Statistical risk models

Zura Kakushadze and Willie Yu

Journal of Investment Strategies

Abstract: In this paper, 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 effective rank (eRank) and yields results similar to (and further validates) the prior method of Kakushadze. We also give a complete algorithm and source code for computing eigenvectors and eigenvalues of a sample covariance matrix, (i) which requires no costly iterations and (ii) for which the number of operations is linearly proportional to the number of returns. This paper is intended to be pedagogical and oriented toward practical applications.

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Persistent link: https://EconPapers.repec.org/RePEc:rsk:journ6:3912131

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