Not long ago, the notion of an investor requesting multi factor attribution on their fixed income portfolios was unheard of. To a near lay-person, the concept of explaining the movements of a portfolio sensitive to interest rates was crazy. Multi factor attribution was for the front office, and its value was hampered by the limitations of the solutions at that time – unofficial results driven by lackluster data quality, without the ability to control data sources (outside of what the vendor chose for you).
At the same time, vendors and solutions providers were working hard to convince the industry that one attribution methodology was better than the other. Lehman (then Barclays and finally Bloomberg) had ”Hybrid Attribution,” other vendors provided “Key Rate Duration”, while still others tried to convince the industry they what they needed was ”Custom Attribution.” I’ll let you in on a secret: 90% of the time the same story is told in the same way. The brand name of a methodology is actually a marketing exercise.
In the interest of full disclosure, BISAM has long been a provider to the needs of the Fixed Income investment management community. We have iterated through several fixed income attribution approaches – those that tried to solve for scenarios that did not provide analytics, and others that were specific to the needs of a client. Eventually we settled on three main methodologies designed to pragmatically explain the returns of any instrument sensitive to interest rates (and even those that don’t – but more on that later). This decomposition explains the returns across five main categories: Carry, Currency, Duration, Spread, and Idiosyncratic (essentially non-market forces).
Early in the history of vended solutions for fixed income attribution, the audience was solely internal. A vendor was expected to provide a very detailed analysis of a portfolio, splitting the five categories I mentioned above into dozens. This is where each vendor started to provide what was viewed as a custom model, but in fact was just a series of unique names for the same market phenomenon. In theory, the more effects a vendor had the better the perception. But a funny thing happened – no one client used every result (or even close to it).
A few years ago, we noticed a shift in the demands of our clients. Internal consumption was still a need, but aligning the results to those of the investors became vitally important. Changes in the market, a reduction in interest rates, the rising complexity of benchmarks – all put even more of a spotlight on alpha. Lower alpha, coupled with increased demand from the investor, meant the same result from the same solution was vital. This, along with an acknowledgement that very high quality data was a necessity, drove the biggest shift we’ve seen since BISAM started in this field. As fixed income attribution moved from a front office to an enterprise view, the middle office controls long present in performance applications now became mandatory.
Since then, we have coalesced around a core set of requirements listed below (whether admitted or not):
So if we can agree at this point that the dust has indeed settled on a fairly standard set of methodologies, it’s important to remember that there is still more to fixed income attribution. The industry must continue to innovate in order to meet investor demands, and taking a focus on consistent and high quality data will be key. We need a spotlight on the operational controls long championed by the middle office…but that’s for another blog post!
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