Volatility, or the variability of the underlying asset, is one of the fundamental key components of property derivative pricing and in the application of real option models in development analysis. There has been relatively little work on the application of volatility to real estate property derivatives and the real options literature, examples being Lee & Ward (1999) and Patel & Sing (2000). Most research on volatility stems from investment performance (Nathakumaran & Newell (1995), Brown & Matysiak 2000, Booth & Matysiak 2001). Historic standard deviation is often used as a proxy for volatility and there is often a reliance on indices, which are subject to valuation smoothing effects. Transaction prices are considered more volatile than the traditional standard deviations of appraisal based indices. This could lead, arguably, to inefficiencies and mis-pricing, particularly if it is also accepted that changes evolve randomly over time and where future volatility and not an ex-post measure is the key (Sing 1998). If history does not repeat, or provides an unreliable measure, then estimating model based (implied) volatility is an alternative approach (Patel & Sing 2000). This paper examines the different approaches to calculating and capturing volatility in UK real estate and considers the importance in applying the measure to derivative pricing and real option models. It draws on a uniquely constructed IPD/Gerald Eve transactions database, containing over 20,000 properties over the period 1983-2005. We look at the magnitude of historic amplification associated with asset price movements by sector and geographic spread.