房地产上市公司盈利能力测算分析——基于因子分析和随机森林算法

Profitability Measurement and Analysis of Listed Real Estate Companies—Based on Factor Analysis and Random Forest Algorithm

摘要: 本研究旨在深入分析中国房地产上市公司的盈利能力，采用因子分析法和随机森林算法作为主要的分析工具。通过对2012~2023年119家A股房地产上市公司的财务数据进行综合评估，本研究识别了影响盈利能力的关键财务指标。研究发现，销售净利率在ROA和ROE中的特征重要性最高，强调了净利润与销售收入比率对盈利能力的核心作用。资产负债率对ROA的影响大于ROE，揭示了负债水平在资产回报率中的重要性。此外，本研究还探讨了房地产行业盈利能力的时间趋势和地域差异，发现盈利能力整体呈现先稳后降的趋势，并在不同地区表现出显著差异。基于研究结果，本文提出了针对性的管理建议，房地产上市公司应当优化风险管理、提升资产运营效率、灵活应对市场政策变化，并实施创新驱动与地域性战略布局。

Abstract: This study aims to deeply analyze the profitability of listed real estate companies in China, using factor analysis and random forest algorithms as the main analytical tools. Through a comprehensive evaluation of the financial data of 119 A-share listed real estate companies from 2012 to 2023, this study identified the key financial indicators affecting profitability. The study found that the net profit margin on sales had the highest feature importance in ROA and ROE, emphasizing the core role of the ratio of net profit to sales revenue on profitability. The asset-liability ratio had a greater impact on ROA than ROE, revealing the importance of the debt level in the return on assets. In addition, this study also explored the temporal trend and regional differences in the profitability of the real estate industry. It was found that the overall profitability showed a trend of stability first and then decline, and significant differences were observed in different regions. Based on the research results, this paper proposes targeted management suggestions. Listed real estate companies should optimize risk management, improve the efficiency of asset operation, flexibly respond to changes in market policies, and implement innovation-driven and regional strategic layouts.