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Abstract
Evaluating portfolio performance through comparison with benchmarks is a classic technique in modern finance. However, biases can impact expectations on excess return and tracking error, particularly in portfolios constructed using mean-variance optimization.
In this report, Artemiza Woodgate, a Senior Research Analyst at Russell Investments , and Andrew Sieg el, the Grant I. Butterbaugh Professor at the University of Washington’s Foster School of Business , tell us how to combat statistical errors in performance analysis and describe their approach to reducing the influence of noisy estimates.
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