This paper studies whether liquidity information is helpful to forecast future prices in the housing market. First, we construct a panel of indicators that measure housing conditions in the Netherlands and in one large suburban area of the Washington DC area. Besides average home prices, the indicators include (quality adjusted) mean and median time on the market, mean difference between list prices and transaction prices, share of transactions below the transaction price, among others. These statistics will be used to construct an index that measures seller's bargaining power and several indicators about housing liquidity. To estimate indicators that measure housing liquidity and sellerís bargaining power we will follow the methods proposed by Carrillo and Pope (2012) and Carrillo (forthcoming). Second, we test if the bargaining power index and the other measures of housing market conditions have any predictive power to forecast home appreciation rates. Conventional time-series models are used to explore the link between housing liquidity, sellerís bargaining power and the rate of change in home prices. This research has important implications for both the real estate industry and policy makers. Given the importance of the housing market and the availability of MLS data, the construction of such indicators on regular basis for all areas in the US, the Netherlands and other developed countries should be a relative straightforward task that could inform economic agents about market conditions. Improved forecasts and understanding of current market conditions should be of interest to home buyers and sellers (and their agents) who generally like to be informed about market conditions when setting their optimal marketing strategies and, of course lenders, the PMI industry, and even participants in the derivatives market. Information about seller's bargaining power and housing liquidity could also be relevant to investors and regulators because, it provides information about market risk and, more importantly, it could be a valuable input to predict future home prices.