An empirical investigation exploring the relationship between listed real estate and infrastructure companies

The purpose of this paper is to examine the performance attributes and investment characteristics of listed real estate companies vis-à-vis listed infrastructure companies. Utilising Bloomberg data, the paper investigates the inter and intra performance of the five largest global stock exchanges, namely New York, Tokyo, London, Shanghai and Hong Kong. A growing school of thought has emerged inferring that performance dynamics of real estate and infrastructure are inherently similar in composition but can be distinctly different in terms of outturn. Nonetheless, many fund managers have a propensity to ‘group’ real estate and infrastructure commodities within their alternative investment "basket" with little thought or consideration afforded to the idiosyncratic nature of the underlying assets driving performance. As such, one key question to ask is whether this "pooled rationale" is justified? Or should commodities linked to real assets (including real estate and infrastructure) be afforded special dispensation attributed to diversification potential and risk mitigation within the confines of a listed investment portfolio.Against the above contextual background, this paper attempts to shed empirical light on risk-return behaviour and diversification potential of infrastructure and real estate companies listed on the aforementioned international stock markets for the period of 2000-2016. To achieve this, we construct risk-adjusted return series (Sharpe Indices) for different major infrastructure sub-sectors (namely transport, utilities, renewable energy and telecommunication) and the real estate markets based on company-level data. A set of inter asset correlation matrices over different sub-periods are then developed to study the temporal dependence of returns between the sectors and across the five stock markets. Co-integration and Granger Causality models are devised to further explore the temporal dynamics of their interaction based on long-term cointegrating and lead-lag relationships.