This paper examines the distributional characteristics of REITs using the daily NAREIT indices for the period 1997-2004. While previous studies have examined the distributional properties of REITs, they have largely used lower frequency monthly data. This paper has two primary aims. Firstly, it extends the existing literature on REITs by utilising the approaches proposed by Peiro (1999, 2002) and illustrating that the conventional skewness statistic, which is normally used to test for normality in return distributions, may provide erroneous inferences regarding the distribution as it is based on the normal distribution. We test for non-normality using a variety of alternative tests that make minimal assumptions about the shape of the underlying distribution. Secondly, building on the reported findings we analyse the implications for risk measurement. We estimate value-at-risk measures on a daily basis for REITs. While VaR has over the last ten years become a main standard risk measure it does suffer from a number of problems, especially concerning the assumptions made regarding normality in the basic estimation of the measure (Hull & White, 1998). We therefore use of Extreme Value Theory in examining the tail behaviour of REITs and integrate this with the estimation of daily value-at-risk figures.