Style analysis, as originally proposed by Sharpe, is an asset class factor model aiming at obtaining information on the internal allocation of a financial portfolio and at comparing portfolios with similar investment strategies. The classical approach is based on a linear regression model, with constraints on the coefficients, estimated by using least squares. This solution clearly suffers from presence of outlying observations. Aim of the paper is to investigate the use of a robust estimator for style coefficients based on constrained quantile regression. The performance of the novel procedure is evaluated by means of a Monte Carlo study where different sets of outliers (both in the constituent returns and in the portfolio returns) have been considered.
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