Dynamic interdependence between the US and the securitized real estate markets of the Asian-Pacific economies
| DOI | https://doi.org/10.1108/JPIF-07-2018-0048 |
| Pages | 92-117 |
| Published date | 09 January 2019 |
| Date | 09 January 2019 |
| Author | KimHiang Liow,Xiaoxia Zhou,Qiang Li,Yuting Huang |
| Subject Matter | Real estate & property,Property management & built environment |
Dynamic interdependence
between the US and the
securitized real estate markets of
the Asian-Pacific economies
KimHiang Liow
Department of Real Estate, National University of Singapore, Singapore
Xiaoxia Zhou
School of Finance, Shanghai University of Finance and Economics,
Shanghai, China, and
Qiang Li and Yuting Huang
Department of Real Estate, National University of Singapore, Singapore
Abstract
Purpose –The purpose of this paper is to revisit the dynamic linkages between the US and the national
securitized real estate markets of each of the nine Asian-Pacific (APAC) economies in time-frequency domain.
Design/methodology/approach –Wavelet decomposition via multi-resolution analysis is employed as an
empirical methodology to consider time-scale issue in studying the dynamic changes of the US–APAC
cross-real estate interdependence.
Findings –The strength and direction of return correlation, return exogeneity, shock impulse response,
market connectivity and causality interactions change when specific time-scales are involved. The US market
correlates with the APAC markets weakly or moderately in the three investment horizons with increasing
strength of lead-lag interdependence in the long-run. Moreover, there are shifts in the net total directional
volatility connectivity effects at the five scales among the markets.
Research limitations/implications –Given the focus of the five approaches and associated indicators,
the picture that emerges from the empirical results may not completely uniform. However, long-term
investors and financial institutions should evaluate the time-scale based dynamics to derive a well-informed
portfolio decision.
Practical implications –Future research is needed to ascertain whether the time-frequency findings can
be generalizable to the regional and global context. Additional studies are required to identify the factors
that contribute to the changes in the global and regional connectivity across the markets over the three
investment horizons.
Originality/value –This study has successfully decomposed the various market linkage indicators into
scale-dependent sub-components. As such, market integration in the Asia-Pacific real estate markets is a
“multi-scale”phenomenon.
Keywords Non-linear Granger causality test, US and Asian-Pacific securitized real estate markets,
Dynamic integration, Return and volatility connectivity, Time-frequency domain, Wavelet decomposition
Paper type Research paper
1. Introduction
Understanding the degree of interdependence between national real estate markets and the
nature of their relationship have implications for market stability and international
diversification, particularly when securitized real estate has become a major capital asset
component of the domestic stock market in many economies. This is because this emerging
asset class has displayed competitive returns and low correlation with the other asset
classes. Its long-term inflation hedging capacity also makes it an increasingly attractive
Journal of Property Investment &
Finance
Vol. 37 No. 1, 2019
pp. 92-117
© Emerald PublishingLimited
1463-578X
DOI 10.1108/JPIF-07-2018-0048
Received 12 July 2018
Revised 27 September 2018
Accepted 28 September 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1463-578X.htm
The first author wishes to acknowledge the financial support provided by NUS on the research project
R-297-000-132-646 which this paper is related to.
92
JPIF
37,1
asset class to invest. However, in contrast to the stock market, it suffers from small market
size, low market immaturity, as well as more speculative behavior and market instability.
Lizieri and Satchell (1997) found that stocks of securitized real estate assets are stocks in the
short-run; but that they are real estate in the long-run. Moreover, Ling and Naranjo (2002)
observed that securitized real estate has become increasingly less sensitive to common
stocks in some countries in recent years. Therefore, a specific focus on international
diversification of securitized real estate markets may be warranted. The current study
revisits the interrelationship between the US securitized real estate market and the national
real estate markets of each of the nine Asian-Pacific (APAC) economies (Australia: AU,
China: CH, Hong Kong: HK, Japan: JP, Malaysia: MY, Philippines: PH, Singapore: SG,
Thailand: TH and Taiwan: TW) by investigating the dynamic linkages between those
markets in time-frequency domain. In this paper, wavelet decomposition via
multi-resolution analysis (MRA) is employed as an empirical methodology to consider the
time-scale issue in studying the dynamic changes in the US–APAC cross-real estate
interdependence. In so doing, this paper adds itself to an understanding of the varying
time–frequency relationship of the two markets, an issue which has not been addressed
sufficiently in previous empirical studies.
With internationalinvestors who are heterogeneousin their trading strategies and operate
on their time horizon, C andelon et al. (2008) argued that the study of stock market
dependence should consider the behavioral differences between the short-term and
long-term traders. The presence of both short- and long-term market participants is a fact
of life in the investing world (McNevin and Nix, 2018). Similarly, in the real estate market
context, Zhou (2012) noted that international investors tend to be heterogeneous in their real
estate trading strategies and that each group of investors operates on different time horizons
to achieve their investment objectives. Consequently, the cross-market correlation, the
transmission of volatility shocks and the causal relationship between the securitized real
estate markets studied can be different at each time-scale. While speculative
traders/investors are more interested in gathering market linkage information at short
scales, large institutional investors operate on predominantly large scales for their strategic
portfolio decisions. In this regard, wavelet-based time-frequency analysis can be used as an
essential tool in analyzing the complex relationship in market dependence across different
investor groups (Gençay et al., 2001). For instance, an earlier study by Lee (2004) used to
decompose the stock market returns into different scale components (crystals). The author
then employedOLS to examine volatility spillover between theKorean and US stock markets.
The main objective of using the discrete MRA of the wavelet transform is to represent
the variability of the dependence structure of a stochastic process on a scale-by-scale basis
(Reboredo and Rivera-Castro, 2014). The maximal overlap discrete wavelet transform
(MODWT) is an improved version of ordinary DWT, being highly redundant,
non-orthogonal transform and can handle any sample size and not only those that are
multiples of 2×. The wavelet filter is the Daubechies least asymmetric (LA) filter of length
L¼8 (LA (8)). The MODWT draws on MRA to decompose a time series into lower and
lower levels of resolution. These levels of multi-resolution decomposition (MRD) are referred
as scales in wavelet studies.
The main contribution of this study lies in combining wavelet analysis and MRA
correlation, return exogeneity, connectedness, impulse response and causality models in
understanding and detecting market integration from the US securitized real estate markets
from the “aggregate”and “multi-scale”perspectives[1]. Overall, the empirical results show
that this study has successfully decomposed the various market linkage indicators into
scale-dependent sub-components. As such, market integration in the APAC real estate
markets is a “multi-scale”phenomenon. Consequently, investors with different appetites for
investment horizons can utilize this detailed information to determine theirtrading behavior.
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US and the
securitized real
estate markets
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