UROP Project Listing System
Project Title:
An Empirical Study of Real Estate Investment Trusts (REITs): Experience from United States, Hong Kong and Singapore
Supervisor:LI Kai
Project Description:To curb the over-heated real estate market, the Chinese government declared that “houses are for living in, not for speculation” and started the campaign to develop rental housing markets. These new policies call for a new property financing tool and raises the expectations for residential and commercial REITs (Real Estate Investment Trust). REITs are a collective investment scheme that sells shares in a trust that owns a collection of buildings, and are potentially important financing tools for developing the rental housing markets. REITs are still greatly under-developed in mainland China, but there are already a lot of successful experience from United States, Hong Kong and Singapore. The main purpose of this project is to: (1) provide a comprehensive study of the structure and design of the REITS in United States, Hong Kong and Singapore; (2) to empirical analyze their historical price patterns as a distinctive asset classes; (3) provide possible policy suggestions on the introduction and development of REITs in mainland China.
Course type: UROP1100 UROP2100  
Applicant's Roles:1. Basic literature review and collect some institutional background information; 2. Collect the historical pricing information for selective representative REITs in United States, Hong Kong and Singapore; 3. Conduct preliminary empirical analysis under the supervisor's guidance.  
Applicant's Learning Objectives:1. Develop a deep understanding of the design, operation and mechanism of REITs. 2. Gain valuable experience in empirical asset pricing analysis and working with programs such as Stata, R or Excel. The ideal candiates should have: 1. Trainings in undergratuate investment analysis or equivalent courses; 2. Good analytical, communication and interpersonal skills; 3. Strong self-motivation and willingness to learn; 4. Proficiency in English and Chinese; 5. Good knowledge of application software (Excel) and statistical software (R or Python or SAS or Stata) is a plus.  
Complexity of the project:Challenging 

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