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摘要
摘要
国民经济和社会发展“十四五”规划中提出推动基础设施领域不动产信托投资基
金（REITs）健康发展， 2021年 6月 9只基础设施领域的REITs基金上市，实现了
REITs在我国落地并发展。目前，大陆地区房地产领域的 REITs仍处于试点阶段，仅有
类 REITs，对其市场风险和发展规律有待深入认识。本文选择越秀、汇贤、春泉 3只在
香港上市的底层资产为大陆房地产的 REITs为研究对象，探讨宏观因素对其市场风险
的影响，并以神经网络法对其市场风险进行预测，为将来大陆地区房地产领域 REITs
的发展提供参考。
在文献梳理和分析、比较的基础上，本文选定了利率、CPI、工业增加值、就业水
平、股票价格、房地产市场行情等六个影响房地产领域REITs市场风险的宏观经济影
响因素，以在险价值作为房地产领域 REITs市场风险的衡量指标，用GARCH-VaR模
型计算 REITs在险价值。采用向量自回归模型（ VEC模型）分析各宏观经济因素对房
地产领域 REITs市场风险的影响程度。在前述分析基础上，将筛选出的重要影响因素
作为输入变量，将REITs在险价值作为输出变量，采用BP神经网络对房地产领域
REITs市场风险进行预测。
本文取得的主要研究结论有：一是房地产领域 REITs的市场风险在一定程度上受
到宏观经济因素的影响。在宏观影响因素中，利率波动对 REITs风险的影响较为显
著；房地产市场行情、CPI、经济波动对 REITs风险也存在一定的影响，但影响更小。
二是 BP神经网络可以实现房地产领域REITs市场风险的良好预测。基于上述研究结
论，本文对 REITs市场风险管控提出了关注关键宏观因素变动、开展REITs市场风险
监测预警工作、建立健全风险监管机制等建议。
关键词：REITs；市场风险；VAR模型；BP神经网络
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Abstract
Abstract
In the 14th Five-Year Plan for National Economic and Social Development, it is
proposed to promote the healthy development of real estate investment trusts (REITs) in the
field of infrastructure. In June 2021, 9 REITs in the field of infrastructure were listed,
realizing the landing and development of REITs in China. At present, REITs in the real estate
field in Chinese mainland are still in the pilot stage, with only analogous REITs, and their
market risks and development rules need to be deeply understood. This paper chooses Yuexiu,
Huixian and Chunquan, whose underlying assets from mainland real estate and listed in Hong
Kong, as the research object.Then this paper discusses the influence of macro factors on their
market risks, and predicts their market risks by using BP neural network method, providing
reference for the development of REITs in the real estate field in Chinese mainland in the future.
On the basis of literature review, this paper selected six macroeconomic factors affecting
the market risk of REITs in the real estate field, including interest rate, CPI, industrial added
value, employment level, stock price and real estate market. Value-at-risk(VaR) is used to
measure the market risk of REITs in real estate field and GARCH-VaR model is used to
calculate the value-at-risk.Vector autoregressive model (VEC model) is used to analyze the
impact of macroeconomic factors on REITs' market risk in real estate field. On the basis of
the above analysis, the screened important influencing factors are taken as input variables, the
value-at-risk of REITs is taken as output variables, and the BP neural network is used to
predict the market risks of REITs in the real estate field.
The main conclusions of this paper are as follows: First, the market risk of real estate
REITs is affected by macroeconomic factors to a certain extent. Among the macro factors,
interest rate fluctuation has a significant impact on the risk of REITs. The real estate market,
CPI and economic fluctuations also have a certain impact on the risk of REITs, but the impact
is smaller. Secondly, BP neural network can achieve a good prediction on REITs' market risk
in real estate field. Based on the research conclusions, this paper puts forward some
suggestions for REITs' market risk control, such as paying attention to the changes of key
macro factors, carrying out REITs market risk monitoring and early warning, and improving
the risk supervision mechanism.
Keywords: REITs, market risk, VAR model, BP neural network
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