Abstract
In this paper, we propose principle factor analysis method to reduce the dimensions of a high dimensional random vector in calculating portfolio’s Value at Risk. The theoretical foundation, algorithm and numerical example of the method are given. This method outperforms the principle component analysis method. Especially, the advantages of the method are marked, while the factors F’s multicollinearity is serious.
This work is supported by National Natural Key Product Foundations of China 10231060.
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Xue, H., Xu, C., Hu, C. (2005). An Algorithm for Portfolio’s Value at Risk Based on Principal Factor Analysis. In: Megiddo, N., Xu, Y., Zhu, B. (eds) Algorithmic Applications in Management. AAIM 2005. Lecture Notes in Computer Science, vol 3521. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11496199_41
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DOI: https://doi.org/10.1007/11496199_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26224-4
Online ISBN: 978-3-540-32440-9
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