The Covariance Matrix between Real Assets

Abstract

For real assets such as private equity, infrastructure, and real estate, computing the time-variance of trade prices is of limited interest because there is not much trading in these assets. The author argues that it is more meaningful to use variance measures over the cross section as indicators for investment risk. In a large database of funds invested in sparsely traded assets, the cross-sectional variance—or dispersion—of fund performances is measured within and between the asset classes in which they are invested. The covariance matrix that is estimated in this way has features similar to the matrix between regularly traded assets that is computed over time. The author argues that the matrix provides a practical framework for analyzing risk and constructing portfolios invested in real assets with the same methods that are habitually employed on liquid assets.