pervasive use of NASD Trace data by both the buy and sell side, and it is being utilized in increasingly complex ways. Naturally, as data becomes more readily available, we are seeing an expansion in fairly typical uses, such as… end-of-day pricing and market share analysis. However, we are also seeing extensive use of data in trading models, historical back testing, and integration into both sell- and buy-side risk analysis.David Lefferts, director, Markit Group
: There has been much more interest from customers to access data across asset classes, from the plain vanilla end of the spectrum to structured instruments such as CDOs.IMD:
What are the drivers causing those changes?Fortunato
: The explosion in the credit derivatives market over the past few years, along with the convergence of asset classes, has created a demand for accurate pricing across credit. Trace has increased the transparency of the corporate bond market, but there is a thirst for broader, accurate credit pricing for best execution purposes.Matt Woodhams, global head of data and analytics, GFI Group
: Certainly for derivatives, regulation is a big driver: holders of derivative positions have to be able to value them accurately.John Nixon, global head, Icap Information:
Anything that presents an arbitrage opportunity is highly desired and encourages increased interest in algorithmic trading. New markets are being created and explored in the search for expanding new investment opportunities.Lefferts
: The demand for cross asset class information is primarily driven by the growth in hedge funds, the reorganization of trading desks to trade by issuer, and the desire for market participants to broaden their trading strategies in an effort to achieve better risk adjusted returns than any one asset class may yield.IMD:
How are changing fixed-income trading strategies affecting end-user firms' data needs?Fortunato
: End users are looking for more trade data. They are looking for specific detail, such as volume and executed pricing data. Simple pricing is no longer enough for many users.Blance:
Investors are looking beyond traditional asset classes in their search for return. Some of these asset classes, such as over-the-counter derivatives, are not as standardized as equities or bonds which trade on an exchange, and even lack standardized identifiers. Consequently, firms must work with their data providers to agree upon identification protocols for these issues. Investors are also analyzing the relationships between traditional and alternative asset classes. For example, a corporate bond asset manager often now tracks the equity, debt and credit default swap markets for the issuers in which they are investing. Because of this, firms require more extensive reference and market data for each of these asset classes.McGuigan
: We have encountered increasing demand for a variety of data due to the strong growth in hedge funds. We have also seen some limited demand in the realm of algorithmic trading, although we believe this is a nascent trend in the fixed-income markets, and only truly possible when dealing with bonds of the largest, most liquid issuers. We also are seeing increased demand from prime brokers.IMD:
What demand are you seeing for direct and low-latency fixed-income datafeeds for algorithmic trading, and how prevalent is this already?Blance:
Currently, we are not seeing a significant amount of demand for low latency fixed-income datafeeds for algorithmic trading. We believe that this may be due to the lack of electronically accessible liquidity pools for fixed-income securities.Nixon
: This exists today with the electronic trading venues such as ICAP's EBS and BrokerTec platforms. Participants who are trading electronically directly connect to the platforms and have access to a robust feed in order to fuel trading engines. What is now required is to ensure technology (servers/bandwidth) keeps up with the volumes flowing through these data feeds…. For instruments not trading electronically, the requirement leans more towards flexibility of use for the data elements rather than for low-latency requirements.Woodhams
: In the data-sets we currently provide, we are not necessarily seeing the demand for the support of algo trading directly. But we are seeing demand in terms of historic data for model calibration and testing prior to launching an algo model.Lefferts
: There is always demand for efficient, real-time data for desktops or in-house applications viewed by traders. However, the demand for sub-second, low-latency data delivery directly into algorithmic trading engines has not yet materialized in the credit markets.IMD:
What factors are driving this demand, and is it industry-wide or limited to a certain sector of the market?Fortunato
: The requirement for best execution and arbitrage trading is behind much of the demand. For traditional asset managers, compliance has become a big deal and market data plays an important role. For hedge funds, the need for speed is essential. Algorithmic trading is going to accelerate these trends.McGuigan
: We see the strongest demand from hedge funds, dealer prop desks and prime brokers.Woodhams
: Large hedge funds are looking to get an edge through algo trading and the sell-side is reacting to stay ahead.Nixon
: The need to have a competitive edge is driving this demand. The demand is industry-wide across a subset of asset classes and user demographics; mostly in the equities, foreign exchange and US Treasury markets.IMD:
How do you think this demand will evolve over time?Fortunato
: We think it likely that it will become more common for vendors to develop and provide low-latency market data management systems for datafeeds.Blance:
While the demand for low latency fixed-income data isn't very high today, we do expect that it will grow over time. We believe that one of the main factors will be buy-side firms looking beyond equities to improve their returns, which could lead them to target additional asset classes such as fixed-income securities.Nixon
: Direct feeds will complement existing information requirements – although not replace them. However, other products and ancillary data will be required to fill in the gaps to fulfill a spectrum of information and analytics requirements for trading and trade processing decision support tools.Lefferts
: As price transparency grows (both commercially and as mandated by regulators), the more liquid end of the market is likely to be the first area to trade electronically and embrace the notion of algorithmic trading (or automated trading engines).IMD:
What fixed-income instruments are best and least suited to this?Blance:
Fixed-income instruments with greater liquidity, such as treasuries and certain "more active" corporate bonds, can be well suited to algorithmic trading. This is due to the fact that it is easier for firms to minimise market impact with more liquid securities and to find a meaningful critical mass of historical data with which to develop algorithms.McGuigan
: At this point—and in our opinion for the foreseeable future—algorithmic trading will only be effective in the largest, most liquid issues.Lefferts
: A significant portion of US and European government bonds are traded electronically in limit order systems (i.e. interdealer systems), however, less liquid credit instruments and OTC derivatives are not. History has shown that limit order systems are best suited to liquid, plain vanilla instruments where ample pricing information is available such that participants are confident enough to put live, "executable" prices into a system.IMD:
