The Relationship between Chinese Real Estate Market and Stock Market

By Gao, Xiaohui; Li, Jingyi et al. | Journal of International Business Research, January 2012 | Go to article overview

The Relationship between Chinese Real Estate Market and Stock Market


Gao, Xiaohui, Li, Jingyi, Gu, Anthony Yanxiang, Journal of International Business Research


INTRODUCTION

The real estate industry in China has boomed since 1998 (Fung, Jeng, & Liu, 2010). The real estate market is an important part of China's economy. Real property composes major part of social wealth. Real estate price index is one of national economy vanes. Meanwhile, Chinese stock market develops from a weak efficient market to a semi-strong efficient market, and becomes an important barometer of national economy. Research on interaction mechanism of Chinese real estate market and stock market will help investors choose reasonable assets and establish efficient portfolios, and help Chinese government carry out effective supervision on capital markets. For example, Chinese government should control the amount of "hot money" that flows into stock market in order to avoid stock bubble while squeeze real estate bubble.

This study applies time series analysis to divide Chinese real estate market into three sub-periods based on real estate sales price indexes from January 1999 to November 2009. ADF test, co-integration test, and Granger Causality test results show that the fluctuations of Chinese real estate prices and stock prices have stage correlation, in some sub-periods the real estate market led the stock market. It might provide helpful information for investors to establish effective portfolios and for Chinese government to make relevant policies.

LITERATURE REVIEW

The arguments about the relationship and interaction mechanism of real estate market and stock market are mainly divided into two sides: segmented or integrated. Liu, Hartzell, Greig, & Grissom (1990) researched the relationship between the U.S real estate market and stock market with asset pricing model and concluded that two markets were segmented. However, Ibbotson & Siegel (1984) analyzed the relationship between the U.S real estate prices and S&P 500 stock index and found the existence of negative correlation. Studies of Okunev & Wilson (1997), Okunev, Wilson & Zurbruegg (2001), and Ullah & Zhou (2003) showed the existence of correlation between the U.S real estate market and stock market, and the stock market played a leading role. Quan & Titman (1999) studied relationship between real estate prices and stock prices of 17 countries, and concluded there was significant positive correlation in the long run. Studies of Stone & Ziemba (1993), Liow (2006), and Shen & Lu (2008) separately showed positive correlations between real estate markets and stock markets in Japan, Singapore and China. Hence it is unclear whether real estate market and stock market are segmented or integrated.

METHODOLOGY AND EMPIRICAL RESULTS

Data Description

The monthly data of Chinese Real Estate Sales Price Index (CRPI) is selected to analysis Chinese real estate fluctuating cycles. Data is from China Economic Information Network Statistics Database.

Shanghai Composite Index HCPI and Shenzhen Component Index SCPI are chosen as the indexes to measure prices changes in Chinese stock market. HCPI and SCPI are published by Shanghai Stock Exchange and Shenzhen Stock Exchange.

In order to remove heteroscedasticity and reduce volatility, the indexes are made dimensionless and taken logarithm to get the corresponding new variables which are LCRPI, LHCPI and LSCPI.

Time Series Analysis and Test

The basic principle of time series analysis is that any economic time series can be composed of its first order differential sequence. To increase the symmetry of differential sequence, mean of all differential values are calculated. Then a new time series can be generated with the first order differences and the mean.

First, we define Y(t) as time series of Chinese real estate price index (CRPI). Then the first order differential sequence of Y(t) is generated:

Y[??](t)= Y(t + 1)- Y(t) (t = 1, 2, 3, ...., n) (n=131)

The results of ADF test indicate that Y[? …

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