This study investigates the dependence structure of returns of different types of equity REIT. Copulas, which provide a tractable way of modelling non-linear dependency among random variables, are employed under financial time series framework. The model consists of two parts: the marginal part, which represents the dynamic behaviour of each individual margin, and the copula part, which represents the joint dependence among those individual components. Specifically, the REIT sub-sector indices are fitted using ARMA-EGARCH models and then analysed using time-varying conditional copulas to ascertain if tail dependence exists and to examine the dynamics of the tail dependency. The study tests a number of well-known copulas, for example, Gaussian, Studentís t, Gumbel, Clayton, and Symmetrised Joe-Clayton, to identify the most suitable one for equity REIT indices. For each copula, the time path of the degree of tail dependence is implied to see how the dependence structure changed over time. The sample data covers the US REITs from January 1993 to February 2009. However, the focus is placed on the recent period in which many extreme events occurred.