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Evaluating Hierarchical Equal Risk Contribution Portfolios in the Chinese Stock Market
Wenlan School of Business, Zhongnan University of Economics and Law, Wuhan, China
Research Center of Finance, Shanghai Business School, Shanghai, China
- 1 Wenlan School of Business, Zhongnan University of Economics and Law, Wuhan, China
- 2 Research Center of Finance, Shanghai Business School, Shanghai, China
Journal of Mathematical Finance·Volume 12 (2021)·Pages 179–195·Published 28 December 2021·DOI10.4236/jmf.2022.121011
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Abstract
This paper investigates the usefulness of the Hierarchical Equal Risk Contribution algorithm to exploit correlation structure in China’s equity market over 2001-2020. By running a horse race of different combinations of metrics and linkages, we demonstrate that the winner strategy always beats traditional portfolio construction techniques. Better-performing risk-based hierarchy strategies vary with stock-sorting methods by size, mean return, volatility, and Sharpe ratio. However, our treatment results in extremely imbalanced asset allocation, implying that we capture information other than the standard Chinese industrial classification.
KeywordsHierarchical Equal Risk ContributionMachine LearningHierarchical Risk ParityAsset AllocationCritical Line AlgorithmInverse-Variance Portfolio
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