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How can you use performance attribution analysis to identify portfolio return sources?

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Performance attribution analysis is a method of decomposing the returns of a portfolio into different factors that explain its performance. It can help you understand how your portfolio is performing relative to a benchmark, what are the main sources of return and risk, and how you can improve your portfolio strategy. In this article, you will learn how to use performance attribution analysis to identify portfolio return sources.

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1 Basic concepts

Performance attribution analysis involves comparing the portfolio return with the benchmark return and breaking down the difference into various components. The most common components are allocation, selection, and interaction effects. Allocation effect measures how much return is due to the weighting of different asset classes or sectors in the portfolio relative to the benchmark. Selection effect measures how much return is due to the choice of specific securities within each asset class or sector. Interaction effect measures how much return is due to the combined effect of allocation and selection decisions.

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Performance attribution analysis breaks down a portfolio's return into sources like allocation (weighting of asset classes) and selection (performance of chosen securities) to understand how a manager achieved those returns.

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Sastaviyana Y.
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Performance attribution dissects portfolio returns: assess asset allocation's impact, pinpoint contributions from security selection, and evaluate market timing effects. Analyze sector exposure, currency impacts, and risk factors. Benchmark comparisons reveal outperformance factors. Attribute returns by time period and use quantitative models for predefined factors. Examine external events like economic changes. This aids in refining strategies, aligning portfolios with goals, and making informed decisions.

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Rajesh N

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Performance attribution analysis is utilized by portfolio managers to dissect portfolio returns, identifying the contributions from asset allocation, security selection, market timing, currency effects, and sector allocation.

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Sourabh Gour

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Performance attribution analysis is a key tool in dissecting a portfolio's returns by attributing them to specific factors like asset allocation, security selection, and market timing. By comparing a portfolio's performance against a benchmark, it pinpoints which investment decisions drove returns. Asset allocation reveals how the weightings in various asset classes contributed, while security selection identifies the effect of individual investment choices. Market timing indicates how well strategic moves in response to market conditions influenced returns. This analysis aids in evaluating investment strategies' effectiveness and refining future decision-making.

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2 Single-factor model

A simple way to apply performance attribution analysis is to use a single-factor model, such as the capital asset pricing model (CAPM). The CAPM assumes that the only factor that affects portfolio returns is the market risk premium, which is the excess return of the market over the risk-free rate. The CAPM can be used to calculate the expected return of the portfolio and the benchmark based on their beta coefficients, which measure their sensitivity to the market risk premium. The difference between the actual and expected returns of the portfolio and the benchmark can then be attributed to the selection effect.

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3 Multi-factor model

A more realistic way to apply performance attribution analysis is to use a multi-factor model, such as the Fama-French three-factor model or the Carhart four-factor model. These models assume that there are multiple factors that affect portfolio returns, such as size, value, momentum, and profitability. These factors can be used to calculate the expected return of the portfolio and the benchmark based on their factor loadings, which measure their exposure to each factor. The difference between the actual and expected returns of the portfolio and the benchmark can then be attributed to the allocation and selection effects within each factor.

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Nilay Parikh

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A multi-factor model is essential for precisely identifying portfolio return sources through performance attribution. I believe robust quantitative models that incorporate multiple return factors are vital to avoid misleading attestations. Though multi-factor analyses require more calculations, they provide a fuller, more accurate picture of what is truly influencing portfolio performance. For example, by analyzing momentum factor exposure, I can see if excess gains stem from riding hot streaks in certain securities. Rather than rely on assumptions, factor models enable data-driven insights into the specific dynamics actually moving the needle. By indicating each explicit return source down to the factor level.

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4 Brinson model

Another popular way to apply performance attribution analysis is to use the Brinson model, which is based on the sector or asset class level. The Brinson model assumes that the portfolio and the benchmark have the same set of sectors or asset classes, and that each sector or asset class has a representative index. The Brinson model can be used to calculate the contribution of each sector or asset class to the portfolio and the benchmark returns based on their weights and returns. The difference between the portfolio and the benchmark returns can then be attributed to the allocation, selection, and interaction effects across sectors or asset classes.

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5 Advantages and limitations

Performance attribution analysis can provide valuable insights into the sources of portfolio returns and help you evaluate your portfolio strategy. It can help you identify your strengths and weaknesses, compare your performance with your peers, and adjust your portfolio allocation and selection accordingly. However, performance attribution analysis also has some limitations, such as data availability and quality, model specification and assumptions, and interpretation and communication challenges. Therefore, you should use performance attribution analysis with caution and supplement it with other tools and methods.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you use performance attribution analysis to identify portfolio return sources?

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3

4

5

6

1 Basic concepts

2 Single-factor model

3 Multi-factor model

4 Brinson model

5 Advantages and limitations

6 Here’s what else to consider

Technical Analysis

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How can you use performance attribution analysis to identify portfolio return sources?

1

2

3

4

5

6

1 Basic concepts

2 Single-factor model

3 Multi-factor model

4 Brinson model

5 Advantages and limitations

6 Here’s what else to consider

Technical Analysis

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