Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return

TL;DR

This paper introduces a novel housing risk index based on time-varying volatilities of U.S. housing variables, which predicts REIT returns and macroeconomic conditions, enhancing asset pricing models.

Contribution

It develops a new factor-based housing risk index using principal component analysis of housing variable volatilities, integrating it into asset pricing models for better return prediction.

Findings

The housing risk index predicts REIT returns consistent with ICAPM.

Higher housing risk beta values observed during 2009-2018.

Housing beta forecasts macroeconomic and financial conditions accurately.

Abstract

This study examines how housing sector volatilities affect real estate investment trust (REIT) equity return in the United States. I argue that unexpected changes in housing variables can be a source of aggregate housing risk, and the first principal component extracted from the volatilities of U.S. housing variables can predict the expected REIT equity returns. I propose and construct a factor-based housing risk index as an additional factor in asset price models that uses the time-varying conditional volatility of housing variables within the U.S. housing sector. The findings show that the proposed housing risk index is economically and theoretically consistent with the risk-return relationship of the conditional Intertemporal Capital Asset Pricing Model (ICAPM) of Merton (1973), which predicts an average maximum of 5.6 percent of risk premium in REIT equity return. In subsample analyses, the positive relationship is not affected by sample periods' choice but shows higher housing risk beta values for the 2009-18 sample period. The relationship remains significant after controlling for VIX, Fama-French three factors, and a broad set of macroeconomic and financial variables. Moreover, the proposed housing beta also accurately forecasts U.S. macroeconomic and financial conditions.