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Title: | CYCLES AND COMMON CYCLES IN SINGAPORE REAL ESTATE, PROPERTY STOCKS AND THE MACROECONOMY | Authors: | LO, FEI HON | Keywords: | Real Estate Liow Kim Hiang Cycles Property Stocks Macroeconomy RE 2018-2019 RE |
Issue Date: | 13-May-2019 | Citation: | LO, FEI HON (2019-05-13). CYCLES AND COMMON CYCLES IN SINGAPORE REAL ESTATE, PROPERTY STOCKS AND THE MACROECONOMY. ScholarBank@NUS Repository. | Abstract: | Cyclical patterns in real estate markets has long been one of the key focal points of real estate research. To build on existing studies, this study stresses on the distinct sectoral characteristics of real estate market cycles in Singapore, by adopting spectral and co-spectral techniques to advance the understanding of frequency space correlation shared between various real estate asset markets and (1) the property stock market; (2) selected macroeconomic variables. In the short and medium terms, price movements in property stocks are more volatile than that in physical real estate markets. For the sample period 1984–2018, evidence from the coherency, cross-amplitude and phase spectra suggests that property stocks share significant but distinguishable price co-movements and lead-lag interactions with the four physical property asset classes (i.e. private residential, office, shop and industrial), particularly in the long term. The property stock market and the private residential market have the highest overall degree of coherency and the shortest time difference between them – a property stock lead of 1 to 2 quarters. Among physical property markets, the office and shop sectors share the highest overall coherence with a negligible time gap between them. In relation to the macroeconomy, the property stock market shares comparatively stronger correlation with GDP and Economic Policy Uncertainty of the United States (USEPU). The industrial market is the most tightly linked asset class with inflation rate. Finally, interest rates and money supply have little or zero coherence with price movements in real estate markets. Through the establishment of sharp distinctions in price co-movements among various real estate asset markets, this study aims to improve market forecasting and enhance existing real estate asset allocation models to help investors achieve optimal performance in multi-asset portfolios. | URI: | https://scholarbank.nus.edu.sg/handle/10635/221062 |
Appears in Collections: | Bachelor's Theses |
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