# Data-Driven Distributionally Robust Risk Parity Portfolio Optimization

@article{Costa2020DataDrivenDR, title={Data-Driven Distributionally Robust Risk Parity Portfolio Optimization}, author={Giorgio Costa and Roy H. Kwon}, journal={ERN: Statistical Decision Theory; Operations Research (Topic)}, year={2020} }

We propose a distributionally robust formulation of the traditional risk parity portfolio optimization problem. Distributional robustness is introduced by targeting the discrete probabilities attached to each observation used during parameter estimation. Instead of assuming that all observations are equally likely, we consider an ambiguity set that provides us with the flexibility to find the most adversarial probability distribution based on the investor’s confidence level. This allows us to…

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