Real Estate Risk Management with Copulas

Real estate risk management tools are traditionally based on mean-variance analysis. The non-normal behaviour of financial asset returns including real estate securities is a violation of one of the fundamental assumptions of mean-variance analysis. In this paper, the pitfalls of using the correlation coefficient as a measure of dependency are discussed first. The use of copulas as an alternative to modelling the dependence structure and more generally as a risk-management tool is then proposed. Copula-based value-at-risk computations are also carried out. The results confirm that the linear correlation measure is unable to capture the dependence between the US and the UK publicly listed real estate securities. The limitations of the joint multivariate normal distribution are also shown.