25 years: Investment management
In the previous video, Ali explained why performance attribution is important for an asset management firm. He also outlined a few examples and how we interpret them. In this video, he goes deeper into some of the theories behind these performance attribution reports and how they are constructed.
In the previous video, Ali explained why performance attribution is important for an asset management firm. He also outlined a few examples and how we interpret them. In this video, he goes deeper into some of the theories behind these performance attribution reports and how they are constructed.
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11 mins 21 secs
There are several different models that can be used for performance attribution, one of which is the Brinson, Hood, Beebower model, more commonly known as just the Brinson model. It is specifically suited for use when the portfolio is measured against a specific benchmark and it focuses on stock selection and asset allocation.
Key learning objectives:
Outline how the Brinson model was developed and what it can be used for
Understand the maths behind the model
Outline the pros and cons of the model
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The model was derived from a series of research papers from the 1980s, the most well-known of which is ‘Determinants of Portfolio Performance’ published by Brinson, Hood, and Beebower in 1986.
The model is now the most widely used model for performance attribution among equity professionals and is specifically suited for use when the portfolio is measured against a benchmark (an index or a combination of market indices).
To perform the model the portfolio and benchmark need partitioning into groups (if the PMs choice). The first decision assessed is how the PM is allocating capital across the groups versus the benchmark. The difference between the weights in the portfolios and those in the benchmark is the active allocation decision. The second decision assessed is how the PM is selecting for each group versus the neutral selection provided by the benchmark. The performance coming from holding different stocks compared to those in the benchmark is what we call the stock selection effect. The objective of the model is to then estimate the value added of each of these two strategies.
However, this is just the first stage, to complete the analysis, we need to consider two specific cases:
We have now measured the performance of the two decisions, however when added, the two components don’t equal total excess return, there is an interaction effect between the selection and allocation decisions. It is the benefit or penalty coming from having the two decisions both in the same direction or having them in opposite directions. E.g. If both of the decisions result in a positive outcome, there is an additional benefit for allocating more stocks that are doing better. Interaction is expressed as:
Pros:
Cons:
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