2026年1月社融预测：74432亿元

Investment Rating - The report provides a forecast for social financing (社融) in January 2026, estimating it at 74,432 billion yuan, indicating a year-on-year increase of 390 billion yuan and a month-on-month increase of approximately 1.09% [7][11]. Core Insights - The report emphasizes the importance of a bottom-up approach in predicting social financing by analyzing economic logic, high-frequency data, and seasonal characteristics. This method has previously yielded accurate predictions regarding both the total amount and structure of social financing [7][11]. - The forecast for January 2026 includes an expected increase in new RMB loans of approximately 53,100 billion yuan, with a year-on-year increase of 90 billion yuan. This includes 18 billion yuan in new long-term loans for residents and 56,600 billion yuan in corporate and short-term loans for residents [7][11]. - Government bond net financing is projected to be around 9,800 billion yuan, reflecting a year-on-year increase of 2,800 billion yuan, while corporate bond net financing is expected to reach 5,600 billion yuan, with a year-on-year increase of 1,100 billion yuan [7][11]. Summary by Sections Social Financing Forecast - The report predicts that the total new social financing for January 2026 will be 74,432 billion yuan, with a year-on-year increase of 390 billion yuan and a year-on-year growth rate of 8.28% for the total stock of social financing [7][11][18]. - The structure of social financing shows a recovery in corporate loans and continued strength in government bonds. However, new long-term loans for residents are expected to grow only modestly due to a decline in new home transactions in major cities [13][18]. Quantitative Framework - The report outlines a detailed quantitative framework for predicting social financing, which includes various components such as RMB loans, corporate financing, and government bonds. Each component is analyzed based on its unique characteristics and predictive variables [12][18]. - The framework utilizes historical data and economic indicators such as PMI and housing sales to forecast the different components of social financing accurately [12][18].