Asset Allocation and Factor Investing: An Integrated Approach

We presented a framework for integrating asset allocation with factor investing, which has the dual benefits of allocating to observable and directly investable asset classes in a manner that tracks a preferred factor profile. We showed how to augment the classic Markowitz objective function to include a term for aversion to deviation from a factor profile. Our approach differs from the Chow [1995] approach to integrating absolute and relative performance because Chow required only a single covariance matrix. Our approach assumes investment in assets with sensitivities to noninvestable factors. We must, therefore, estimate a covariance matrix of assets as well as a covariance matrix that captures the sensitivities of the asset classes to the factors.7 We illustrated this integrated approach with a case study that showed how the composition and performance of the optimal portfolios change as we change the composition of the factor profile and as we vary our degree of aversion to deviations from the factor profiles. We produced in-sample results showing that factorsensitive portfolios performed better during regimes in which the factors behave in accordance with our expectations, compared both to their performance during the full sample and relative to the unconditioned portfolio during the factor-conditioned subsample. Whether this performance would prevail out of sample depends on the extent to which the historical covariation of the factors and asset classes persists in the future. Finally, we wish to emphasize that this new methodology for integrating asset allocation and factor investing is very general. Although we illustrated it with a simple example based on several broad asset classes and two macroeconomic factors, it can be applied in a variety of settings, such as the construction of portfolios that are sensitive to security attributes such as value, size, and momentum; portfolios that are sensitive to unavailable asset classes; or portfolios that are sensitive to volatility regimes. © 2017 Institutional Investor LLC. All Rights Reserved.