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Testing the Robust H-CLUB with Synthetic Data

version (301 KB) by JohannesBuck
We test the quality of the Robust H-CLUB by generating synthetic data and calculate estimates


Updated 27 Oct 2017

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The H-CLUB was originally proposed by Fan et al. in the paper "Robust Inference of Risks of Large Portfolios"
We use two different scenarios - the normal condition and the stress scenario.
In the normal condition we just test the quality of results when the data is according to the necessary conditions. In the stress scenario we introduce strong serial dependence, outliers etc. such that the conditions for the algorithm to work are not fulfilled anymore.
We then test how well it behaves under such strong conditions.

Cite As

JohannesBuck (2021). Testing the Robust H-CLUB with Synthetic Data (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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