Return-Based Style Analysis Versus Sector Performance Attribution
Summary
Return-based style analysis estimates a manager’s effective exposure to selected asset classes by fitting the manager’s returns to those assets. The response explains that the method commonly uses multivariate linear regression over rolling windows, with Kalman filters as another possible approach. It therefore has a close connection to regression, even when presented as a constrained variance-minimization problem.
For identifying which equity sector contributed most to a broad market index’s return and risk, the response advises against using style analysis as the primary tool. Estimating sector weights from index returns can be difficult when there are many explanatory series, and the resulting weights are not themselves a direct attribution of performance. Given sector data, performance attribution and risk attribution are more direct ways to measure each sector’s contribution. The response offers this as practical guidance rather than a worked comparison; it does not specify attribution formulas or test results.
Key ideas
- Return-based style analysis commonly estimates exposures through rolling multivariate regression.
- Kalman filters can be used as an alternative for estimating changing exposures.
- Style analysis may struggle to resolve exposures when many variables are included.
- Sector return and risk contributions are better addressed with performance and risk attribution.
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# Questions related to Sharpe's return-based style analysis # Questions related to Sharpe's return-based style analysis I have been reading about Sharpe's return-based style analysis, which tries to determine the manager's exposure/effective asset mix to changes in the values of the asset classes. It does so by using quadratic optimization (minimizing the variance of the manager return minus coefficient times returns of chosen asset classes). My question is: 1) Does this analysis give the same/different interpretation as/from the multivariate linear regression model? 2) I want to answer this question: which sector had the biggest return and risk contribution to the market from t = t1 to t= t2? What percentage of total return and risk is coming from the TMT sector from t = t1 to t = t2? I have daily returns of MSCI ACWI (the world equity market index) and MSCI ACWI for all the sectors (tech, financials, health care, etc). Would Sharpe's return-based style analysis be a good method to answer those questions? ## Answer by rhaskett (score 2, accepted) https://quant.stackexchange.com/a/40293 1) Return-based style analysis (RBSA) generally uses multivariate linear regression over rolling windows to get results. Sometimes Kalman Filters are employed instead. 2) Not the best, honestly. returns-based style analysis tries to guess the dependence of your fund (ACWI) and it struggles with resolution for large numbers of variables. The number of sectors is not too large but large enough to cause problems. You can likely can get the weights for the ACWI sectors over time. So you should be able to just do performance attribution and risk attribution which is much easier.
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