دانلود رایگان مقاله همبستگی های زمان گرا در بازارهای املاک و مستغلات جهانی: GARCH چند متغیره با رویکرد اثرات فضایی

Abstract

The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

5. Conclusions

In this study, we have employed the MGARCH with spatial effects approach to examine the daily returns of 15 national property market indices from January 3, 2002 to May 31, 2016, taking into account the structural breaks of each time series linked to the recent GFC from 2007 to 2009. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models, like DCC–GARCH models. The main findings are presented as follows.