We offer an explanation of why changes in house prices are predictable. Extending the static model in Leung and Tsang (2010), we analyze the housing market with loss averse sellers and anchoring buyers in a dynamic setting. A buyer's current offer price increases with the housing unit's previous purchase price, and the seller has the tendency to delay the sale of a housing unit that has a loss. We show that when both cognitive biases are present, changes in house prices are predicted by price dispersion and trade volume. Using a sample of housing transactions in Hong Kong from 1992 to 2006, we find that price dispersion and transaction volume are indeed powerful predictors of housing return. For forecasting both in and out of sample, the two variables perform as well as conventional predictors like real interest rate and real stock return.