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Mar 01, 2012 · Abstract. Principle Component Analysis (PCA) is one of the common techniques used in Risk modeling, i.e. statistical factor models. When using PCA to estimate the covariance matrix, and applying it to portfolio optimization, we formally analyze its performance, and find positive results in terms of portfolio efficiency (Information Ratio) and transaction cost reduction.

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