MODELLING PRICE DYNAMICS IN THE HONG KONG PROPERTY MARKET

The property market in Hong Kong plays an important role in the political, social and economic life of this vibrant city. Understanding the dynamics of the market is essential to guide government policy making and investment decisions. Using data collected between 1993 and 2006, this study investigates the monthly returns, volatilities, and time-varying correlations in the residential, office, and retail property markets in Hong Kong. A vector autoregressive (VAR) model is used to examine the conditional mean, and a multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model is adopted to analyze the conditional variance. The dynamic conditional correlation (DCC) approach is utilized to specify the MGARCH model. All of the property types show strong auto- and cross-correlations, which indicates that the sectors relate to each other closely. All three sectors have higher volatilities when major political and economic events occur. The findings reveal the possibility of balancing investment portfolios between the three sectors in the Hong Kong property market. However, exposure to the residential sector may reduce the chance of investment diversification because of the higher correlation of this sector with the other property sectors.