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Abstract
This empirical performance attribution methodology provides an objective alternative to the existing practice of employing proprietary model–dependent systems with portfolio composition information. With only a time series of portfolio returns, this methodology detects multidimensional risk exposures, whether intended or unintended. The results allow for comparison of styles, risk exposures, and sources of performance across managers. Furthermore, as part of a well-designed internal investment process, this independent attribution methodology delivers a feedback mechanism for identifying systematic biases in analytical models that need correction.
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