A Wavelet-Based Study of Systematic Risk: The Public Real Estate Markets Case
27 Pages Posted: 14 Jun 2018
Date Written: May 10, 2018
In this study, we examine the dynamics of real estate local and global betas using a novel approach - wavelet analysis on nine Asia-Pacific and the US public real estate markets from January 1995 to June 2016. Specifically, Wavelets are localized in both time and scale, and can be used to filter data up into different frequency components. We appeal to the continuous wavelet transform to estimate the two real estate betas across the usual three investment horizons (short-run, medium-term and long-run), as well analyze their dynamic causality relations in asset pricing from the time-frequency perspective. The main empirical insight is that both real estate local beta and real estate global beta coefficients have a time-scale tendency in sample real estate markets. Their joint market risk increases in the long-run at both the local and global levels. The causal relationship between the real estate local/global betas of the US and Asian real estate markets is the strongest at longer time horizons. Moreover, there is non-linear causal relationship between real estate global beta and real estate local beta in all three investment horizons, with a strong feedback relationship exists between the two real estate beta measures in the medium-term for 80% of the sample real estate markets. A better understanding regarding the implications for real estate capital market securitization and market integration at the local and international levels has become important because international financial markets have become increasingly interdependent with continuing liberalization of cross-border capital flows.
Keywords: real estate local betas, real estate global betas, wavelets, continuous wavelet transform, local stock market, global stock market
JEL Classification: F3, G15
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