This webinar will discuss why robustness is essential for investors using smart beta strategies and will describe the sources of deficiencies. It will also explain the need for robustness checks in performance analysis of such strategies and the various methods by which Scientific Beta improves robustness. Finally, it will assess the robustness of a set of competitor and Scientific Beta indices both from an index design point of view and through the lens of Scientific Beta's robustness measurement protocol.
Overview
Assessing the robustness of smart beta strategies should play a central role for investors in their due diligence process. Such strategies often experience an out-of-sample degradation of performance compared to that presented in the historical in-sample period. Investors should always check that interesting in-sample results are complemented by a consistent construction framework and transparency on the methodology and implementation from the side of the strategy provider.
They should also be able to measure the robustness directly using appropriate tools and metrics in order to cross-check whether the strategy's behaviour is consistent with its stated objective. This way, they can be in a better place to select those strategies that will perform out-of-sample in a manner consistent with their historical (simulated) profile.
However, assessing the robustness of a strategy based on historical simulations can become challenging due to sample dependence.
This webinar will discuss why robustness is essential for investors using smart beta strategies and will describe the sources of deficiencies. It will also explain the need for robustness checks in performance analysis of such strategies and the various methods by which Scientific Beta improves robustness. Finally, it will assess the robustness of a set of competitor and Scientific Beta indices both from an index design point of view and through the lens of Scientific Beta's robustness measurement protocol.
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