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Statistical Risk Models

Zura Kakushadze and Willie Yu

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Abstract: We give complete algorithms and source code for constructing statistical risk models, including methods for fixing the number of risk factors. One such method is based on eRank (effective rank) and yields results similar to (and further validates) the method set forth in an earlier paper by one of us. We also give a complete algorithm and source code for computing eigenvectors and eigenvalues of a sample covariance matrix which requires i) no costly iterations and ii) the number of operations linear in the number of returns. The presentation is intended to be pedagogical and oriented toward practical applications.

New Economics Papers: this item is included in nep-ecm and nep-rmg
Date: 2016-02, Revised 2017-01
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Published in The Journal of Investment Strategies 6(2) (2017) 1-40

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