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arXiv · 1501.02382

Robust Inference of Risks of Large Portfolios

Jianqing Fan·Fang Han·Han Liu·Byron Vickers
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Abstract

We propose a bootstrap-based robust high-confidence level upper bound (Robust H-CLUB) for assessing the risks of large portfolios. The proposed approach exploits rank-based and quantile-based estimators, and can be viewed as a robust extension of the H-CLUB method (Fan et al., 2015). Such an extension allows us to handle possibly misspecified models and heavy-tailed data. Under mixing conditions, we analyze the proposed approach and demonstrate its advantage over the H-CLUB. We further provide thorough numerical results to back up the developed theory. We also apply the proposed method to analyze a stock market dataset.

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BibTeXRIS

Jianqing Fan, Fang Han, Han Liu, Byron Vickers. 2015-01-10. Robust Inference of Risks of Large Portfolios. https://arxiv.org/abs/1501.02382

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