摘要
在党的十九大号召防范化解系统性金融风险进程中,房地产作为国家支柱型产业,控制其财务风险尤为重要。本文以我国港股上市房地产企业为研究对象,综合已有研究创新性地构建出其专有财务风险评估指标体系,共包含23个财务指标;同时运用基于因子分析的Z值与Logistic回归分析模型进行实证检验,相比先前研究,此模型能更好地为港股房地产企业评估财务风险,且模型预测精确度也均有一定程度提升,最高可达88.5%。港股房地产企业可以将其财务数据直接代入评估模型以判断企业发生财务危机的可能性并识别影响财务危机发生的主要因素,从而帮助企业及时采取相应措施降低风险,具有较强的现实意义;同时也可以进一步丰富房地产企业财务风险模型构建方面的研究。
In the process of the 19th National Congress of the Communist Party of China to prevent and resolve systemic financial risks, real estate as a pillar industry of the country, controls its financial risk is particularly important. This paper selects the real estate enterprises listed in Hong Kong stocks as the research object, and synthesizes the existing judgment index system to construct a proprietary Financial Risk Assessment Index System suitable for the listed real estate enterprises of China's Hong Kong stock market, which contains 23 financial Indexes. At the same time, the Z-value of factor analysis and the logistic regression analysis model are empirically tested. Compared with previous research, this research model is better applied to assess financial risks for Hong Kong stock real estate enterprises, and the accuracy of model prediction can be improved up to 88.5%. For Hong Kong stock real estate companies, they can directly substitute the financial data of the company into these two evaluation models to judge the possibility of financial crisis and identify the main factors affecting the financial crisis, thus helping enterprises to take corresponding measures to reduce risks in time. It has strong practical significance;meanwhile, this paper also can further enrich the research on the construction of financial risk model of real estate enterprises.
作者
齐岳
蒋杉杉
宋莹莹
QI Yue;JIANG Shan-shan;SONG Ying-ying(Business School, Nankai University, Tianjin 300071)
出处
《财务与金融》
2019年第1期66-75,87,共11页
Accounting and Finance
基金
2015年国家自然科学基金重点项目"现代社会治理的组织与模式研究"(71533002)
2018年国家社科基金一般项目"金融创新背景下多目标公司治理投资支持实体经济研究"(18BGL063)
2017年天津市普通高等学校十三五综合投资规划专业建设项目
属省级教育教学研究项目
关键词
房地产
财务风险
风险评估
因子分析
回归模型
Real Estate Enterprises
Financial Risk
Risk Assessment
Factor Analysis
Logistic Model