This paper constructs a portfolio protection model to deal with uncertain adverse returns. Our model considers an adjustable discrete uncertainty set to control the conservatism of the robust portfolio. Without prior assumptions on the data generating process, we develop an a priori probabilistic guarantee of the robust portfolio. Unlike previous measures that depend solely on the uncertainty model, our measure also takes into account asset allocation and investment horizon. We provide an application of international portfolio protection covering the financial crisis period. Computational experiments and ex-post analysis provide evidence for the effectiveness of our model.JEL Codes: C14; D81; G11; G15.Keywords: Portfolio protection; Robust optimization; Multivariate tail dependence; Nonparametric predictive inference.
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