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The contribution of this article is to present an investment process that allows the asset manager to limit risk exposure to macro-factors – including expectations on correlation dynamics – whilst allowing for selective exposure to risk factors using factor-portfolios that emulate the risk and return profile of market micro-factors.
The design of the process provides the ability to explicitely limit risk exposures to macro-factors based on forward-looking narratives allowing the investor to reflect – in the resulting active allocation – expectations of financial or systemic crises by, say, restricting the overall exposure to the credit macro-factor that includes the risk factor exposures (micro-level) arising, for example, from corporate and supranational spreads whilst simultaneously increasing the exposure to flight-to-safety macro-factors under a local or global crisis. This process is better suited to drawdown-averse investors that are willing to forgo some upside in order to effectively limit significant portfolio losses from crises, systemic or otherwise.
In order to improve the optimization over the rugged solution space resulting from superimposing macro-factors' risk envelopes on the factor-portfolios' tracking error allocation, a genetic-algorithm-based optimization is proposed.
