（1）量化结论基于历史统计，如若未来市场环境发生变化不排除失效可能。 （2）政策对于信贷的引导可能领先于实物工作量表现，高频数据反应不及时可 能导致预测出现误差。 量化分析报告 2025 年 8 月社融预测：26928 亿元 2025 年 09 月 01 日 ➢ 我们从社融各子项的经济逻辑、高频数据、季节性特征等角度出发，于每月 月末进行社融预测。每月的社融数据通常由央行于次月 10-15 日公布，存在一定 的滞后性。在之前的报告《社融指标全解析与预测框架构建》中，我们构建了自 下而上的社融拆分预测框架，过去一段时间对社融的总量和结构给出了较为准确 的预测。 ➢ 预计 2025 年 8 月新增社融约为 2.69 万亿元，同比增加-0.34 万亿元，社 融 TTM 环比约为-0.91%；社融存量同比增速约为 8.88%。新增人民币信贷约 为 0.94 万亿元，同比减少 0.10 万亿元，其中居民中长贷新增 0.12 万亿元，企 业贷款和居民短贷增加 0.64 万亿元；政府债券净融资约 1.36 万亿元，同比减少 0.26 万亿元；企业债券净融资约 0.10 万亿元，同比减少 0.07 万亿元。 ➢ 从结构来看， ...

- The report constructs a bottom-up framework for forecasting social financing (社融) by analyzing sub-items based on economic logic, high-frequency data, and seasonal characteristics[1][8][9] - The framework includes predictive models for various sub-items such as enterprise loans, resident short-term loans, government bonds, and corporate bonds, using specific economic indicators like PMI, housing sales data, and high-frequency issuance data[9] - For enterprise loans and resident short-term loans, the model employs rolling regression with PMI and Tangshan steel plant capacity utilization rate as independent variables[9] - Resident medium-to-long-term loans are forecasted based on housing mortgage data and three-stage characteristics of housing sales[9] - Enterprise bill financing is modeled using a rolling regression with a 5-year window, taking discount rates as exogenous variables[9] - Government bonds are tracked using high-frequency issuance and maturity data, with adjustments for discrepancies in reporting standards[9] - Corporate bonds are forecasted using a 5-year rolling regression to reallocate weights, effectively reducing reporting discrepancies[9] - Foreign currency loans are predicted using a 3-month average, considering correlations with RMB exchange rates and US-China bond yield spreads[9] - Trust loans and entrusted loans are forecasted by tracking issuance and maturity disclosures, with additional judgment for infrastructure-related increments[9] - Non-discounted bank acceptance bills are estimated using a 3-year average due to the cessation of high-frequency data publication[9] - Non-financial enterprise domestic stock financing is forecasted by deducting financial enterprise portions from monthly net equity financing data[9] - Loan write-offs are predicted using values from the same period last year, considering significant seasonal effects[9] - Asset-backed securities (ABS) issued by deposit-taking financial institutions are tracked using high-frequency ABS net financing data[9] - The July 2025 forecast predicts new social financing of approximately 1.53 trillion RMB, a year-on-year increase of 760 billion RMB, with a TTM month-on-month growth rate of 2.05% and a stock growth rate of 9.11%[8][9][18] - Structural predictions for July 2025 include government bonds net financing at 1.18 trillion RMB, corporate bonds net financing at 390 billion RMB, and resident medium-to-long-term loans at 5 billion RMB[9][18]

- The report constructs a bottom-up framework for forecasting social financing (社融) by analyzing sub-items based on economic logic, high-frequency data, and seasonal characteristics. This approach allows for detailed predictions of both total social financing and its structural components[7][8] - The framework includes predictive methods for various sub-items such as RMB loans, government bonds, corporate bonds, and others. For example, RMB loans are forecasted using PMI and Tangshan steel plant capacity utilization rates as independent variables, while government bonds are tracked using high-frequency issuance and maturity data[8] - Specific predictive methods include rolling regression for RMB loans and corporate bonds, using past averages for items like foreign currency loans and entrusted loans, and high-frequency tracking for trust loans and ABS net financing[8] - The March 2025 forecast for new social financing is approximately 5.68 trillion RMB, with RMB loans contributing 3.78 trillion RMB, government bonds 1.53 trillion RMB, and corporate bonds 0.01 trillion RMB. Structural predictions also include detailed breakdowns such as enterprise loans, resident short-term loans, and resident long-term loans[8][16] - The report highlights that government bonds continue to drive social financing growth, while corporate credit shows signs of recovery. PMI data and real estate sales are used to support these predictions[9]