流动资金需求测算方法研究

发布时间：2018-06-29 16:49

本文选题：流动资金需求预测 + 制造业企业　；参考：《中国工业经济》2016年05期

【摘要】：银监会在2010年颁布的《流动资金贷款管理暂行办法》中提出商业银行流动资金贷款需求测算公式。本文研究了银监会测算公式存在的问题,提出了从静态时点和动态新增两个角度进行流动资金需求量测算的新方法。首先,采用“宝钢股份”的财务数据说明了银监会方法和新方法的计算差异并发现仅用一个企业的计算结果很难证明两种方法在预测准确性上是否存在显著差异。然后,用A股制造业企业2010—2014年的大样本财务数据对两种方法的准确性进行了实证检验,从两种方法对资金需求的预测方向一致性看,新方法预测的准确率高于银监会方法,但两种方法的准确率均不高。本文进一步研究发现,上市企业存在较高比例的非理性流动资金借贷行为,这种行为干扰了预测准确性。剔除非理性行为干扰之后,两种方法预测准确率会明显提高,并且两种方法在准确率上的差距也显著缩小。本文的研究结论对商业银行改进流动资金贷款需求量测算办法和企业进行资金需求数量预测均具有重要意义。
[Abstract]:In the interim measures on the Administration of liquid Capital loans issued by the CBRC in 2010, the formula for calculating the demand for liquid capital loans of commercial banks is put forward. This paper studies the problems existing in the calculation formula of CBRC, and puts forward a new method for calculating the demand of liquid capital from the static point of view and the dynamic increase. Firstly, using the financial data of Baosteel, the paper explains the difference between the CBRC method and the new method, and finds that it is difficult to prove whether there is a significant difference between the two methods in the accuracy of prediction with only one enterprise. Then, using the large sample financial data of A share manufacturing enterprises from 2010 to 2014, this paper empirically tests the accuracy of the two methods. The accuracy of the new method is higher than that of the CBRC method. However, the accuracy of both methods is not high. In this paper, we find that there is a high proportion of irrational liquidity lending behavior in listed companies, which interferes with the accuracy of prediction. After eliminating the interference of irrational behavior, the prediction accuracy of the two methods will be improved obviously, and the difference in accuracy between the two methods will be narrowed significantly. The conclusion of this paper is of great significance for commercial banks to improve the calculation method of liquidity loan demand and enterprises to forecast the amount of capital demand.
【作者单位】：中国社会科学院工业经济研究所;中国社会科学院研究生院;
【分类号】：F275

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