Since fixed-income instruments are not traded on exchanges, how will client quoting and distribution architectures have to change in order to support this?Woodhams
: They may not be traded on exchanges but most brokers have screens for electronic trading of fixed-income instruments—as do many banks for their customers. As a result, client quote and distribution architectures are some way down the road to dealing with this.Nixon
: Existing electronic trading platforms are quasi-exchanges: venues to trade specified instruments, with market data feeds specifically designed for clients who have built their own front-end interfaces to effect trading. Highly robust, distribution architectures are required as a result of a participant's desire to have the most timely information available to them.Lefferts
: In the government bond markets, dealers have used real-time data from interdealer broker systems as an input to their trading engines, automatically updating their executable prices on these same venues to reflect the levels at which they are willing to trade. This application of technology is akin to algorithmic trading. For this type of trading activity to grow in other sectors of the fixed-income markets, the current distribution/request-for-quote systems would need to move away from permissioned multilateral execution to more broad, automated real-time execution/matching. In some liquid instruments, these platforms have already increased the ability to automatically execute orders in this way.IMD:
Will we see the emergence of order-driven fixed-income markets—or even bond "exchanges"—alongside request-for-quote systems? Where do you think liquidity will converge?McGuigan
: This could occur over time, but we do not envision bonds trading on order-driven exchanges in the near future. Currently, client-to-multi-dealer request for quote systems provide a convergence of efficiency, transparency, and liquidity in the fixed-income markets.Fortunato
: Client liquidity has already converged in the online markets. Around $200 billion is traded through TradeWeb each day. That's more than the NYSE and Nasdaq combined and many multiples of the nearest competitors.Blance:
With the low levels of liquidity in all but a small number of securities, such as US treasuries and supernationals, we believe there will be continuing use of request-for-quote systems. Electronic trading lends itself to the liquid issues, but as liquidity falls away, its use becomes limited.Lefferts
: Electronic interdealer systems, which have dominated government bond markets, are effectively order-driven markets. Over time these order-driven pools of liquidity may expand to other liquid instruments while request-for-quote systems will likely be the method of choice for the foreseeable future for less liquid bonds. Although NYSE ABS has not had significant traction to date, the SEC's recent approval for ABS to trade unlisted corporate bonds may allow it to garner more activity—especially in smaller retail orders where broker-dealers do not want to commit capital and are acting as agent.IMD:
Given that some issues don't trade every day, how will evaluated prices be used in the future?Blance:
Traditionally, the demand for evaluated pricing has been within an organization's net asset value calculation function. We believe that demand in this area will continue to grow as investment strategies become more wide-ranging and the need for more frequent updates increases. However, demand is also increasing in the front and middle offices, particularly in risk and compliance departments.McGuigan
: Since there is an increased demand from regulators to provide market context or trade observation data--at least theoretical end of day pricing—evaluated prices will continue to play a significant role for less liquid sectors of the markets.Nixon
: Evaluated prices will continue to be used as a reference price for mark-to-market purposes. However, more stringent regulatory and operational risk controls on pricing sources and models derived to evaluate the price and "secondary" pricing sources to validate evaluated price will continue to be desired.Lefferts
: The vast majority of fixed-income issues do not trade on any given day. However, by utilizing price information from those issues that do trade to calibrate models, determining fair value of an illiquid issue will also improve over time.IMD:
What changes will the industry see to regulation around fixed-income data as the market evolves—can we expect similar transparency and best execution directives as for equities?Blance:
Regulation is already driving greater transparency and the requirement for more frequent data updates in the fixed-income markets. Going forward, we anticipate that organisations will need to have access to greater depth and frequency of data to meet regulatory mandates.McGuigan
: We absolutely see the industry going in that direction. NASD Trace has been huge a step in that direction, and you can't put the genie back in the bottle…. [And on the retail side] as investors continue to increase their holdings in fixed income, there is likely to be greater and greater scrutiny on the fixed-income markets, and hence greater demand for pre- and post-trade comparative pricing and measurements of best execution.Lefferts
: Regulators recognize there are differences between the equity and fixed-income markets and that one size does not necessarily fit all. However, generally speaking the mandate regulators have to "protect" investors will encourage them to usher in more transparency. MiFID is an example of a broad approach to transparency that cuts across asset classes.IMD:
How important is it to offer data on other instruments, asset classes and geographic markets as trading becomes more cross-asset and international?Woodhams
: Very important. The successful vendors will be those who can offer data across a range of instrument types, markets and geographies, especially those that are related (e.g, CDS, bonds and equity) and can ally these offerings with sophisticated technology.Fortunato
: Clearly, this is an important capability. TradeWeb operates in 16 global marketplaces and is in a position to provide real-time pricing from many of these markets on its multi-dealer-to-client online marketplace. While niche players will always exist, liquidity will tend to concentrate around market leaders in any industry.McGuigan
: Investors, particularly hedge funds, make decisions based on relative value and correlations between asset classes, and the emergence of electronic trading has made these decisions less costly to implement, thus the demand for data correspondingly increases. The emergence of further capital structure analysis has driven the development of cross-asset class derivatives, which has also increased demand for data. So there is an inherent benefit to being able to provide data across asset classes and geographic markets.Lefferts
: The importance of being able to offer data across instruments, asset classes and geographic regions cannot be underestimated. As funds turn increasingly to cross-asset class strategies and banks further integrate their capital markets groups, providing depth and breadth of data across a range of instruments is critical.Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
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