What is Attribution Analysis?
Attribution analysis, also known as “return attribution” or “performance attribution,” is an evaluation tool used to explain and analyze a portfolio’s performance against a particular benchmark. It is used to identify sources of excess returns from a firm or fund manager’s active investment decisions.
Components of Attribution Analysis
Attribution analysis compares the return generated by a particular portfolio with that of a portfolio that has been benchmarked for evaluation. It involves comparing different components of the portfolio, which are the result of investment decisions made by the portfolio manager.
The most important factors for effective attribution analyses are portfolio allocation, asset/security selection, and the interaction of these effects – as outlined by the BHB (Brinson, Hoover, and Beebower) model – which is one of the commonly used performance attribution methods.
1. Allocation Effect
The allocation effect refers to the returns generated by allocating portfolio weights to specific segments, sectors, or industries. For example, a portfolio may consist of 20% allocated to assets in the technology sector, 50% to the utility sector, and 30% to the transport sector. The weights are then compared with a benchmark portfolio.
- If the portfolio weighs a sector higher than the benchmark, it is described as an overweight
- If the portfolio weighs a sector lower than the benchmark, it is described as an underweight
Ideally, the aim of a portfolio manager or investment decision-maker is to place a higher weight on sectors that perform well (i.e., overweight the sectors) and place a lower weight on sectors that are bad investments (i.e., underweight the sectors).
To quantify the effect of allocation decisions, the sector weights and returns in the portfolio are compared to those in the benchmark portfolio, and the arithmetic difference in returns is the effect of the portfolio manager’s decisions regarding asset allocation.
2. Selection Effect
The selection effect refers to the impact of the selection of specific stocks or securities within a segment on the portfolio’s overall return.
- A positive selection effect occurs when the portfolio return from a particular segment is greater than the benchmark return from the same segment.
- A negative selection effect occurs when the portfolio return from a particular segment is lower than the benchmark return from the same segment.
Since the analysis compares returns from equivalent segments in the portfolio against the benchmark, the excess (or lost) returns are attributed to selections within segments, which are made by the portfolio manager.
Caveat: It is important to note that stock selection is unrelated to allocation in that it is not affected by segment weights, but simply by decisions regarding specific securities that are included in the portfolio.
3. Interaction Effect
The interaction effect is the combination of the selection and allocation effect. If the portfolio allocation outweighs and outperforms the benchmark, the interaction effect is positive, and vice versa. The interaction effect is essentially the cumulative effect created by asset allocation, security selection, and other investment decisions made by the portfolio manager.
However, it is important to note that the interaction effect is not easily attributable due to the fact that it is a mathematical consequence of the allocation and selection effects rather than an actively made investment decision.
Active Management Effect
The active management effect refers to the sum of the allocation, selection, and interaction effects. It is essentially the difference between the portfolio returns and the benchmark returns, and the excess (or lack thereof) is attributed to the portfolio manager and their decisions.
What Makes a Benchmark Valid?
A valid benchmarked portfolio comes with the following characteristics:
- Reflective of the current investment landscape
Importance of Attribution Analysis
For portfolio managers – An effective tool to assess strategies
Attribution analysis can be used to separate the selection and allocation effects. The selection effect reflects the quality and ability to pick the right securities at the right time. It allows managers to reflect on the entire investment decision-making process and gives them opportunities to improve.
It is also used to evaluate the performance of employees at an asset management firm. If an analyst or employee recommended overweighting a particular sector or buying a particular stock, the returns can be attributed to their performance, and it can be used to reward them and motivate them further.
For investors – An effective tool to assess the performance of fund managers
For investors and clients of portfolio managers, attribution analysis is an important method to assess how a portfolio manager has performed and whether they have adhered to their investment strategies and styles.
For example, a portfolio manager may have underweighted the right sector but has picked high-return stocks, and it shows that they are better at selection than allocation. Similarly, a portfolio manager may agree to build a risk-averse portfolio. Examining the allocation and selection strategies can increase transparency and assure investors that the risk-averse strategy is being implemented.
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