Performance Attribution Models

brinson fachler attribution model overview the brinson fachler attribution model is a widely used performance attribution methodology that decomposes the excess return of a portfolio relative to a benchmark into three main effects allocation effect measures the impact of allocating assets differently than the benchmark selection effect measures the impact of selecting securities that perform differently than the benchmark within each category interaction effect measures the combined impact of allocation and selection decisions the brinson fachler model, developed by gary p brinson and nimrod fachler in 1985, is an extension of the original brinson hood beebower model it is considered one of the most comprehensive and widely accepted frameworks for performance attribution in the investment industry the model provides a clear separation between allocation decisions (asset allocation) and selection decisions (security selection), making it particularly useful for evaluating the performance of portfolio managers how it works the brinson fachler model calculates these effects using the following formulas allocation effect (portfolio weight benchmark weight) × (benchmark return total benchmark return) selection effect benchmark weight × (portfolio return benchmark return) interaction effect (portfolio weight benchmark weight) × (portfolio return benchmark return) total effect allocation effect + selection effect + interaction effect the model also calculates risk attribution using covariance matrices and marginal risk contributions to understand the risk contribution of each component when to use use the brinson fachler attribution model when you want to understand the sources of excess return in a traditional asset allocation framework you need to separate the impact of asset allocation decisions from security selection decisions you want to analyze performance at multiple levels (total portfolio, asset class, sector, etc ) hierarchical attribution model overview the hierarchical attribution model is an alternative performance attribution methodology based on the "balanced portfolio attribution" approach by stephen campisi in this paper it decomposes the excess return into allocation effect measures the impact of allocating assets differently than the benchmark selection (or active) effect measures the impact of active management decisions within each category stephen campisi's "balanced portfolio attribution" approach, published in the journal of performance measurement, addresses some limitations of traditional attribution models by providing a more balanced framework that avoids the asymmetry issues present in other models the hierarchical aspect of this model allows for a multi level analysis of performance, starting from broad asset classes and drilling down to more specific categories, making it particularly useful for complex portfolio structures how it works the hierarchical model calculates these effects using the following formulas allocation effect (portfolio weight benchmark weight) × (benchmark return total benchmark return) selection effect portfolio weight × (portfolio return benchmark return) total effect allocation effect + selection effect important contrary to the classical brinson fachler model, the hierarchical model rescales the weights within a given asset class see the original publication for a detailed of the advantages of doing so when to use use the hierarchical attribution model when you want a simpler decomposition of excess return (two components instead of three) you're dealing with complex portfolios that include funds and indexes you need to account for unexplained components in the attribution analysis you prefer the balanced attribution approach described by stephen campisi