||Real estate markets are often subject to price shocks whose amplitude may be very high. According to R. Shiller (1998), these shocks are as difficult to explain as those that affect equity or debt markets. The investors and all financial institutions are in need of hedging products or derivatives that are based on the dynamics of the underlying asset and especially on its volatility. The standard deviation, directly computed from repeat sales, overestimates this WRS index: The repeat sales method is a means of constructing real estate price indices based on a repeated observation of property transactions. PCA repeat sales index: Baroni, Barthelemy and Mokrane (2007) use real estate capital returns and compare them to other returns calculated from economic or financial variables. To get real estate returns they use repeat sales transactions and compute their corresponding returns for the economic and financial variables. Then, each real estate returns are explained by the other returns, using a linear regression. Finally the index is estimated from the factors time series.In a first section, we describe the different methodologies and consider the risk taken into account in each index. In second section we describe the dataset which contains 1,000,000 transactions leading to more than 300 000 repeat sales observations on the Paris area during the period 1973-2005. In third section, we present the results on the return and volatility robustness to revision for the two indices. We conclude on the possibility of creating derivatives on these indices.