The price in an efficient market can adjust to new information instantaneously to eliminate any arbitrage opportunities. Such a phenomenon is not always observed in the real estate market because of its unique charact...The price in an efficient market can adjust to new information instantaneously to eliminate any arbitrage opportunities. Such a phenomenon is not always observed in the real estate market because of its unique characteristics, which include fixed location, heterogeneity and low transaction frequency. Using housing and office market data of some major cities in China, this paper examines the return and risk characteristics in these markets and assesses market efficiency. It finds that a number of instruments, including lagged quarterly and annual excess returns and, to some extent, the measure of the deviation of price from the intrinsic value, predict future returns. Therefore, weak form and semi-strong form efficiency can both be rejected in these real estate markets. These empirical findings suggest that there is slow price adjustment in real estate markets in China, which may be attributed to inefficient information transmission systems and long searching time in the markets.展开更多
The purpose of this paper is to investigate the relationships among the variables, and how interest rate, unemployment, stock market, and consumer confidence affect housing market index （HM1） in the U.S.. We constru...The purpose of this paper is to investigate the relationships among the variables, and how interest rate, unemployment, stock market, and consumer confidence affect housing market index （HM1） in the U.S.. We construct vector autoregression （VAR） model with variables such as unemployment rate （UMR）, consumer confidence index （CCI）, the Dow Jones industrial index （DJI）, and interest rate, etc., to forecast the HMI. Our model and analysis show that U.S. HMI very sensitive to unemployment and interest rates. Every 1% moves in unemployment and interest rates will result in HMI to move in the opposite direction by 11.7% and 11.4% respectively. However, changes in CCI and stock mark index have only minor impacts on HMI--0.49% and 0.3%, changes for 1% fluctuation in CCI and DJI. Our research also shows that relationships among these variables associated with housing market are very stable in the long run.展开更多
文摘The price in an efficient market can adjust to new information instantaneously to eliminate any arbitrage opportunities. Such a phenomenon is not always observed in the real estate market because of its unique characteristics, which include fixed location, heterogeneity and low transaction frequency. Using housing and office market data of some major cities in China, this paper examines the return and risk characteristics in these markets and assesses market efficiency. It finds that a number of instruments, including lagged quarterly and annual excess returns and, to some extent, the measure of the deviation of price from the intrinsic value, predict future returns. Therefore, weak form and semi-strong form efficiency can both be rejected in these real estate markets. These empirical findings suggest that there is slow price adjustment in real estate markets in China, which may be attributed to inefficient information transmission systems and long searching time in the markets.
文摘The purpose of this paper is to investigate the relationships among the variables, and how interest rate, unemployment, stock market, and consumer confidence affect housing market index （HM1） in the U.S.. We construct vector autoregression （VAR） model with variables such as unemployment rate （UMR）, consumer confidence index （CCI）, the Dow Jones industrial index （DJI）, and interest rate, etc., to forecast the HMI. Our model and analysis show that U.S. HMI very sensitive to unemployment and interest rates. Every 1% moves in unemployment and interest rates will result in HMI to move in the opposite direction by 11.7% and 11.4% respectively. However, changes in CCI and stock mark index have only minor impacts on HMI--0.49% and 0.3%, changes for 1% fluctuation in CCI and DJI. Our research also shows that relationships among these variables associated with housing market are very stable in the long run.
