Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building and Real Estate | en_US |
| dc.creator | Guo, Xinxin | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/6349 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Construction of real estate market early warning system in Guangzhou | en_US |
| dcterms.abstract | Real estate industry in China has made remarkable achievements since the reform and opening up. As a pillar industry, real estate is playing an increasingly important role in the national economy of the mainland China. In recent years, because the capital investment increased so fast in some cities in the mainland China such as Beijing, Shanghai and Guangzhou, real estate price rose rapidly, some abnormal phenomena such as "overheated", "abnormal heat" appeared in some degree and serious market risk existed in the real estate industry. Therefore, it is found important to construct the real estate market early warning system that can give signals for possible preventive actions. This paper analyzes the real estate market fluctuations and construction of the real estate early warning system in Guangzhou through theoretical analysis and empirical validation. Firstly, it summarizes the concepts, theories, methods and models in real estate cycle and real estate early warning. Secondly, it empirically analyzes the real estate cycle from 1995 to 2010 by using single index and composite index respectively on the basis of curve fitting and principle component analysis. The cycles of Guangzhou real estate market are found in short duration which are approximately three to four years long. In addition, to construct the real estate early warning system, yellow early warning method is adopted through selecting the real estate price growth rate as the warning factor indicator. Meanwhile, the composite index can be deduced by using cluster analysis and principal component analysis to select the warning signs and its weight respectively. Then the findings conclude that the patterns of composite warning signs and growth rate of average selling price of commodity housing are in similar trending. Besides, the 3δ method has been used to determine the warning limit to analyze the warning factor. Finally, cubic exponential smoothing method has been used to deduce warning factor and forecast the real estate market in Guangzhou, the predicted warning values in 2011 and 2012 are in the safety zone. | en_US |
| dcterms.extent | ix, 82 leaves : ill. ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2011 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Real estate business -- China -- Guangzhou. | en_US |
| dcterms.LCSH | Real estate development -- China -- Guangzhou. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b24629662.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.64 MB | Adobe PDF | View/Open |
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