Last modified: 2018-05-12
Abstract
Due to technological advancement, roboadvisory platforms have allowed significant cost reduction in asset management. However, this improved allocation may come at the price of a biased risk estimation. To verify this, we empirically investigate allocation models employed by roboadvisory platforms. Our findings show that the platforms do not accurately assess risks and, therefore, the corresponding allocation models should be improved, incorporating further information, through clustering and network analysis.
References
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