The importance of data management for fixed income attribution

By Ian Thompson, global director of portfolio analytics, StatPro

26 February 2019

The importance of performance attribution in fixed income investing cannot be overstated. Portfolio managers use it in both support and defense of their investment strategies.

It is integral for sales and marketing teams when it comes to asset gathering and client retention. Clients also rely heavily on it to determine how effectively their investment managers are enacting their given mandates.

That is why it’s crucial for fixed income managers to be working with robust data management and analytics tools. Accurate FIA calculations are impossible without good data. In the world of fixed income data, a minor change can result in millions of dollars in cost differential. It is of the utmost importance to work with good data and have good data management. Data availability is also a challenge: it’s difficult for firms to obtain the necessary risk metrics and information needed for FIA.

There are a couple of specific reasons why firms struggle with FIA data. One is that accessing the right data inputs still remains a difficulty for many firms. Legacy applications and outdated models that many managers still rely upon are simply unequipped to deal with the deluge of data today; the sheer volume and complexity of the inputs they need make them unwieldy, slow and limited in scope.

The complexity of market data has exploded over the last decade plus, derivatives are commonplace, and many fixed income benchmarks have more than 20,000 holdings (compared to 500 in the S&P 500 index). This means that manual calculations of specific data points are very difficult at best, and likely not possible in most cases. Indeed, in our conversations with hundreds of clients, dealing effectively with the data is often mentioned as a top challenge1.

Ultimately, this means that firms need much greater transparency on data when it comes to FIA. In addition to the attribution outputs this also includes the source data, including portfolio, index, pricing, yield curves and risk data at all levels and for all periods. Having a data management system in place that can help you parse through and makes sense of the massive amounts of FIA results as well as the data inputs today is critical.

Risk, performance and FIA

Fixed income attribution is the place where risk and performance come together.

There are many risk inputs when it comes to FIA; that’s why it’s critically important to use technology that can provide risk models for these inputs and that can provide transparency on risk, performance and attribution within the same platform.

When deciding whether to include a given asset class in a portfolio to help meet a client objective such as generating income, risk is perhaps the first aspect a manager will examine, along with potential return2. Having a highly flexible user interface to drill down into FIA results together with the underlying risk data allows managers to easily identify the proper risk factors that determine performance. Such a system also enables clients to assess the skills of management to provide added value relative to a benchmark.

Accurate fixed income return contribution analysis provides a clear picture of which of the portfolio’s investments contributed to overall profit or loss in a given reporting period. Attribution provides a deep breakdown of how the performance was achieved.

Difficulties aligning different types of data

Firms struggle with aligning all the different types of source data needed for properly calculating FIA.

That’s why it is critical to have a system in place that will provide the flexibility to allow for many different data sources. Having accurate, clean and controlled data makes it possible for firms to show clients the correlation between the risk profile and performance. It’s also crucial to have consistency in the data used by the front and middle office.

For example, the analytics, yield curves and prices used in the calculation of the returns and effects must be aligned with one another and calculated using similar assumptions. It is critical that accurate and aligned data is being used, as this is one of the biggest factors in calculating accurate FIA outputs.

To do this, firms should work with cloud-based technology that utilizes APIs to extract and align data from different silos into a central repository such as a data warehouse.

Deluge of data volume

The above point is correlated with the fact that firms are dealing with massive amounts of data, and in many cases unable to make sense of it all.

It’s become extremely difficult for managers to analyze and glean insight out of the massive amount of data that exists in the marketplace. More so than other sectors, the fixed income world is full of different and complex types of instruments, each of which comes with an extraordinarily complex mathematical web of macro and micro factors that can impact yield and return.

Data challenges in FIA tend to be greater because of this massive volume of information. Applying expertise in data integration from across all the different asset types fixed income managers invest in is critical, especially in unconstrained and/or global mandates.

Fixed income managers are normally comfortable dealing with complex mathematical formulas, but the deluge of data being created today, and on a daily basis, means that still using inappropriate and unscalable legacy solutions is only adding to the complexity. That’s why working with a customizable, cloud-based data analytics architecture – as noted above – is a need-to-have as opposed to a nice-to-have in today’s environment.

Utilizing vendor-provided data

It is a requirement for firms to work with accurate, clean and controlled data.

There are many data inputs needed when it comes to FIA, such as duration, spread, yield curves, and many other management outputs. However, it can often be difficult for firms to get the underlying data necessary for making fixed income attribution calculations- there can be difficulties in pricing different asset types, for example. In the end, having inconsistent data or data sources can lead to a situation where there is a misalignment of prices, risk numbers and yields.

A vendor that can provide data from different indices, either entirely or in conjunction with adding in the firm’s own risk numbers along with the vendor data, gives the firm options and can greatly reduce the potential pitfalls associated with poor data sourcing. A vendor providing the full set of index data and analytics, which then can be augmented by the firm’s own risk numbers, is an extremely valuable approach to FIA.

Implementation challenges

Fixed income firms face several challenges when it comes to implementation.

The first is that there is no global industry standard for methodologies. The treatment of instruments between the front and middle office can vary greatly, and it can be difficult for firms to bridge the gap between risk and performance.

Secondly, the combination of data sensitivity and huge data volume leads to implementation challenges. Fixed income projects are notorious for being time-intensive and laborious, particularly where the fund manager has to source the data themselves.

Robust technology is a must

Simply put, it is a necessity to work with a robust, modern, ideally cloud-based technology solution to make sense of the vast amounts of data firms deal with today when it comes to calculating FIA.

Without it, it’s almost impossible to accurately answer questions such as:

Were our assumptions correct?

Have the drivers of our returns been what we thought they would be?

Do we have the right risk and pricing assumptions and models?

Fixed income managers must be able to accurately answer these questions. As the challenges in the fixed income realm continue to grow, managers need to be assured that the numbers they are using to make investment decisions are accurate. Working with a highly flexible, cloud-based interface allows for easy identification of risk factors that determine bond level performance. Such a system also enables clients to assess the skills of management to provide added value relative to a benchmark.

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