When is Cash Policy Effect appropriate?

For risk decomposition, FactSet and Barra have worked in close cooperation to provide Barra analytical calculations with Barra terminology as an option in Portfolio Analysis. One of the most common questions we get from clients is why there are data and calculation differences between Barra and FactSet when it comes to risk-based performance attribution. One of the most obvious differences is that Barra includes an additional component of the analysis called “Cash Policy Effect” that is absent from risk-based performance attribution in FactSet. This can be a source of confusion, and therefore warrants greater understanding.

What is Cash Policy Effect?
The impact of a cash position is separated out of the analysis and calculated first. The effect is analogous conceptually to cash drag and mathematically to the effect you would expect to see in a Brinson attribution that separated out cash at the top level grouping. After the Cash Policy Effect is computed, the benchmark weights are ratcheted down proportionately by the cash weight so there is no active underweight in equity.

Whether to include or exclude Cash Policy Effect in risk-based performance attribution comes down to a very specific question: If your portfolio has 10% in cash, and a given security has a 4.75% portfolio weight while the benchmark weight is 5% do you consider yourself to be overweight or underweight the security by 25 basis points in your analysis of relative performance?

Of course, the answer depends on the investment process.

Imagine a portfolio constructed quantitatively using an optimizer to achieve the optimal positions and weights. Then, as a purely secondary step, the cash/equity split is determined and that decision may well be more about practical business considerations. Clearly, in this case, the Cash Policy Effect makes perfect sense because you want to back out that cash allocation decision first and then assess the portfolio ex-post as it was truly constructed in the beginning. The intention was absolutely to overweight our selected security by 25 basis points.

But, from our experience, we don’t believe that this is how a typical FactSet client constructs portfolios. FactSet won't assume why the portfolio holds cash. FactSet won't introduce hierarchy into a risk-based performance attribution framework (when the absence of hierarchy is the primary benefit of risk-based performance attribution vs. Brinson/Exposure-based attribution) to account for cash. FactSet won’t adjust benchmark weights inside performance attribution calculations (and thereby re-define active security weights) due to the portfolio's cash position. We believe that most likely you intended to have a 25 basis point underweight.

As I said before, the answer depends on your investment process. FactSet remains committed to offering choice, so inevitably Cash Policy Effect will be another Portfolio Analysis option. We just aren’t willing to make this a development priority until it makes sense for our clients.

So, given this explanation, the logical follow-up question is how significant is the difference? Should I really care? First, the more cash in the portfolio, the larger the Cash Policy Effect. Second, more extreme and disparate security returns lead to larger differences. I created a relatively simple example to help quantify the differences (click to enlarge).


Security J is the example from our base question. Reviewing the results, the most important differences are the directional changes in the Active Weight and Total Effect. If this were your portfolio, would you think of Security J as a positive contributor or a detractor from your relative performance? Active weight is crucial because as you attribute performance to the systematic risk factors, you rely on the active exposure to the factor and that critically depends on the active weight in each security.

In conclusion, the decision to use Cash Policy Effect should depend on your investment process. Its misuse can easily generate highly unintuitive results that reduce confidence in the analysis.

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