Equity / Multi-Asset
It’s difficult to bring a new approach to equity attribution but we think that we have found a way!
Every performance system does equity attribution and there are only a limited number of models to choose from; it’s a relatively straight forward process.
Nevertheless, these equity attribution models, the few Brinson variants and the Karnosky-Singer model were created by asset allocators, not equity stock pickers.
If asset allocators can teach equity performance some tricks then maybe fixed income can too, albeit on a less profound level.
We try to add additional value in three ways, all extensions of things that we also do for fixed income:
Holdings and transactions, enhancing quality
Using holdings and transactions is much more necessary in fixed income.
Using the same approach in equities allows us to exactly replicate the accounting performance of the fund.
This gives a much higher degree of confidence that the numbers users see are correct.
It also gives feedback to the Operations team.
After calculating performance we have automatic checks of the numbers, looking for inconsistencies between holdings and transactions.
Where these occur it usually indicates booking problems which can be fed back for correction in the source system.
We have found that this quickly improves the quality of the source data as processes in the Operations team change.
Investing outside the benchmark
In fixed income it is common to buy assets that are not in the benchmark.
Sovereign funds may buy credit, single country funds may buy international bonds.
In equities this can also happen with investments into small cap and emerging equities, for multi-asset there may be many ex-benchmark investments.
Usually these would be captured as pure asset allocation decisions.
However, if the exposure is into an active fund it may be desirable to split the return into allocation and selection.
We include the ability to add alternative benchmarks that particular assets or sectors can be set against to allow that split.
Regrouping the results
Although a particular sector scheme may be useful to create the attribution, it will rarely tell the whole story of what has happened in the portfolio: size, country, currency and style factors can also have had an effect.
Multiple sectors schemes can be created, using descriptive data (countries, sectors) or numeric data (P/E, P/B) to then be used to regroup the attribution on the fly later.
In this way the user can quickly see how different effects have created the portfolio attribution.