Abstract

Protecting portfolio against extreme losses is a fundamentally difficult task since past experience provides a poor guidance for the future. This paper focuses on a robust approach to the portfolio insurance, which does not require historical calibration, and therefore avoids the hazards of data mining. We make a non-technical introduction to this methodology and compare it to traditional strategies such as Option Based Portfolio Insurance (OBPI) and Constant Proportion Portfolio Insurance (CPPI). We further propose its extension to the case when the investment horizon is not defined. As an illustration, we show how to apply this methodology to managing active risk of a smart beta equity portfolio.

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