We examine the major potential drivers of five international housing markets utilizing a quantile regression approach. In particular, we investigate property market dynamics during three variant market environments, namely, under downward (bearish), normal (median), and upward (bullish) trending conditions. Monthly data series for the United States, United Kingdom, Australia, Singapore, and Hong Kong are analysed, in an attempt to quantify uncertainty and detect trading patterns for the largest securitized real estate markets. We find that the stock market volatility, measured by the "pushing factor" VIXSamp;P500, provides agents with the most reliable and efficient information in terms of predicting market returns during bear market conditions, whereas "pulling factors" such as money supply, treasury yields, and unemployment explain the main stylized facts, incorporating contagion and diverse endogenous and exogenous shocks. Our work provides a richer understanding on comovements in house prices, allowing policy makers to anticipate shocks in global markets in a timely manner.