Exchange Traded Funds (ETFs), including the innovative leveraged (long and inverse) types, and the ever more creative traditional versions, are accelerating in popularity as preferred investment and trading vehicles. Real estate, a major investment sector, has been made more accessible through these tools. This study investigates if the introduction of real estate ETFs is impacting the volatility of their underlying real estate stocks. Tests conclude that the introduction of leveraged (long and inverse) and traditional real estate and real estate related ETFs, linked to the Dow Jones US Real Estate and Financial Indices and the leveraged (long and inverse) ETFs, benchmarked to the Russell 1000 Financial Services Index, significantly increased the volatility in their component real estate stock prices. The leveraged ETFs tied to the Dow Jones US Real Estate and Financial Indices caused the highest volatility, approximately tripling the volatility in the underlying real estate securities. Traditional ETFs were second, causing slightly more than a 70% increase in volatility, while the leveraged ETFs linked to the Russell 1000 Financial Services Index, having induced a 50% increase in volatility, were third. The increased volatility could not be attributed to any other external event.

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.

This study examines the impact of United States monetary policies on domestic mortgage rates, incorporating a holistic set of macroeconomic variables in its analysis. Two obstacles have prevented this integration in the past: the data gap in the federal funds rate during the zero lower bound (ZLB) period; and the utilization of a single equation rather than a system of equations to model the relationship between the mortgage rate and its determinants. First, we establish that the shadow federal funds rate introduced by Wu and Xia ( 2015 Wu, J. , & Xia, F. (2015). Measuring the macroeconomic impact of monetary policy at the zero lower bound (Working Paper No. 13-77). The University of Chicago Booth School of Business. [Google Scholar] ) is a valid proxy for monetary policy during the ZLB period, and we use dimensionality reduction to create proxy variables for important macroeconomic measures. Second, we utilize the generalized impulse response approach to measure in level and first difference the impact of monetary policy and the macroeconomic environment on the long-term mortgage rate. Generally, the effect of macroeconomic variables outweighs that of monetary policy. In addition, omitting macroeconomics variables overestimates the impact of monetary policy on the mortgage rate in level and first difference. For example, shocking the first difference (level) of the federal funds rate by one standard deviation overestimates the impulse responses by 15% (51%) and the variance decompositions by 27% (37%). The current research implies that a noticeable increase in the mortgage rate is associated with an economic environment characterized both by tightening monetary policy and strong economic growth. Further, the impact of monetary tightening on the mortgage rate is expected to weaken if secular stagnation continues to prevail.

Proliferation of traded derivatives that relate to the same underlying—such as stocks, bonds, and credit default swaps (CDS) all tied to the value of an underlying firm—raises questions about which instrument leads the adjustment to a new equilibrium when information enters the market. In this article, the authors explore the issue of using CDS, bonds, and stocks of 10 financial firms before and during the crisis of 2008. Using a cointegration framework, they calculate each security’s contribution to overall price discovery. They find the stock market to be the most informative, followed by the CDS market, with the bond market least of all. Before the crisis period, about two-thirds of price discovery occurred in the equity market and about one-quarter in the CDS market. From fall 2007 through 2008, however, the influence from stocks dropped to about 50%, while the CDS market’s contribution increased to close to 40%.