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ABSTRACT
This study uses bivariate dynamic conditional correlations (DCC) to analyze REITs' relation with stock and bond markets from 1999 to 2018. The results show that the daily DCCs of both Equity REIT and Mortgage REIT returns experienced several structural changes attributed to the state of the economy, levels of leverage, inclusion or exclusion of REITs from the major S&P indices, and REITs getting their own Global Industry Classification Standard (GICS) category. To account for the structural changes, we allow the impact of the macroeconomic driving forces of the DCCs to vary over time. First, we formulate an OLS model using dummy variables regression (DV) to indicate regime membership, using endogenous break-dates. Then, we estimate a Markov regime-switching model (MRS) that allows the impacts of macroeconomic variables to differ during high and low variance regimes. Both complementary regime-sensitive models (DV and MRG) exhibit significant improvement relative to a traditional OLS model. The findings have significant implications for portfolio and risk management. For example, we find that with the new GICS sector, Equity REIT returns decoupled from the Financial Sector and the overall market as measured by the SP 500. These types of correlation shifts can significantly alter optimal portfolio weights whether trying to maximize returns, minimize risk, or achieving the highest risk-adjusted returns.
KEYWORDS
Structural changes; REITs; portfolio rebalancing; Markov-regime switching; dynamic conditional correlations
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Understanding the time-varying correlations among major asset classes is vital for active asset allocation, risk management, and hedging. To this end, we investigate the timevarying nature of correlations between the REIT markets and the equity (SP500) and bond markets. Our study documents many structural shifts (sub-periods characterized by different dynamic relations) generated by the state of the economy, levels of leverage, the inclusion or exclusion of REITs from the major S&P indices, and the new Global Industry Classification Standard (GICS) sector. While time-varying correlations can be explained by the small set of macroeconomic variables introduced by Yang et al. (2012) (i.e., default spread, term spread, mortgage spread, and the VIX), we more than double the Yang et al. (2012) sample period and allow the estimated intercepts and coefficients of these explanatory variables to vary across sub-periods when the dynamic correlations exhibit a structural shift. We...